Scott Turner is most notable for his work on the Minstrel storytelling system. Minstrel is notable in terms of storytelling systems because it is one of the first, long with Liebowitz’s Universe, to employ a model of authorship and an author’s plans. Minstrel is also notable for its elaborate system for implementing creativity. The work is very tightly bound up in the rhetoric of traditional AI. The model of creativity works in terms of problem solving, and uses analogical reasoning to cast problem solving strategies from one domain into another.

While my work is not aimed at story generation, and my approach is very different, Turner is a useful perspective to keep in mind in terms of drama management, authorial goals, and creativity within story worlds.

Storytelling and Creativity

The problem as initially framed is an issue of story telling. Turner is interested in developing a computer program that can tell stories. Originally, this research began with finding a copy of Vladimir Propp’s Morphology of the Folktale, and then experimenting with the recombination of stories using Propp’s formal structure. Turner quickly found that Propp’s morphology, while it may be useful for understanding stories, is insufficient to instruct a computer to tell them. To tell or understand a story, it is necessary to have more than form, but a large network of information: author goals, reader expectations, and cultural knowledge. Turner turns his attention not to the makeup and content of stories themselves, but the process by which an author creates a story.

Developing stories involves thinking about the purpose and the message of the story, in addition to its form and content. This is one of the more innocuous claims that Turner makes, but it is arguably somewhat controversial. His goal is to rule out the idea of nonsense stories which do not employ causality or simply do not reach any kind of satisfying conclusion. However, many stories have messages, but those messages may not be clear or straightforward at all. They may be messages that require a great deal of interpretation, leading to diverse ranges of valid interpretations. Turner’s examples are simple, tending to employ very simple moral messages. In his defense, we have to start somewhere. It’s not possible to leap straight into a storytelling system that can write something along the lines of À la recherche du temps perdu without being able to write something simple first.

Storytelling requires a strong knowledge of not only the story, but the world in which the story takes place, the meanings of the terms and elements that occur within it. Minstrel uses an Arthurian world, where it is necessary for the storytelling system to understand what dragons and knights and princesses are, what it means for a knight to charge or be wounded, and what characters might be liable to do after some event. This does not mean understand in the sense of exact definition, but rather have a functional understanding of how these work within the story world.

Storytelling also requires creativity. This is the constraint that Turner issues which is the most remarkable. Creativity requires both the judgement of creativity, as well as an ability to be creative in the first place.

Minstrel’s architecture employs a problem solver, and treats the process of developing a story as a problem to be solved. Turner does not see this as a specialized process, used for scientific endeavors, but rather an everyday one. He claims that problem solving is invariant across problem domains, so the same problem solving method may be used in any domain, from astrophysics, to navigation, to grocery shopping. This argument is contestible, but through using it, he is able to make an interesting observation about how to use creativity. Creativity is the process of using knowledge or a method from one domain and applying it to another. In planning terminology, this involves an integrated process of search and adaptation. Experiencing a problem in one domain, the planner searches through other domains to find structurally similar problems, and then adapt them into the original domain. The interesting thing about this, for all the critiques of AI planning, is it is a method of thought that exists outside of conventional situational thinking, and is a reasonably effective means of producing creative solutions to problems.

The architecture that Turner uses involves extensively making use of author goals. There are four kinds of goals: thematic goals, consistency goals, drama goals, and presentation goals. In addition to employing creativity, the story must be able to satisfy these goals according to the author’s needs. Consistency goals are about producing consistent and causally sound stories, drama goals involve satisfying constraints to make the story dramatically interesting, such as having foreshadowing, suspense, and so on. Presentation goals aim to make the story clear and legible to the reader. Thematic goals are interesting to me, and I will address those in the next section.

A Model of Storytelling

Turner argues that storytelling is a matter of satisfying author goals. People write stories intentionally, for deliberate reasons. As such, the stories themselves have goals within them. To illustrate the importance of author goals, Turner looks at Meehan’s Talespin. Talespin does not make use of authorial intentions, and instead has only character plans and intentions. The Talespin stories are generally not too good, meandering and lacking purpose, and occasionally getting into infinite loops. Turner argues that storytelling requires more than mere simulation, and that authors are not merely simulators.

My goal in the adaptation project is not to tell stories, but make games. The challenge to simulation puts me on the defensive, but it is necessary to acknowledge that in order for there to be stories, there must be more than simulation alone. I would argue that what is missing from Talespin is some sense of values or meaning within the world. The example of the bear going to get berries is boring not because there is no authorial meaning, but because the actions and events are not meaningful to the reader.

One way of dealing with the matter of author goals I suppose is to challenge them in favor of reader goals. Authors may write bad stories that meander or go nowhere. The author may have goals which are uninteresting or nonsensical. The author may value these goals, but the readers may find them bewildering. This is not unusual, people write bad stories all the time. Merely having author goals is not enough to make a story interesting. The life of a story is not dependent on the author who writes it, but the community of readers who value it. This is a very important observation that should be made with literature of author goals in story planning.

The actual method of story generation in Minstrel is developed by planning and problem solving. The planner manages the author-level goals, and the problem solver works to find means of solving those goals. At the top level, Minstrel’s goal is to “tell a story”. As this proceeds, Minstrel will choose a moral, a theme, and then begins applying drama goals, performing consistency checks, and making the story presentable. It does this cycle for each scene in the story. This approach to story development is extremely top-down. The work is pioneering, but it is distant from the actual method by which a writer may actually compose a story. Writing involves iteration and revision of the entire work in cycles. I would argue that when the goals are established and some of the basic elements are introduced, the writer does perform simulation, to see what happens next. Minstrel achieves causality by looking backwards from an event and seeing what could have caused it. A real author will employ some of this approach, but will aslo use simulation to simply get causality by advancing time and playing it out.

The model presented is that stories have themes, where a theme is some sort of moral “lesson”. This is a contestible account of the reason behind storytelling, both within stories and of the reasons for writers to create stories. By employing diverse lessons to other storytelling domains, this suggests that the theme of a story and the world of a story can be separated unproblematically, which is false. Stories are culturally anchored, and themes may be conventionally bound to one set of story worlds. An example in the realm of Aesop’s Fables, which contain the kinds of lessons Turner is interested in, is the story of the And and the Grasshopper, which has a remarkably different ending as told in the West versus in Japan. Western culture is much more individually oriented, and focused on independence, whereas Japanese culture relies on interdependence and mutual support. Lifting themes from one domain to another may be creative, but it may also run the risk of cultural imperialism when done unawares.

Huizinga is one of the original voices in the study of play and games. Homo Ludens is his study of play in culture. The work is taken primarily as an anthropology of play, and Huizing is strikingly broad in his examination of play in different cultures. Much study of culture and philosophy in the West has limited itself to looking at history in Greece, Rome, and then Western Europe. Huizinga does explore these, but also reaches out to India, China, Japan, and the Blackfoot Tribe. For someone writing in 1938, this indicates some appreciable cultural diversity. Huizinga is perhaps notable for his coinage of the term “magic circle”, but his work is deeper than normally credited. His understanding of play is also wrapped up in conflict, which is a point of contention between him and other scholars. The ultimate manifestation and function of play to Huizinga is the resolution of conflict, which in turn creates social order.

Nature and Significance of Play as a Cultural Phenomenon

This chapter opens looking to understand the role of play within culture. Huizinga notes that play is older than culture, it is spread beyond merely the human species, as animals play. Play is clearly important, but it is unclear as to why we do it. Play must serve a function so that we can play at all. Play is elusive when attempting to ascribe some form of biological function to it, as it rejects and expands beyond any attribution posed onto it. The idea or concept of fun is equally elusive. Both the ideas of play and fun are linguistically problematic, because they mean very different things across languages and cultures. However, play itself exists independent of any name assigned to it, and independent of our understanding. Play is supra-logical and irrational.

The goal is to approach play as the player might percieve it. Huizinga’s goal is to look at play as a special activity within a culture, to see it within its context, not try to understand how it is conditioned from the outside. Our culture is permeated with play, from language, to myth to ritual. Each of these involves negotiating between that which is imaginary to that which is real. Language is a system of reference, and linguistic signs are different from their referents. The signs are, in a sense, not real (not concrete, anyway), and they relate to concrete things in the world. Myth interprets the physical world by explaining it in terms of the divine. Ritual connects meaning and concrete practices with symbolic practices. All of these are systems of play.

Play is difficult to classify in relation to other concepts. Huizinga makes the claim that play is the opposite of seriousness, but this proves problematic. Play can be serious, but his explicit assertion is that “Play is non-seriousness.” (p.5). This is different from claiming that play is not serious. Other things that are non serious are also not play, such as laughter, the comic, jest, and folly. Play cannot be classified morally (as good or bad), not can it be classified aesthetically. Play eludes classification and determination by other terms.

Play is voluntary. It may be deferred or suspended at any time. It involves stepping out of the “real,”  and as such it is in a position of inferiority to the “serious”. Play and seriousness exist in a cycle, where the ordinary world is suspended when the play begins, and resumes when it terminates. Play exists inside everyday life, but apart from it, existing in a special time and space. In time, it begins, goes on for some duration, and then finishes. Afterward, it is over, but exists as a memory, and may be re-enacted. In space, play occurs in special consecrated grounds that are set aside for the play to take place. This enclosure is what defines the magic circle. Examples of these sacred spaces are the playground, the arena, the card-table, the temple, the stage, the court of justice, and so on.

Within the circle, play imposes new rules, and creates order. This is counter-intuitive, as play is usually what breaks rules, but within its space, the rules of play are sacred. Deviation or breaking these rules spoils the game. Within the space, the course of play is enchanting and captivating. It is enthralling that it creates another world and, for lack of a better phrase, opens up a new form of consciousness. However, within this, there is an element of tension. Within the scope of the play, something is at risk, or the players want something to “go” or “go off” or simply happen. The player has some sort of motivation and objective. Due to this motivation and the possible outcome, an ethical dimension arises in the play. Even though play itself transcends morality, within the scope of play, there is a moral structure, determined by the rules of play.

The moral structure connects the performance of the player to the player’s adherence to the rules. It is morally important to abide by these rules and still meet the goals. A player who is a cheat still operates within the space of the rules. Even though the cheat breaks the rules, it is in order to win. The person who ignores the rules brazenly and does not act to win is something worse (like the parent who dismantles the pillow-fort, or the dog who runs onto the soccer field), because they have violated the sacred order of the magic circle. Breaking the rules reveals the fragility of the play itself. Huizinga explains that play is robbed of its illusion, which literally means “in-play”. This is notable for several reasons. The first is that illusion is an interesting word for capturing the believability of the world of play, as compared to, say immersion. A player who experiences immersion may still be aware of the fact that the world is imaginary, whereas the player experiencing illusion is seeing the world of play as of foremost importance.

The Play-Concept as Expressed in Language

In this chapter, Huizinga looks at the terms for play as expressed in different languages and cultures. The uses of the terms for play are quite diverse. One of the earlier distinctions is between the Greek terms paidia and agon. The term paidia represents the childish sense of play, as in things that are non serious and lighthearted. The other term, agon, is about contest and conflict. This is the term Huizinga is primarily interested in, as it denotes contests and competitions which were of great importance in Greek life. Agon is, incidentally, the root that gives us “agony,” so its connection to games is of a much more serious nature.

Huizinga investigates several other languages, and finds that there is a large diversity in terms, but different terms separate the agon/paidia difference with some frequency. These terms are discussed on the Wikipedia page for Homo Ludens. At the end of the chapter, he examines the words for seriousness or earnestness in these languages as well, although this proves to be problematic as finding the opposite of play is difficult linguistically. Huizinga concludes with a point that helps clarify the relationship between seriousness and play.

Leaving aside the linguistic question and observing the play-earnest antithesis somewhat more closely, we find that the two terms are not of equal value: play is positive, earnest negative. The significance of “earnest” is defined by and exhausted in the negation of “play”–earnest is simply “not playing” and nothing more. The significance of “play”, on the other hand, is by no means defined or exhausted by calling it “not-earnest”, or “not serious”. Play is a thing by itself. The play-concept as such is of a higher order than is seriousness. For seriousness seeks to exclude play, whereas play can very well include seriousness. (p. 45)

Play and Contest as Civilizing Functions

Culture arises from play, but in doing so, it takes on the form of conflicted play. “The view we take in the following pages is that culture arises in the form of play, that it is played from the very beginning. Even those activities which aim at the immediate satisfaction of vital needs–hunting, for instance–tend, in archaic society, to take on the play-form.” (p. 46) The use of play is used in negotiating conduct within a group, or between two opposing groups. The agon form of play is epitomized in the contest, and it is frequently through these sorts of contests, that order is established within the culture. Winning and losing within a play contest is usually merely symbolic, but the meaning of the win or loss is interpreted concretely within the culture.

Play contests establish a social order. The stability of the society comes from a defined order, which is determined by contests demonstrating some kind of strength. The leader of a group would be the one who is superior in some form or another. Social heirarchy may be demonstrated through playful displays. I find this claim very odd, though. Within interactions, I would agree that these take on playful forms and the interactions may be seen as contests of some kind, but to argue that entire cultures are ordered according to this play seems far fetched. The rules for defining victory and the resulting order must be consented upon or at least accepted, especially for the victory to be connected to any kind of ethical or moral superiority in the culture itself. This would indicate the need for protocols to determine social order by these playful forms, but it is ambiguous as to what forms these might take.

Play and Law, Play and War

These are two chapters which explore both the practice of law and the practice of war as playful social constructions. They exist outside of the scope of everyday life, they operate in special environments where there are special rules, yet both are still serious with real consequences. Regarding war, Huizinga qualifies his claim by indicating that it is a cultural function only when the members regard each other as antagonists with equal rights.

Overview

In order to adapt a fictional world, it is necessary to adapt the world’s model. Discerning and constructing a model is a complex and delicate act, and it requires creativity and agency. This process, as a subset of adaptation, falls within the broad category of translation. Modern theories of translation are varied, but to guide my approach to adaptation, I will borrow from the position popularized by Itamar Even-Zohar and Gideon Toury that a text should be understood as having a relationship and life within a culture, and that to translate a work is to continue that text through time. Adaptation specifically not only continues the text through time, but also through media. Adaptations subject texts to the affordances and constraints of different media, letting the source text not only live in a new era, but also be seen in a new light, from many perspectives. Throughout these translations and adaptations, there is something, some essence of the original text that is preserved. That essence is the model that underlies the world in which the text takes place. Model is a term that I am borrowing from mathematics, indicating a formal and causal structure which illustrates the values and possibilities of the world, of which the course of the text is but one outcome.

The particular perspective that I am espousing for this particular work, Jane Austen’s Pride and Prejudice, is that of a videogame. This is, a seemingly unusual direction to take Austen’s work, but there are many reasons why such a project is a viable, and even ideal. I will start with the political reasons, as these are my driving motivations on this project.

Political Motivations

Genre is a significant problem with popular games. Many if not most games developers feel limited to a few narrow genres that seem to dominate the medium, especially in consumer publications. Games that are not sports, first person shooters, massively multiplayer, simulation, real time strategy, rhythm games, Japanese style roleplaying, fantasy adventures, or platformers, tend to be cast as oddities. This brief list includes genres that are defined both by mechanics, interaction, as well as themes, which is fine because this is largely how games tend to be marketed. The domains of political and casual games are important and growing, but are still popularly considered outliers. This casting does not prevent new genres for forming or becoming popular. Both Guitar Hero and Grand Theft Auto 3 were medium defining products. However, there is still a prevalent sense within the game industry that genre boundaries cannot be blurred. This restraint is severely limiting to developers and presents a new subset of problems.

In the case of adaptation, many games are adapted from fiction and film, a tradition that goes back all the way to the Atari 2600 days. This practice remains strong today, and one of the chief expenses of the mainstream game industry is purchasing the rights to intellectual property. However, among these games, the genres are even more narrow. Almost all games that are adapted tend to be action style games, adapted from action or adventure films, with elements of shooters or platformers. In terms of the scope of possible adaptations, this field is extremely narrow. While Joseph Campbell’s monomyth is broad, it is far from universality or majority in culture. Many films and narratives are made which exist outside of this tiny scope. These remain inaccessible until new methods for adaptation are formed.

Not all games aspire towards artistic expression, and not all game developers or designers see art practice as the essence of their work. I think that they would consider games a medium though, and while expression may not be a central goal of creating an artifact in a medium, it is a consequence. A vocal subset of game designers have realized that this expression something over which they can exert authorial and artistic intent, and have encouraged games acceptance to this end. Some of these practitioners have created works with wild success, and while popular recognition of these artistic elements is growing, the community which is receptive to these artistic intentions is eclectic. Avant garde is a form of artistic practice which could never be popular due to its nature, but games must find some stage between popularity, entertainment, and artistic legitimacy in order to move forward.

The most searing indictment against mainstream games, at least in terms of legitimacy, is gender. Even beyond products marketed explicitly towards the “hardcore gamer” demographic, much of gaming community is composed of adolescent males, and this culture has created a perpetuating, misogynistic environment that is actively hostile to women. A medium cannot attain legitimacy if it excludes half of the population, and the juvenile culture and reputation only harms the chances of games being taken seriously as a medium. This indictment applies to the mainstream game industry, as notable exceptions occur with products such as The Sims and the category of casual games.

Adaptation of sources that lie outside of the narrow genres of action and adventure, specifically those in traditionally female dominated narratives is the answer to unlocking the puzzle of genre and legitimacy.

But: Why Jane Austen?

Jane Austen is an unlikely but surprisingly ideal candidate for adaptation. One of the reasons for this is because her books have a strong history of adaptation. In fact, there seems to be an entire culture built around recreating the works of Jane Austen. Despite her reputed stuffiness, her works and the adaptations thereof are unexpectedly mainstream. We feel this influence most strongly in film, especially in explicit adaptations which are set historically. There are also a number of works which are adaptations, but cast Austen’s values in contemporary settings, where they remain surprisingly coherent. Examples of these contemporary adaptations are the 1995 film Clueless, and Helen Fielding’s book Bridget Jones’s diary. These adaptations are important because they do not cast Austen’s world in terms of its representational elements, but rather, in terms of its values and mechanics.

The other remarkable quality of Austen’s world is that it has had a propensity for extension. Austen was succeeded by a number of other authors (although admittedly much less talented), who saw fit to write sequels to her novels. This practice may be thought of as a sort of contemporaneous fan fiction. This sort of extension is not unique to Austen, especially as there are other authors, especially in pulp fiction who collaborated and built upon each others’ worlds. A good example of this practice comes from H.P. Lovecraft, whose contemporaries extended his world as well as his particular style and formula for writing. Austen’s culture of adaptation can be thought of as extending her world and values.

A final reason why Pride and Prejudice (and Austen in general) is an ideal candidate for adaptation comes from the structure of the book itself. The plot of the story revolves around Elizabeth Bennett, the second of five daughters. The problem with this situation is that the family property has been entailed, meaning that it must pass to a male heir. Thus, whenever Mr. Bennett dies, then the entire family will be without property and cast into poverty. This premise sets up a perfect stage for a game. The player, as Elizabeth Bennet, must navigate a social landscape, make careful choices, and attempt to become successful in the world’s three currencies: money, status, and love.

Despite the textual nature of Austen’s writing, her world continues to be popular and engaging. The culture of adaptation surrounding Austen suggests that her world continues beyond the form of the novel in which it was first revealed to us. If we are to adapt Austen, we must adapt her world, and to do that, we must adapt the world’s model. In this process of adaptation, we aim to transfer the essence, the living matter that makes Austen’s world so vibrant, from one medium into another. This new medium has its own affordances and structures, so the transference must be extremely careful, in order to find ways that the source can be well connected to the new medium. The model of Pride and Prejudice is well suited to adaptation into game mechanics. But in order to see precisely why this is the case, it is necessary to examine the model of the world in detail.

The Model and Mechanics of Pride and Prejudice

If we believe that Austen’s world has a model in the first place, then it must be expressible in some sort of formal and relational structure. I use the term model in the sense borrowed from mathematics. I will not examine a comprehensive definition of models in this paper, but I will rather use a loose one. A model is a formal structure (meaning that it can be written down mathematically or programatically) which describes the states and possible behaviors of a system. The notion of system as used here is very broad, denoting the entire story world, including all of its characters, places, and events. In this section, I want to focus on the mechanics, specifically. This is the aspect of the model that informs how states change and what sorts of things happen.

To think about mechanics in a literary world is to think about the sorts of things that happen in that world. There are two issues at stake with this: One is to look at climactic or dramatic events, and the other is to look at the mundane, everyday events. A accurate portrayal of mechanics must involve both. In many projects to explore dramatic domains, the focus has been to examine dramatic events only. Narrative tends to exert a sort of dramatic compression, where a lot of information, the boring content that is unnecessary or distracting from the dramatic elements is excised. Story generation programs struggle with this, because computationally there is a fine line between dramatic compression and incoherence. However, within texts, there are backgrounds, and it is these backgrounds that help fill in and flesh out the world, making it engaging and believable. In a world that is simulated, the relationship between dramatic and mundane events resembles the relationship in film rather than the stage. Backgrounds are fleshed out with participating individuals, but only a few take up focus.

some sort of negotiation and compromise between dramatic and mundane elements to the world must be employed. If all mundane elements are removed, then the story will devolve into a plot, which would be dry, formulaic, and removed from the elements of the living world. If there were no compression at all, the matter of relevance and significance of events would be muddled among a blur noise and tangential events. Thus, both dramatic events and non-dramatic events must be at play in the model. Non dramatic events tend to fill in the background, to create a sense of environment, in which the dramatic events are situated. In his essay “Where the Action Is” Erving Goffman gives a typology of actions: Actions are either consequential or inconsequential, and they can be either problematic or unproblematic. Dramatic actions are consequential and usually problematic. Mundane actions are unproblematic.

Characters also adhere to an elaborate social code. Social interaction has a scripted and ritual structure. These rituals range from the small and simple, such as a conversation, a meal, or a card game, to the moderate, a social visit, or an extended visit, a ball, to the very broad, of which the best and primary example is courtship. These rituals have an explicit structure, and are understood as symbolic elements of the literary world, but they are also flexible. What is important in a simple ritual is partly the significance of the ritual itself, but also (and primarily) the conduct of the characters involved. Additionally, some rituals may include choices, and there are methods and formulas for making those choices that are consistent with the ritual structure. Rituals may be violated, and while it is rare in short rituals, moderate and extended ones experience all manner of violations, which is the cause of a great deal of social distress and embarrassment. I mentioned earlier that the three forms of currency in Pride and Prejudice are money, love, and status. Status is harmed by erring in or violating these rituals.

Ritual can be well understood using the language of performance, especially as explored by Goffman and Schechner. Given other performance oriented theories relating to computation, digital media, and roleplaying games, this seems like an appropriate tool to use. Goffman’s theory of performance also lays out mechanics for the functions of deference, demeanor, and embarrassment. These theories place great emphasis on conduct and enactment, which seems to be in key with the way that characters must act in Austen’s literary world.

To model the mechanics of a fictional world, we must understand what things can happen within the world. In this section, we have outlined an approach to looking at how things happen, using the method of performance.

Being There

In the overall goal of adaptation of a story world into a game, the reader must be transformed into a player. It is possible to give the player the seat of a spectator, where the world unfolds and takes place, giving the player control over certain influences, or direct control over all of the characters, much like in The Sims, but that does not seem consistent with the way in which Austen’s world is adapted in practice. The practice of adaptation aims to recreate an experience of the world. Thus, the player must exist and dwell within the world, taking control over a character, and have a stake in what happens to that character within the course of the game. Pride and Prejudice fortunately gives us a character, Elizabeth Bennett, who happens to not only be the protagonist, but also have very unclear motivation throughout the story. Elizabeth Bennett is the clever daughter who has principles, but no explicit goals, in contrast to the rest of the cast, all of whom have very well defined goals.

The experience of being a character situates the player within the world, within a structured environment. By virtue of being a character, the player must have a great deal of freedom, but is also limited significantly by what is possible within the story world. For example, there are a great many ways for a character to conduct herself that are consistent with the structure and expectations of the story world. It should be possible for the player to do almost anything that the other characters do in the book. However, certain things that a game player could think to do might be well outside the scope of the story world. Players as a demographic tend to passionately explore all the possibilities and the extremities of game worlds, testing them to see how far they go. As a design goals, it should be possible for players to do anything that makes sense, but to disallow or provide consequences for anything that is too outlandish. Pride and Prejudice is a good example of a world that contains some of this sort of feedback within the world mechanics. There are strong social codes, and violating those codes will ruin a character’s status and reputation.

Introduction

The purpose of my research is to simulate fictional worlds. The challenge to be explored in this paper is the conflicted role of AI within this investigation. I argue that existing approaches to AI are insufficient to tackle this greater problem, and an approach to AI that addresses a social and cultural context is necessary beyond one that addresses individual agents. To understand why, we must closely look into the topic of simulating fictional worlds.

Specifically, my goal is to adapt fictional worlds into games. This grand project is rife with complexity and challenges. I can not hope to provide give a complete exposition on this problem, but rather, my aim is to provide a method or approach for looking at adaptation. The essence of adaptation consists of several steps, but my goal within this paper is to illustrate the challenges pertaining to developing the model of the fictional world, and thinking of it computationally.

It is not my intention to discuss the actual domain in much of the paper, but it is worth mentioning for reasons of contextualization. The narrative to be adapted is the novel Pride and Prejudice, published by Jane Austen
in 1813. While it would seem to be an odd and perhaps counter intuitive target for study, it is a rich domain and on close investigation is unusually well suited for the adaptation problem. The reasons for this are twofold: The first is that Austen has a community and tradition of adaptation. Her novels have been frequently adapted into film, and have spawned other literary adaptations and continuations. The second reason is that Pride and Prejudice has a surprisingly game-like story world. The world has the values of love, money, and social status. Characters interact socially at well defined social situations. They take part in cultural rituals of various scales: from a small scale ritual such as a card game, to a moderate scale ritual such as a social visit or a ball, to broad scale rituals such as courtship.

Let us explore the conceptual steps to looking at the picture of adaptation. First, we understand that fiction defines a world, not just an individual story. A world is the stage on which the plot of the story is enacted. The world itself is defined by a model. That distinction means that the fiction includes some details and excludes others, and lays out a scope of possibility for what can plausibly occur within that world. Building and interpreting the model is a creative act, and is by no means straightforward. Much like translation itself, interpretation is necessary, but subjective. Accepting that we can understand a story world in terms of a model, we can form a computational representation of that model.

The idea that fiction is foremost a world and secondarily a story ties into the work of narratologists David Herman and Marie-Laure Ryan [Herman 2004, Ryan 2006]. The actual narrative defines a sequence of events through the story world. As such, the resulting story is just one of many possible stories that could occur in the world. Furthermore, the writing shapes the nature and properties of the world through the language used. The last step wherein . This is the step that receives the least attention in this paper.

That a story world can be understood in terms of a model is essentially a structuralist claim, and it requires opening up the idea of what a model means. The word model implies a symbolic formulation of objects and rules. For the story world to be understood as a model, it must be first interpreted. The complexity and consequences of this interpretation is quite deep, and is explored in this paper. Once defined, though, it can represent the possibilities of the story world with some coherence. When used to analyze story worlds, models are generally understood vaguely, without explicit formalization.

My main concern for this paper is with the last step: Once we have a model of the story world, how can that be transformed into something that may be simulated computationally? Characters act according to the model of the story world, but exactly how they act and what they do requires some additional work. The field of AI seeks to provide a computational solution to the intelligence and behavior of characters. However, the traditional use of AI relies on assumptions which are inappropriate for the adaptation of fiction. We shall see many challenges posed by traditional AI. These challenges shall be matched with contrasting perspectives that reformulate the constraints of AI in a way that makes them usable for the adaptation of story worlds. This reformulation does not reject the use of symbolic AI, but changes the target of representation from the individual to the broader cultural system.

Cognition and Representation

Artificial intelligence has a detailed and intricate history shaped by many individuals and many different philosophical biases. AI is not a single ideology, it is a tradition shaped by many ideologies. There does exist within the discipline a strong current of particular ideas, which I shall call traditional AI. This is also known as “Good Old Fashioned AI”, or GOFAI, or just symbolic AI. GOFAI is a movement and perspective on computation and cognition that derives from the work of Newell and Simon. The heart of this is the physical symbol system hypothesis: “A physical symbol system has the necessary and sufficient means for general intelligent action.” [Newell 76]

A physical symbol system is essentially a formal model. The physical symbol system uses rules to operate on existing symbols and transform them into new ones. Such systems are symbolic abstractions of the Turing machine. Formal models are powerful tools, and will be employed to great effect later in this paper. However, the relationship between formal model and intelligent action is far more problematic than the physical symbol system hypothesis might first suggest.

The ostensible goal of AI is to provide a computational solution for intelligence. Exactly what this means ranges widely between AI applications. For expert systems, intelligence means an encyclopedic knowledge of a domain. For planners, it means the ability to formulate a plan for a successful course of actions within a particular problem domain or environment. AI applications tend to provide solutions for problems that could ordinarily be solved by a human individual. The intelligence as described by AI is significantly different from applied human intelligence.

AI still serves a valuable function, but to understand its value, we must examine the practice of AI, and what it aims to achieve.

While AI problem solving is intelligent, in the sense that it finds a solution for a complicated task, it is not the same as a human solving the problem. This distinction can be seen in several lights. One perspective on human problem solving is to view a human engaging with a problem as a whole system. The human is not one isolated mind, but an individual in a situation making use of situational affordances. Examples range between a mathematician proving a theorem, or an airplane pilot adjusting the speed of a plane [Hutchins 95, 98]. Even mathematicians, whose work is largely cerebral, make use of situational aids, such as paper or a chalkboard, and use culturally established conventions for conducting proofs. AI can not make use of these affordances, and an AI application is not substitutable for the human doing the problem solving. Instead, the AI represents the entire system, creating representations of the affordances used in memory. This is a distinction between representation and embodiment.

The practice of AI cannot hope to represent all of the interwoven parts demanded by an open approach to cognitive science. The vast sensory apparatus of human experience, replete with cultural and embodied meanings, would be nearly impossible to transform into a computational system. Even from a technical perspective, the human brain is far more distributed than today’s computers. Instead, AI is limited to represent very abstract elements of human cognition. Human activity that operates at a clear symbolic level can be performed computationally without duress. Activities such as these are rote calculations, theorem proving, navigation, path planning, and so on. These activities are embodied, but they may be interpreted and described at a symbolic level, and this is the level on which AI can operate.

However, this process of symbolic transformation is not a clear task. Even for a relatively straightforward application such as a path planner, how the path is represented symbolically can make a major impact on how the algorithm can be understood in context. For example, if the algorithm assumes that the planning agent already knows the environment in which it must plan, versus having it need to discover the environment dynamically. The agent may read in the data for the environment absolutely, or it may be limited in terms of what it can perceive (it may not be able to see around an obstacle, for instance). The environment itself may be represented as discrete or continuous space. These differences involve significant changes in the representations and symbols used within the model. All of these inform the discourse around the AI system.

Representation connects a model to the world, either the physical world, or the world of human meaning. For the purposes of building a simulation of characters, representation is a major element. For providing characters that are believable, that can be simulated to act like characters within actual fiction, intelligence is absolutely necessary. However, the role of intelligence is somewhat unusual. AI applications are built around problem solving, so in order to simulate characters with AI, the task must be posed as some sort of problem. There is a tradition of AI applications which simulate characters and fictional worlds, and I’ll review those here, and connect them to the larger agenda of problem solving.

AI projects that simulate characters tend to fall under two categories: simulations and story generators. The latter category are software that generate stories in the form of text readable by people. One of the earliest and most influential story generation projects was Tale-Spin, which set characters in an imaginary cartoon-like forest world, where animals would interact with each other and try to satisfy goals [Meehan 1976]. Tale-Spin is notable because of instances where stories would fall into infinite cycles. The architecture used a system of planning that exclusively focused on characters, and has been criticized for not accounting for the plans of the story author.

Both Lebowitz’s Universe [Lebowitz 1984] and Turner’s Minstrel [Turner 1994] story generation systems were influenced by Meehan, but these took alternative models to story construction. Universe relied on the author’s narrative goals, which would frequently include constructing situations that would be against the interests of the characters themselves. The system was applied to generate soap-opera stories, and maintain a consistent level of complexity and interest. I would argue that Universe is not precisely a story generation system, but rather a plot generation system instead. Minstrel is aimed at constructing stories creatively, and uses creativity based on analogical reasoning and self evaluation. The model of Minstrel is centered on the process of the author.

In addition to story generators, games have played a strong role in the representation of characters. Games fall under the category of simulations, and represent characters by having the characters engage with the user interactively. The strongest example of characters in games The Sims, which is a notable title for many reasons. The Sims uses a model of behavior that is not based on planning, but rather on needs and motivations that is inspired from Maslow’s hierarchy of needs. The Sims allows players to observe and command the virtual characters (called sims), who interact with objects and each other in a compelling (if not realistic) manner.

A final example of simulated characters is in the AI project Facade, by Mateas and Stern [Mateas 2002]. Facade is an interactive drama, where the player represents a character who visits the house of two longtime friends, Grace and Trip, whose marriage disintegrates over the course of the evening, with the player stuck in the middle. Facade is built to ascribe to the principles of Aristotelian drama, where the tension is meant to fluctuate according to a defined dramatic arc. The simulation is organized by a drama manager, which introduces events to alter the dramatic flow of the experience.

Each of these projects makes use of an explicit model of the story world that they represent. The types of models direct the expressive and representative capability of the resulting system.

For characters to be represented computationally, they must be understood at a symbolic level. This is the heart of the transformation of the story world’s model into computational form. The decisions that must be faced in constructing symbolic representations inform the discourse of the simulation. Because this is a process of adaptation, that discourse of the simulation must be woven into the discourse of the narrative itself. Because of the nature of the domain, an approach that follows in the tradition of GOFAI would be very inappropriate. Story worlds convey more than minds, plans, and psychology of individual characters. A simulation must convey the system of interaction between the characters, and the essence of the world of which they are a part.

Adaptation and Models

The process of translation not only extends a work of literature into a new language, but also extends the work in time. Texts have a life within a culture, which will emerge, grow, bloom, and eventually dwindle. Translation is a means to breathe new life into a text, extending it in time, and into a new cultural world [Bassnett 2002]. This extension come with a set of challenges. A text is necessarily connected tightly to the cultural system whence it originates. The translator is responsible for not only preserving the identity of the text being transferred, but also weaving it into the new culture. The focus of my work is not translation, but rather it’s sibling, adaptation.

Adaptation carries with it all the burdens of translation, but brings the source text not only into a new time, and culture, but into a new medium. This extra dimension brings in added complexity, but it also changes the perspective on the problem of translation. Media speak with their own languages, with conventions established by genres and existing works. Even within a single format, there are different forms: The conventions of the epic poem are different from the conventions of the novel, or the short story.

A productive way of seeing fiction is not as a static or formal artifact, but rather as a world. When characters make choices within a fictional text, their futures are already written. But for those choices to be meaningful to readers, the futures must be imagined as dynamic. Similarly, works define a space of meanings and possibilities. Story worlds are not reflections of what is foretold within a written narrative, but they represent what has the potential to occur at each moment within the world where that narrative takes place.

At a distance, the problem of adaptation operates on some sort of space of equivalence. The individual adapted works are very different, but adaptations and translations must have something in common with the source material. That something is some common intrinsic structure belonging to a work that must be preserved across language and media for a translation or adaptation to be successful. This structure must illustrate the types of characters, relationships, events, plot points, and so on. This intrinsic essence is what I call the work’s model.

A model conveys the essence and meaning of a text. It also conveys the values and most important elements. The model should be imagined as the bricks and mortar which build the space in which the narrative plays out. Johnson-Laird [Johnson-Laird 1983] explains that models are a tool for cognition and are a functional understanding of the world. Narratologist David Herman bridges the space between narrative and cognitive science. Narrative defines a world, and readers understand a story by understanding the underlying model. “This amounts to claiming, rather unspectacularly, that people try to understand a narrative by figuring out what particular interpretation of characters, circumstances, actions, and events informs the design of the story.” [Herman 2004] The actual narrative then, is but one trace through a live simulation of this model.

Forming Models

A problem in building models is what to include versus exclude. The construction of a model is a significant and meaningful act. When one constructs a model of some system or domain, some information is included, and designated as important, and other information is disregarded, and designated as unimportant. This simple and initial step is an important and fundamental case of meaning making. Some branches of cognitive science [Johnson-Laird 1983, Gentner 1983] argue that the construction of models is a basic unit of cognition. By virtue of this isolation, models impose values on the phenomena that they represent.

Models that make use of classifications also impose values. Bowker and Star discuss the political ramifications of classification and sorting, explaining that classifications create ethical claims on the material that they describe [Bowker and Star 1999]. The imposition of classifications says a great deal about what one values in those systems.

A simple example is to look at models of fiction as answers to questions about some particular narrative. Consider an example of classic film such as Citizen Kane. What is this film about? The immediate answers to this question will lay the foundation for a model that describes the work. “It’s about lost childhood,” “It’s about the ambiguity and elusiveness of truth,” “It’s a fictional biography,” “It’s about William Hearst.” Each of these answers begins to describe the essential elements of the film. When describing what is important, the weight and emphasis given to different characteristics shapes the bias of the model as a whole.

Realistically, none of these can claim to have a hold on an absolute truth. Each of them expresses a way of looking at the material with a certain perspective. As is the case in critical thinking, the reader must take a position on the text, and that is the first step toward building a model. Depending on what sort of interest or agenda the reader might have in approaching a text, that will color the reader’s perspective. Models are not right or wrong, but they may be more or less useful depending on the perspective of the interpreter. Scientific theory is a domain where there are many models, often contradictory ones. Newtonian physics is inconsistent with Einsteinean physics, but they are not right or wrong, they are instead or less useful or appliccable to a given problem.

We must be aware of the models we use in approaching a text for adaptation. It is easy to approach a text with a position already established, and this may color the resulting interpretation. It is not possible to come to a text with a blank slate, or if we could, then we would not be able to understand the text at all, because it would not connect to anything in our experience. It is instead necessary to be aware of the models that already exist in mind when interpreting a work.

Both the process of interpretation and the process of creation involve building models. When approaching a text or a procedural artifact, the reader will bring their own models and perspective to the work. There is a cognitive interplay between both the world of the creator and the world of the reader around a created artifact. However, the model belonging to the work may come to take on a life of its own, revealing elements missing from the models of both the reader and the author.

BioChemFX is a detailed and elaborate simulation of deadly chemicals being released in an urban area. The simulation is designed to help develop safety procedures and train rescue workers to respond to the threat while saving the most lives. However, embedded in the software is how the gas spreads, but missing is clear instruction on who to rescue. When a toxic chemical outbreak occurs, the treatment of it raises questions regarding the value of human life. Bogost explains that this is a matter of inclusion and exclusion, combining rules with subjective ideals [Bogost 2006].

In addition to identifying content, models also expose relationships and procedures. These give the model a predictive power. By understanding the procedural laws of the model, one can predict what might occur to real phenomena based on the rules of the model. This principle is the foundation of the scientific method, but the method can be used beyond prediction of events in the real world.

Models so far have been used as general and loosely imagined structures. But when the matter of computation is introduced, they must be made concrete. Computational models are formal systems, or physical symbol systems, the same things at the heart of Newell’s approach to AI and cognitive science.

A formal model is a symbolic construction, borrowing the notion of symbol both from traditional AI, as well as from the semiotic tradition. Signs in semiotics are inherently arbitrary and meaningless, only taking on meaning when coupled with a reference. Similarly, a model on its own has no meaning. A model only gains meaning when its symbols signify some external idea known to somebody. To be useful and understood, models must be creatively interpreted. In order for the model to signify a system that is meaningful, it must represent material outside of the system itself. A model encodes relationships and functions, but representations are needed to tie the model to human systems of meaning. A model without representation is nothing at all. The model must have representation in order to exist. The two exist in opposition to each other, but are necessary to sustain each other. One might argue that a model defined logically has no representation, but formally it must use icons defined in some meta language. Even abstract logical formulations must be written in an alphabet.

The dimension of representation ties so deeply into human embodiment that it is impossible to escape. When someone wishes to develop an AI system which can understand itself, the developer is faced with the issue of infinite regress. An example is the Cyc project’s attempt to understand phenomenological concepts [Adam 1998]. A wholly internal system of knowledge is thus useless. This is not to say that propositions, rules, or symbols are useless, but rather they must represent something to somebody.

Similarly, an argument may be made that no representation can ever mean anything without engaging with other representations. A pure representation on its own can do nothing without engaging with other meanings. A human might be able to supply an interpretation of some isolated observation, but in order for the artifact to convey anything, it must have some meaningful composition of representations, that is an arrangement which conveys relationships. In order for something to be an artifact with communicative potential, it must have a model.

The field of games is surprisingly rich from the perspective of the relationship between models and representations. Game scholar Jesper Juul argues that games are a combination of real rules and fictional representations [Juul 2005]. Digital artifacts have the power of simulation, they can take a procedurally encoded model and simulate it in time. Michael Mateas argues that digital artifacts can be used for the purposes of artistic intention by presenting a procedural system [Mateas 2003]. According to Mateas, an artistic work that uses AI (Expressive AI), is composed of a computational machine and a rhetorical machine. The two of these share vocabulary and a model.

Mateas also argues that there are two parts to the computational machine. There is one system which defines the rules and makeup of the work, which is what I call the model, but there is a second system which contains the running system, which I call the simulation. The model and the simulation are separate. The model is authored by the creator of the artifact, and once the simulation is started, the model may not be adjusted. Instead, the simulation is dynamic and interactive, receptive to engagement with a user. Both contain representative material. The model has the greatest expressive affordances for the author, and the simulation has expressive affordances for the user.

Developing a model for an artifact, whether a new one or an adaptation is a rich and deep activity, even if much of it is done automatically. There is a dilemma of inclusion and exclusion, of imposing values and ethical decisions, and no model will ever exhibit absolute truth. These are not restrictions, but are the very power of models, and simulation, as a system for realizing and formalizing models is a the medium with the greatest potential for expression using them. Models are ambiguous and flexible, interdependent on representation, and intrinsically playful. These are all factors in the construction of models, but they may also be seen as the mechanism for their judgement and analysis.

Traditions of AI

The domain of artificial intelligence can be used to build a computational simulation of fictional characters, but traditional AI lacks the perspective to represent models of story worlds. The central difficulty has to do with the fact that traditional AI is preoccupied with the mind, and can understand things outside of the mind only with difficulty. Things outside of the mind, such as the entire story world, are highly important for fictional adaptation. Even when the world is understood as a model, there are ambiguities that must be explored and addressed. Traditional AI tends to have a totalizing perspective, omitting much that should require attention.

The flaws of traditional AI all stem from the central issue of perspective. The flaws reside in AI’s handling of embodiment, cognitive extension, situation, rationality, cultural values, performance, and emotion. This section attempts to run through the flaws, illustrate what is lacking and why a change is necessary, and touch on any literature that discusses the conflict. Traditional AI limits its understanding of intelligence and cognition. These flaws obstruct the larger goal of adaptation, and the solutions aim to broaden AI’s perspective and epistemology. It is my goal in this section to build a new approach to AI, one step at a time, that can be used to better tackle the problem of simulating fictional worlds.

Traditional AI is flawed, but it can be refined. It is not my intention to throw out physical symbol system entirely, but rather change focus. Because the adaptation process makes use of formal models, a symbolic understanding of character is important. That understanding must not be fixated on the individual psychology of the character, rather, the scope of representation must surround the cultural and social system of which the character is a part. Instead of fixating on goals and planning, the modified approach to AI should focus on goals and activity.

1  embodiment

AI represents cognition without a body. The fact that AI lacks embodiment is no surprise. The only domain of AI that can arguably make use of embodiment is robotics. However, the lack of embodiment in traditional AI is indicative of a stronger ideology: that mind and body can be effectively and unproblematically separated. Traditional AI thus has a bias toward abstract thought that is independent of physical being. Through the origins of AI in symbolic systems, which are themselves mathematical constructs, traditional AI lacks the perspective imposed by embodiment. Free from the constraints of physical grounding, symbol systems can reason in the abstract. Intelligence without embodiment conveys a view from nowhere [Adam 1998].

The separation between mind and body should not be seen as unproblematic. Abstract reasoning without perspective is especially dangerous. There is a difference between information and knowledge, and the central difference is that knowledge requires a knower, who has a position, and who has a viewpoint. When photography emerged, it was seen as something that could represent the world with absolute accuracy, and would lack the personal expression of painting. Instead, early photographers soon discovered that their new medium had the artistic affordances in spite of photography’s ostensible accuracy. Having a viewpoint alone is meaningful. Representing the world without a viewpoint is at best meaningless, and at worst misleading.

Many AI projects have embraced this lack of perspective, most notably the Cyc project. The ideology behind this has its roots in Cartesian thinking. Descartes believed that the mind is wholly separable from the body, and even the physical world. To him, the mind is equivalent to the soul, and existing eternally in spite of the finite nature of the world and human existence. The Cyc project aims to create an encyclopedia of commonsense knowledge, all framed using symbolic propositions. The Cyc project seeks to encode human knowledge, but without the perspective of a knower [Adam 1998].

Embodiment is an unusual argument to bring into a discussion of procedural adaptation of fiction, but it has two important consequences. One, the fictional model is a view from somewhere, that of the author. The simulated world must acknowledge that it has a particular viewpoint. It is not meant to be a disembodied picture that describes reality, but it describes someone’s perspective on reality, or at least, someone’s constructed world. Fictional models therefore have a perspective complete with bias and emphasis on some elements of the world above others.

Perspective complicates representation of the model of a fictional world. Without embodiment, symbolic formulations have no perspective. Models without embodiment present information in abstract and present a model that lacks the capacity for criticism. Because information is represented objectively, it stands without grounding, and communicates itself as absolute. Representations of fictional worlds are biased, and should be understood as such. An astute reader does not believe every word written on a page is gospel truth, but rather understands the meanings accounting for the perspectives of the author and the characters. Underneath this issue are the matters of literacy. Literacy is the ability for a reader to interpret a work in context, although this is by no means a straightforward skill. A work is literate when it situates itself within the context of other meanings. For a fictional adaptation to be embodied, it must be literate.

Secondly, the characters themselves, who are to be simulated, are embodied within the fictional world. They are fictional, but in a good story, they must have some physical presence. I do not mean this in the sense of simulating physical bodies. It would be a mistake to interpret embodiment as merely physical simulation. Moreover, physical movement and articulation are not generally important in fiction. However, the characters will have their own perspectives on the world, they will not necessarily have the complete picture, but they will be bound to the reality that they live in.

Characters’ interactions with each other are embodied, and many meaningful interactions in fictional worlds have bodily manifestations. A good example is a character’s gaze. Such a thing is very significant in fiction and in human interaction, and can be understood symbolically, but it is expressed bodily. It is argued that all symbolic meaning can be traced back to embodiment [Lakoff 1980, 1999]. To accommodate embodiment of characters, we do not need to reject symbolic representations, but understand that those symbolic representations are anchored within the body. It also suggests that embodied action should be a starting point for understanding symbolic representations, and not the other way around.

2  individual vs extension

Beyond the body, a flaw of AI is to examine the individual in isolation, as a single atomic agent, without connection to the surrounding world in which the individual must reside. The application of fictional adaptation requires adaptation of much more than individual agents acting independently. What is missing is the social and cultural context of the agents, and our approach to AI must consider agents within this broader picture.

The idea of looking beyond the individual or the mind falls within the broader scope of cognitive extension, which claims that cognition is not limited to the self, but extends outward. Cognitive extension pushes the understanding of cognition out of the mind and into the body, into tools, instruments, and artifacts, and into the social and cultural landscape. If AI is a computational approach to cognition, it must account for the extendability of cognition.

Cognitive extension blurs so many boundaries that it makes cognitive science a muddled mess. Its position on tools and artifacts is sound, supported by many philosophical positions [Freud 2005, Heidegger 1977, Norman 2002]. Tools are considered extensions or prosthetics of mankind, but this extension is not unproblematic. The use of the tool shapes the human using it as much as it acts as a prosthetic. One way of looking at this is that the tool comes with its own model of the world, and through using it, the human comes to adopt or incorporate that model. In this light, instrumentality is a continuation of embodiment, but may be understood in a symbolic manner.

We can imagine fictional adaptation as incorporating this element. Objects used by characters, props, must have symbolic models that integrate with the model of the story world. In using objects, characters’ ability to interpret and interact with the world is changed. This begins to shift the emphasis in our use of AI from abstract cognition to activity.

The logic behind cognitive extension it is that because cognition makes use of the affordances of the body and of tools, so too must it make use of cultural and social practice. Agents act in concert with each other, and within a framework of meaning defined by the cultural setting of which they are a part. Where cognitive science has been closely tied to psychology, cognitive extension connects psychology to sociology and anthropology. Integrating the two reveals that mind and culture are interdependent [Shore 1998]. What this will mean for AI will be discussed in subsequent sections.

3  situation

Planning is a predominant theme in AI. This makes sense, because AI was developed to solve problems. The kind of problems and problem solving were very particular. To develop the General Problem Solver, Newell and Simon studied how a very specific demographic approached very specific problems, within a very specific situation. The demographic was, exclusively white male engineers and scientists, Carnegie Mellon students and graduate students, specifically [Adam 1998]. The problems were generally scientific or mathematical in nature [Newell 1963], and the situation was that of a laboratory or academic environment. While this form of research was in line with absolute knowledge without perspective, here it is worth critiquing because of its neglect of situation.

When the AI methods that derived from the GPS research have been exposed to other situations, they have frequently come off as peculiar or stilted. These are so called “expert systems,” which usually are best used as tools by field experts who can apply their own knowledge to the system’s results. Problem solvers cannot be used independently without some sort of interpreter to operate the program. The reason for that can be understood by acknowledging context under which AI emerged as a product. Problem solving is only one part of human cognition, and that we do much more than planning in our daily lives. Problem solving is also extremely dependent on problem formulation. When a problem is ill posed or not fully understood, it cannot be solved. The way we solve problems depends on how we view the problems in the first place.

It is perhaps a philosophical challenge, to the rhetoric of problem solving, but it seems that in order for a problem to exist, it must exist within a situation. The problem must have some sort of context, and be for somebody who has an investment in the solution of the problem. A mathematical formula is not a problem until it is important that it be solved. The space in which problems are posed and meaningful is a situation. This concept is important to fictional adaptation because simulated characters may have goals and plans, but those do not mean anything until they are contextualized within the space that the character inhabits.

Situation is one way in which traditional AI does not account for the broader picture. Situation directly informs and affects cognition. Instead of using the same logic and formal rules anywhere and everywhere, situated cognition says that we think differently under different circumstances. Meaning itself is dependent on those very circumstances. For fictional adaptation, characters must be faced with a variety of situations. Situations might range from simple events such as a conversation, to broader ones such as breakfast or a social visit, to even broader grand ones, such as courtship which could be the context of the entire narrative.

Situation does not mean that symbolic AI must be rejected. Instead, situation must be accounted for. Because meaning and activity are dependent on situation, situation again ties into the system of models. A situation describes a model for activity. The model of the fictional world must describe the potential situations that may arise, and inform the possible activities that can be conducted by agents under those circumstances. This framing is symbolic, but again changes the focus of AI from planned atomic actions to situated activities.

Situation informs the identity of characters. When a character has a role within a narrative, that role serves as a context which situates the character’s actions. Identity thus is a composite of situations that apply to the character [Clancey 2006]. This approach also complicates the rhetoric of planning. Planning agents tend to have hierarchical plans stored in memory. With this viewpoint, plans would be integrated with the agent’s situation.

Planning is important to simulated characters, they necessarily form plans within their worlds and attempt to see them out, but plans in fiction are inevitably thrown askew. The problem solving method proposed by planning uses tree based search, which means that when a subplan fails, an AI will usually go up and try the next thing. In fictional worlds, this sort of reaction is not often the case or even possible. Instead, an agent’s goals or intentions define a situation that the agent experiences. Instead of planning according to all potential actions, situated activity directs the agent from the bottom up, according to the agent’s context.

Turning over planning in favor of situated activity exposes something else very important for fictional characters: demeanor and conduct. Frequently what is important about character interactions is not what the characters do explicitly, but how they do it. These factors are tightly related to the situations wherein the characters are occupied.

4  rationality

Traditional AI has a preoccupation with rationality. Rationality is certainly worthwhile and important in the domain of problem solving and critical thought, but it is a small part of the picture when compared to representation and fictional characters.

For an agent to be rational, according to Newell [Newell 1976], means that the agent acts in a way that it believes will help achieve its goals. If we understand this as the basis for rationality, it offers a more complex perspective than might be initially imagined. This perspective of rationality carries with it an inherent acknowledgment of bias, belief, and goals. An observer may consider an agent’s goal of self destruction undesirable, but the agent’s plan to jump off a cliff is perfectly rational given its goals.

Rationality is still an ambiguous issue even with this in mind. For the purposes of fictional adaptation, fiction is rife with characters who behave decidedly irrationally, acting at times in spite of their goals. This suggests that rationality and goals alone are not sufficient to account for the complexities of fictional characters.

Rationality relates to planing and clear understanding of goals. Story characters often have goals, but frequently act in spite of those goals. Thinking in terms of rationality makes discussion of character revolve around goals and desires. A rational character must be defined in terms of goals. Literary characters may have goals, but they are not defined in terms of them. Furthermore, a character’s goals may often be conflicting, and these conflicts reflect issues of the values in the story world.

Frequently in agent based programming, where agents have conflicting goals or objectives, an evaluation function is used to evaluate what the optimal objective is. Even in situations where none of the options may be desirable, they can be framed in terms of better or worse. The process of this evaluation is at the heart of rationality, and derives from the origin of the word itself. “Ratio” means measurement, thus a rational action is one which measures all of its alternatives. This is an approach which hardly seems desirable, but it must be addressed somehow. An agent must act eventually. However, to apply an evaluation function conceals the significance of that choice. In addition to a weighted comparison, the agent must also express the dilemma of choice, and that must be reflected in character. The arithmetic simplicity of evaluation functions must not conceal the importance of how the agent has made its decision. Fictional characters are necessarily irrational. This does not mean that they act flagrantly against their interests (although sometimes they may), but it means that their faculty for measurement is biased, incomplete, or spurious. This complexity is essential to the representation of character.

5  cultural/social symbols/values

The work of symbolic systems depends on a careful relationship between model and representation. Both the model and the representation of fictional simulation must tie into the system of meaning given by the fictional work. This system of meaning is cultural: it is derived from the cultural world of the author, and of the culture of the world within the work itself. Traditional AI looks at only individual cognition, so it is our agenda here to find a way to open it up to cultural meaning.

The agenda of looking at cultural meaning is to continue pushing the subject material of AI outside of the mind. Not only must AI extend to the body and the extensions of the body, it must extend into the meaning systems that are socially and culturally instituted. In the trend of cognitive extension, we must look to culture because cultural practice may be considered an extension of man. Tools are prosthetics which extend our interaction and interpretation of the world, but cultural practices serve this function as well.

As an example, consider the discipline of statics as studied in engineering. This discipline is about the study of structures in static equilibrium. It is a cultural practice because it is used by a specific population (engineers) in the context of other applications, such as the construction or analysis of structures. Statics views the world as decomposed into bodies, which exert forces and moments upon each other. This is a viewpoint, a lens, by which the world can be interpreted and be understood meaningfully with respect to the system of Statics.

Another example is a dance at a ball in the context of Pride and Prejudice, our fictional adaptation target. An observer in this situation interprets the actions performed by the participants in a very careful light. Meaning is made through the use of subtle cues and simple actions, such as gaze, a man asking a girl to dance, and the girl’s subsequent acceptance or refusal. This is a cultural system with a very precise set of meanings, and the situation can be used to interpret events in accordance with that system of meaning.

The matter of cultural meaning is thus an issue about representation. There is a relationship between the physical world and the model, which must be acknowledged by an the AI in the adaptation. All parts of the model ultimately tie into a cultural system of meaning. Since the focus of AI on individual agents is flawed, we see here that a stronger accommodation of the fictional world’s cultural system must be examined.

6  performance

Performance has two meanings in the scope of computation. The first is in the sense of efficiency. In this meaning, a system performs well when it is efficient and completes a task in optimal time, or does the task especially well if there is some criteria for judgment. The other sense of performance comes from the idea of performativity. In the project of fictional adaptation, the criteria of performance seems straightforward: The system performs well if it conveys a believable and compelling adaptation of the target narrative.

While they are quite different in application, both these understandings of performance share a common thread. Performance indicates that there is an audience. The system is doing something for somebody, and can do so well or poorly. Even in the case of efficiency, performance is at stake because time or efficiency is valuable to somebody. In the case of fictional adaptation, performance occurs at two levels. First, the system must perform for the user and believable. Secondly, the characters must perform roles in their interaction with each other.

Performance focuses on interaction between the AI system and the user. This idea has been espoused in reference to computation in general [Laurel 1993]. Performance tends to be very common in games and interactive drama projects. Joe Bates and others [Bates 1994, Mateas 2002] have argued that AI for artificial characters should focus on believability rather than realism. The idea of realism, much like rationality, has been an issue with traditional AI. Under the dogma of pure symbolic reasoning, realism can be seen as an issue of depth, rather than context. This chain of reasoning would justify things such as the Cyc project. Believability rejects the necessity of realism. Instead, it emphasizes the communicativity of representation, rather than the sophistication of the model.

An important subject that is affected by performance is interaction. Not just interaction between the user and the system, but between characters within the system itself. The traditional AI approach to interaction claims that the thoughts and minds of agents must be modeled explicitly, and communication and interaction should work at a low level of intentions and goals [Cohen 1990]. This literature describes the minds of agents as being enormous sets of logical propositions, representing things that, for the agent, are true. This literature is referred to as “Beliefs, Desires, and Intentions,” and it contains descriptions of how to model an agent’s understanding of knowledge. In the full spirit of “realism,” BDI literature describes how to represent immensely complex logical propositions for relatively simple interactions between agents.

Let us begin with an example. With the Wednesday advertising supplement in hand, a supermarket patron approaches the butcher and asks “where are the chuck steaks you advertised for 88 cents per pound?” to which the butcher replies, “How many do you want?”

This delightful snippet is analyzed in terms of logically formulating a complex network of propositional relationships that describe the beliefs, goals, and intentions of the butcher in this example. This formulation is problematic. On one hand, it is necessary to represent, to some degree, the knowledge and intentions of agents. It is perfectly compatible with the epistemology of traditional AI. However, this symbolic formulation is arguably not realistic. Furthermore, this formulation of intentions breaks down when considered developmentally [Vygotsky 1978, Tomassello 2001].

Sociologist Erving Goffman has proposed a model of interaction based on performance [Goffman 1999]. The key to this is the idea of interaction, and the idea that agents interact with each other in addition to the user. Characters make use of roles, and perform those roles. Goffman’s approach is influenced by the school of symbolic interaction, which claims that interaction is ultimately symbolic in nature. Unlike BDI, symbolic interaction focuses on believability. Instead of a character being a set of abstracted goals and intentions, the character has roles which abstract out the types of interactions that the character may engage in. Much like interaction with artifacts, roles are models of interaction.

In the example with the patron and butcher, the symbolic interaction approach would reject the complex interplay of beliefs and intentions. These would be replaced with a pair of roles, and perhaps a social script which the agents would enact. The interaction between the two is symbolic in nature because it is meaningful within the context of the shopping activity. For fictional adaptation, this type of model is vastly superior to the mess presented by BDI.

7 Emotion

The relation between thought and emotion tends to be very contested in the study of cognition. Rationalism excludes emotion particularly. AI has a difficult time accommodating emotion, especially in regards to the relationship between emotion and behavior. Emotion is disconnected from the rhetoric of planning.

Emotion is very important in the lives and behavior of humans, and is furthermore enormously important in fiction. Studies have shown that emotion has an effect on decision making [Oatley 1996]. Such a study might sound like the rational mind is being interfered with by emotions, but the argument is the opposite: that emotions are the basis for decision making and even rationality. This argument hearkens back to Aristotle, who claimed that emotional appeal was an integral element to rhetoric.

Humans are sensitive to emotions and can easily percieve the emotions of others. This cycle of emotional response occurs in reading fiction, and is used to develop an understanding of the fictional world. In reading, the mind conducts a mental simulation of the characters’ emotions, and this helps develop a kind of emotional intelligence [Oatley 2008]. Within fiction, characters are subject to many emotional forces, which must clearly be accounted for in order to perform fictional adaptation.

AI oriented around planning does not have the tools to represent or model emotion. Emotion needs to be represented in the model and behavior of agents. Agents need to experience emotions and those emotions must have effects on their behavior. To model this, we must provide an explanation for how emotions arise in agents, how they are expressed, and what their varieties are. A useful discussion of emotion comes from Ortony, Clore, and Collins who view emotion as valenced reactions [Ortony et al. 1990]. Emotions are experienced in reaction to events, others, and objects, and depending on how the world is perceived, this can affect the emotional response of the agents. This model does not discuss expression of emotions in great detail, but provides a compelling model that differentiates between emotion and mental state.

To accommodate emotions within AI would require that agents experience reactions to things in the world, which would in turn affect the conduct of the agent. Emotion and rationality are connected, and rationality is principally the characteristic of carefully measuring the value of actions and outcomes. With this in mind, the effects of emotions can be represented as skewing the weights of the decision making process. An action that would be poorly valued by a cheerful agent might seem much more desirable, even “rational,” to an angry one. Emotion is represented not only in decisions, but also the manner in which agents conduct ordinary activities.

Changing Perspective

The points in the above section describe what I consider to be the flaws of traditional AI, but taken together, they can be seen as a reorientation of the project. In critiquing the approaches to traditional AI, several trends have emerged. It is not necessary to reject the symbolic nature of AI, but we have seen that changes must be made to the target of study for AI to successfully address the problem of fictional adaptation. The resulting changes are that:

1. The model of the story world is the unit of analysis.
2. The story world is a cultural system with contextual meanings and values. It is impossible to assign values from outside of the system.
3. Situation and activity are the basis for all behavior that occurs within the system. Plans are at most secondary to situated behavior.

I suggest that we shift the focus of study. The problem is the adaptation of fictional worlds. By virtue of looking at worlds, the focus should be on the environment and the relationships between characters. Instead of thinking of the intelligence and goals of individuals, we must think about the logic of the world itself. The world is culturally oriented and contains an index of situations, roles, activities, and actions that characters may engage with. At any given point, a character will be in the middle of some situation or another, taking on a particular role with which to take part in the situation. This role will constrain their ranges of actions. Actions have symbolic values with respect to the story world, and affet its state. Characters may operate according to plans, but foremost, they will operate according to their identities, and express what makes them who they are.

To continue with this, it is necessary to understand the values of the world, and the mechanics. The values describe generally what is important in the world, and what numbers of values the characters might like to keep track of. The mechanics describe what possible things can happen in the world at all. The mechanics of a given situation are dependent on what values of parameters characters might have in that situation, and these parameters are affected by the execution of the mechanics.

Worlds have values in several respects. There are values in the moral sense of what concepts, events, relationships, and qualities are legitimate or meaningful in the space between the characters. There are also values in the sense of what parameters that might be attributed to characters, as specific statistical values. In discussing this latter type, there are two ways of doing such: one is defining what the important parameters are, what they are called and how they are articulated, and two is determining what quantities the actual characters have, or how these quantities are changed with respect to the characters actions or activities.

It is my intent not to provide a final answer to the inquiry of determining the values of a story world. As is the case with any interpretation of a fictional world, the determination of these is not only very subjective, but also very open ended. A fictional story world might operate around one principle, but on further study, the story is revealed to be about deeper meanings. There is a relationship between these strata of meanings that is especially important to consider on the subject of adaptation. I want to suggest an approach toward looking at meanings, thinking of them mechanically, and then using that as a starting point for the adaptation process.

In the space of political games, the goal is frequently to untangle a set of relationships in some everyday system, and uncover what values lie underneath.

The mechanics of a world are the scope of what can happen. In the context of fiction, this is necessarily limited by many factors, but centrally the range of actions a character might perform are dependent on their appropriateness, and the nature of the character itself. Narratives operate according to causal rules, thus one aspect of character may provoke one meaningful act, which may cause another. Characters operate according to some form of social codes, which dictate what their range of choices are in any given situation. Occasionally, there may not be many options, and instead what is of importance is not the action itself, but the conduct, the means of expressing the action. These differences are subtle but significant.

I think that in many fictional worlds, where the action is oriented around character and not centrally around action, that the worlds are primarily socially oriented. Social mechanics take the form of rituals. Rituals work in a manner which amounts to a kind of performance of everyday life. Rituals should be understood in terms of duration. There may be short rituals, for events that are short and pass quickly, such as a conversation, a game of cards, a dance. There are moderate length rituals, that might take the course of a several hours in the narrative world, or several pages in the text, such as a social visit, a date, a work day. And there are extended rituals, which may last a long time, even over the course of an entire story, such as courtship or coming to maturity. There is a heirarchical nature to these rituals, and with increasing spans of time, there are also increasing degrees of freedom and flexibility. Short rituals are tight and restrictive, but larger rituals have more room for transgression.

Characters entering into rituals must adopt some kind of role for their position within the ritual. A social visit would have roles for the host and the guest, a conversation will have fluctuating roles of speaker and listener. Roles come with implicit expressions of power dynamics, creating a currency of interaction. How the character abides by its role is significant and will affect the values and parameters associated with that character.

This approach of role, character, value, and mechanics is very different from the models of goals and planning established by traditional AI. However, the given approach is not inconsistent with the symbolic perspective of AI. Instead, these recast the symbols, anchoring them within perspectives and into the activity of the agents. A number of contemporary cognitive scientists have aimed to shift the focus and object of study of cognition. A prevalent trend is to shift the focus from representing thought to activity [Lave 1988, Nardi 1995, Cole and Derry 2005, Hutchins 1995]. Activity is important for studying cognition, and it is also important for representing the content of a modeled world. It represents the scope of what characters can do. Activity is the mechanics of the fictional world. If we understand what characters can do, and what effects those actions have, then it is arguable that we understand the cultural world in which those characters reside.

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I am really interested in metaprogramming, writing programs which can modify themselves dynamically. More notably, users of metaprograms will be able to change their functional operation. The advantage of being able to do this is that it enables a great deal of power for development and creating things, but primarily, it’s just a lot of fun. There is something about being able to call functions using reflection that just is really pleasing and entertaining to me.

Most commonly scripting frameworks are used to create secure environments for scripts, and often these scripts will be developed ahead of time, but they also enable a possibility of dynamic scripting, where a scripting environment may be able to do interesting things during run time. Possible examples of run time uses are controlling agents within a world by issuing commands and writing code for an agent’s “brain”, then loading to that into the agent which is live in the world. It would be possible to create a dynamic music or image making program, where the artist can control what is being played or drawn using the scripted code.

With the recent release of Java 1.6, we now have standardized implementation of JSR 223, also known as the scripting framework, which enables some exciting metaprogramming possibilities. This allows one to script on top of Java. So, it would be possible to interact with Python, Ruby, Javascript, or any  other sort of scripting language through this one framework. Interestingly, it is also possible to use Java as a scripting language. Thus, you can script for a Java program… in Java. This may seem ridiculous to some, but I think this is simply delightful.

Here is an example of the scripting framework in use. Note, to actually run this, you must add the java-engine.jar, found in jsr223-engines.zip to the classpath.

package scripttest;

import java.lang.reflect.Constructor;
import java.lang.reflect.Method;
import java.util.Map.Entry;
import java.util.logging.Level;
import java.util.logging.Logger;
import javax.script.Bindings;
import javax.script.ScriptContext;
import javax.script.ScriptEngine;
import javax.script.ScriptEngineManager;

/**
 *
 * @author Calvin Ashmore
 */
public class Main {

    /**
     * @param args the command line arguments
     */
    public static void main(String[] args) {

        ScriptEngineManager mgr = new ScriptEngineManager();

        ScriptEngine scriptEngine = mgr.getEngineByName("java");
        System.out.println(scriptEngine);
        Bindings bindings = scriptEngine.getBindings(ScriptContext.ENGINE_SCOPE);
        for (Entry<String, Object> entry : bindings.entrySet()) {
            System.out.println("  " + entry);
        }
        System.out.println(scriptEngine.getContext());

        try {
            scriptEngine.put(ScriptEngine.FILENAME, "Toasty.java");
            String script = "public class Toasty {" +
                    "  private float myStuff;" +
                    "  public Toasty(float stuff) {" +
                    "    myStuff = stuff;" +
                    "  }" +
                    "  public String toString() {" +
                    "    return \"I have a thingy! \"+myStuff;" +
                    "  }" +
                    "  public int performWombat(String theWombat, float multiplier) {" +
                    "    int toast = Integer.valueOf(theWombat);" +
                    "    float thingy = toast * multiplier;" +
                    "    double d = Math.sqrt(1 + thingy*thingy);" +
                    "    return (int) d;" +
                    "  }" +
                    "}";

            Class toastyClass = (Class) scriptEngine.eval(script);
            Constructor c = toastyClass.getConstructor(float.class);
            Method m = toastyClass.getMethod("performWombat", String.class, float.class);

            Object toasty = c.newInstance(1.0f);
            System.out.println("My toasty: " + toasty);

            System.out.println("This will work:");
            System.out.println("result: " + m.invoke(toasty, "234", 1.23f));

            System.out.println("This will not:");
            System.out.println("result: " + m.invoke(toasty, "eek", 1.23f));

        } catch (Exception ex) {
            Logger.getLogger(Main.class.getName()).log(Level.SEVERE, null, ex);
        }
    }
}

(Apologies for the strange variable names) It generates the output:

com.sun.script.java.JavaScriptEngine@1abc7b9
javax.script.SimpleScriptContext@c55e36
My toasty: I have a thingy! 1.0
This will work:
result: 287
This will not:
Jan 21, 2009 9:27:15 PM scripttest.Main main
SEVERE: null
java.lang.reflect.InvocationTargetException
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
        at java.lang.reflect.Method.invoke(Method.java:597)
        at scripttest.Main.main(Main.java:70)
Caused by: java.lang.NumberFormatException: For input string: "eek"
        at java.lang.NumberFormatException.forInputString(NumberFormatException.java:48)
        at java.lang.Integer.parseInt(Integer.java:447)
        at java.lang.Integer.valueOf(Integer.java:553)
        at Toasty.performWombat(Unknown Source)
        ... 5 more

This example is able to instantiate and call methods on a simple object effectively. However, in order to do the more interesting things described above, we need to make use of interfaces. So, the scripted class will implement an interface defined by the main program. That interface will define the contract for operation. So, instead of using reflection to call methods, we can simply cast the object to belong to the interface and call the methods directly. I’m not going to write this yet, but maybe soon.

Evidently, I’m not the only one who is interested in models and worlds and values. I was referred to Matthew Kirschenbaum‘s essay “Hello Worlds“. This was interesting because he not only references the work of Ian Bogost and Michael Mateas, but he frames the discussion as an application of digital humanities, to think about worlds and as the material content of both literature and games. He also mentions, however briefly, Jane Austen. Austen is inescapable, an inevitable fact underneath everything, a humming constant beneath the universe. All roads lead to Jane Austen. I don’t know whether to be pleased or frightened.

It is encouraging to read that my game design ideas are interesting to some people! He is not the first person to suggest the idea of a Jane Austen Pride and Prejudice Game, though. I don’t have links for some of the others, but there is clearly a demand for this kind of thing. I am not sure if the project that I am working on is exactly similar to what they have in mind, but there is a chance that it will fill the role.

Later today I am intending on posting a text analysis, and hopefully hopefully both of the papers that I have been working on. We’ll see how that goes.

Schechner’s perspective on performance is broad and inclusive. He sees it as including much more than theatre, but along an entire spectrum, which ranges from everyday life to rituals and art. Two perspectives on performance are the models of the web and the fan. Schechner is heavily influenced by Victor Turner, who treats performance and play as the “as if”. Within the context of performance, the imaginary becomes real, and the “as if” is equivalent to the “is”. Schechner’s goal is to unite all applications of performance under one theory which is inclusive of its many applications. Much of this text is influenced by his travels to Australia and Southeast Asia, and one aim is to reincorporate the rituals of the New Guinea tribesmen, Australian Aborigines, the Balinese, and many others, with the practices of both classical and modern theatre. Schechner was influenced by Goffman as well, acknowledging the performances of everyday life.

To discuss performance, Schechner uses two models, the web and the fan. The fan presents performance as an organized spectrum of categories, and the web reveals the dynamic influences and interconnections. In the fan model, the further one moves up the fan, the more orderly the function of performance, and the lower, the more free and disorderly. The opposing ends of the fan meet, however, as the establishment of a new ritual, which requires a great deal of play and freedom, then becomes a new structure of order. The web model is structured around item (5), which is Schechner’s own background. This is not an indication of bias, but rather perspective, as it his vantage point.

Approaches

Schechner opens this chapter by critiquing an approach to classical Greek theatre, called the Cambridge thesis. This thesis aims to discern the origin of theatre, and the emergence of comedy and tragedy. The Cambridge thesis asserts that both tragedy and comedy evolved from specific rituals. Tragedy comes from the dithyramb, and comedy comes from phallic dances, both of which emerged from some “primal ritual”. This assertion is dubious for a variety of reasons, not least being the absence of any evidence for a primal ritual. Furthermore, rituals do not seem to have much in common with theatre that would indicate the emergence of one from the other. Schechner is not interested in supplying a new origin theory, and is critical of the use of origin theories toward the understanding of theatre. Instead, he is interested in what theatre might have in common with ritual characteristically.

Schechner unites several groups of performance under the same heading: play, games, sports, theatre, and ritual. These share four important qualities: a special ordering of time, a special value attached to objects, non productivity in terms of goods, and rules. (p. 8) Time may be understood as structured in terms of events, which must be completed no matter how long they take. Time may be set, which is an imposed fixed clock time, creating antagonism between the activity and the clock. Time may be symbolic, where the activity represents something happening in a different ordering or flow of time, where time is simply considered differently. While these varying perspectives are distributed among the types of activities described, all are present in digital games. Objects within these performances take on new and special meanings, and their value within the context of the performance may be entirely different than outside. In a ball game, the ball is of crucial and extreme importance, but outside it is inexpensive and has little practical value. The non productivity of performance is in common with what Huizinga and Callois say about games, however Schechner notes some challenges. Performance in theatre has some productive capacity, it fills a theatre house and makes money, sports games are extremely lucrative. However, nothing material is actually produced in the performance itself. Rules apply because performances are activities apart from everyday life. Rules are most notable in the context of games, but also operate in theatre as well. Despite the magnitude of performances, rules are generally held to be the same. The players in a major league baseball game may be better than in a sandlot game, but the rules that govern their conduct are the same nonetheless. Rules are not only designed to tell the players how to play, but how to keep the play space safe against encroachment from the outside.

Play and ritual are seen as opposing ends of performance, but they are still similar. Play is intrinsically motivated, while ritual is extrinsically motivated. The role of freedom is described in positive and negative terms. In performance, constraints are layers, but at the center is always some sort of freedom. The example Schechner gives to illustrate this point is of a theatre performance, where an actor is first confined by the physical space, then by the conventions of theatre, then by the drama or script, then by the instructions from the director, but finally, underneath all of that, the actor has freedom. The relationship between these is what Shechner describes as the axiom of frames. When an outer frame is looser, then the inner frame must be tighter, and vice versa. An example is when a theatrical performance has a very rigid script, then the actor’s freedom within that is more important. Or when the actor has a great deal of freedom, as in improvisational theatre, the conventions used become important.

Drama, Script, Theatre, and Performance

The rituals and scripts used in Paleolithic times were not modes of thinking, but patterns of doing. With Greek theatre, this came to be reversed: action was understood abstractly. Modern theatre is moving to reverse this once again, it loosens the matter of exact presentation, and comes to focus again on doing. Schechner examines the relationship between drama, script, theatre, and performance as concentric rings, with performance as the widest, most encompassing and loosely defined thing on the outside, with drama as the tightest and most delineated thing and is the smallest circle on the inside.

• Drama is the smallest and most intense circle. A drama is independent of the people who carry it, and it may be carried between places and times. Even if the people who perform the drama do not comprehend it, the drama remains preserved.
• Script is all that can be transmitted between places and times. The script is the code of events, and is transmitted between people. The transmitter must know the script and be able to teach it to others.
• Theatre is the event that is enacted by the performers. This is what the performers do during production. The theatre is concrete, present, and immediate. The theatre is meant to be the manifestation of the drama, but it is an articulation and concretization of it.
• Performance is the whole constellation of events that take place in and among the performers and the audience. This is all encompassing and inclusive, containing all of that which is not determined by the script or drama.

Schechner gives another brief summary of the terms: “To summarize thus far: the drama is what the writer writes; the script is the interior map of a particular production; the theatre is the specific set of gestures performed by the performers in any given performance; the performance is the whole event, including audience and performers (technicians, too, anyone who is there).” (p. 87) It is difficult to define performance because of its flexible and permeable boundaries. In public performances, such as celebrations, festivals, and the like, it is easy to shift between being a performer and a spectator.

Another useful framing: performance is “Ritualized behavior conditioned/permeated by play.” (p. 99) This is used to consider performance as a general animal phenomenon. However, Schechner argues that self awareness and cultural transmission are necessary for performance. Play is arguably derived from real life systems, but real systems would not exist without play and freedom to establish them. Schechner borrows from Huizinga in looking at play. Play behavior is derived from hunting and violent/combative activities, but these are also forms of play. The relationship between these activities and play is seen as a sequence of cycles. Playing/hunting leads to ritual/playing, to drama/ritual, to hunting/drama, back to playing/hunting. Rituals and dramas are generally crisis oriented. Crises are moments where balance and order are threatened and must be restored. Although it is arguable that many social rituals exist to maintain order, as opposed to restoring it.

Selective Inattention

Schechner discusses social drama, and borrows a diagram from Victor Turner. I do not know if it appears in Turner’s book, so I am reproducing it here. Schechner’s goal is to take that concept and integrate it with aesthetic drama. Turner’s cycle works in four stages: 1) breach, 2) crisis, 3) redressive action, 4) reintegration. This structure works to maintain social function and consistency. Theatrical tragedy follows this cycle with some degree of accuracy. However, in tragedy, the redressive actions usually wind up leaving the protagonists dead. The “infinity diagram” demonstrates how social drama turns to affect theatrical drama, and social drama also takes on the form of the theatrical.

This book is about the linguistics of writing. Generally, linguistics is centered around the language of speech, and neglects the characteristics of writing. I was interested in this book from two main perspectives. The first is the consideration of written text for analysis. The second is the purpose of developing some sort of writing system for character communication within a simulated world. An in-world language is arguably necessary, (as discussed in Crawford), but is an enormously risky venture, fraught with problems and difficulties. Sampson does not provide clear answers to these questions, but does provide a vocabulary and method for thinking about them cohesively.

Linguistics has classically ignored written language in favor of speech. This division comes from several philosophical perspectives. speech and langauge play an important part in the development of parts of the brain in evolution, and this evolutionary root underscores the importance of speech to language. Writing is a cultural development, and its influence becomes the strongest after the invention of print. Writing is still very important culturally. Sampson’s thesis question is to develop a linguistics of writing.

Three categories of study must be distinguished around writing: typology, history, and psychology. Typology deals with form: what types of written languages are there. The types of written languages, as played out in alphabets and such, are often determined by cultural differences. An example is the adoption of Roman versus Cyrillic alphabets in Eastern Europe. The spoken languages are similar, but the alphabets are divided along the line of the Roman Catholic and Eastern Orthodox churches. The history of writing examines how writing changes. The historical development of writing is different from the historical development of speech, as can be seen to play out in spelling, conventions, and the like. Sampson makes an interesting argument about the value of writing. The linguistics of speech avoids declarations of value to ways of speaking. It is inappropriate to argue that one spoken language is better than another, because value is determined within a culture, and cannot be asserted externally. However, writing does not face this problem. Writing is a tool like any other, and writing systems may have more or less value depending on the circumstances of their use.

Sampson introduces a vocabulary for discussing writing. “I shall use the terms script, writing-system, or orthography, to refer to a given set of written marks together with a a particular set of conventions for their use.” (p. 19) Orthography has much to do with conventions beyond the actual symbols themselves. A language and a script are often conflated, but they are different. Writing is not the same as the transcription of speech, and this is due to the conventions of use. Writing operates according to different grammatical rules and conventions. Multiple scripts may be used to write for one language, and one script may be used for multiple languages as well. The units of writing are graphs. Sampson argues against the use of the terms symbols, characters, letters, and the like, due to their inspecificity. Sampson defines writing itself is a system for communicating using “permanant, visible marks”.

There are to major kinds of writing systems: semasiographic and glottographic. The former uses images with conventions of reading and interpretation. This can be translated into a spoken language, but not read directly. Semasiographic scripts are not normally understood as writing, but are pervasive in communication. Visual illustrations to convey instructions are semasiographic. More poignantly, mathematics is a semasiographic system. These are generally passed over in favor of glottographic systems. There is a lot to be said for semasiographic systems in digital media, and Crawford’s early work using sentence construction belongs in this category. It is interesting to note that semasiographic symbols may have “names”, or translations, which convey how to read the individual icon, but the entire system is still semasiographic because even witht the names, the text cannot be simply read.

Sampson divides glottographic systems into logographic and phonographic subcategories. He notably eschews the term “ideographic” because it is unclear. Logographic systems are similar to semasiographic systems in that they are pictoral, but they are not meant to be interpreted or translated explicitly. Spoken language is “double articulated”, according to Andre Martinet: It articulates thoughts into units, and then provides vocal codes for these units. Thus, a written language that can be read may articulate either the vocal codes, or the units of thought themselves. A pictographic language uses images to designate words is logographic. Phonographic scripts represent the actual phonetic symbols in the words, and generally letters are used to denote vocal sounds.

Systems may be classified according to a couple more principles. Systems may be motivated (iconic) or arbitrary. This difference applies to both phonetic and logographic scripts. A motivated phonetic alphabet will have like-sounding characters resemble each other, while a motivated ideographic script might have graphs which resemble the things they are supposed to represent. Systems may also be complete or incomplete (defective). Completeness relies on the capacity of the written language to carry across the range of expression in the actual language. It is relatively straightforward to see how ideographic scripts may be incomplete, but phonographic languages may be incomplete in other respects as well. English writing is unable to carry through in script the various vocal intonations that might be associated with a sentence. In human speech, intonation can carry across much important data.

Having discussed these fundamental points, Sampson reviews many different written languages. Only a few of these were really noteworthy, so I will examine those here:

The first case study is of Sumerian writing. This was developed for the highly specialized purpose of recording transactions. It is composed of both motivated and arbitrary graphs: Many transactions were written with an image denoting the object being bought or sold, and a number, the components of which are arbitrary in comparison. Because writing was specialized and intended for this very specific purpose, it is difficult to consider it incomplete. Sampson makes a brilliant analogy to computer programming. One usually does not say that a programming language is incomplete because it cannot express Tennyson. The both programming languages and Sumerian cuneiform emerged to fill particular needs. Sampson also compares the transaction writing to a kind of mnemonic, like a note that one might jot down in a calendar, which is adistillation of a sentence into its salient elements.

Consonantal writing is phonographic orthography without vowels, as is the case in Hebrew script. Generally, context is sufficient for determining the meaning of ambiguous terms. However, the language has low redundancy. The term of redundancy is borrowed from Shannon and Weaver, and is a property of information theory. “A system possessing relatively high redundancy is one where, in an average signal, the identity fo any given part of the signal is relatively easy to predict given the rest of the signal. Suppose that a policeman telephones to give you details of a suspect who needs to be looked out for, but because the line is bad you hear only some of the letters and numbers as they are spelled out: you hear the suspect’s name is F*ANK DAW*ON and his car registration is OWY 9*8P.” The suspect’s name in this example is easy to determine because English names have high redundancy. Car registrations have low redundancy, so the missing digit is impossible to reconstruct. Redundancy is an important consideration in written text, as well as in the laanguage used to communicate itself.

In terms of alphabet and construction, Han’gul composes graphs according to phonetic differences and is clearly differentiated. Graphemes map to phonemes, and similar phonemes have similar graphemes and vice versa. Syllables are organized into larger structures through construction. The tying of these graphs together is powerful for phonetics, but for language construction, I need a semantic system for developing a composed language.

Notable scholar of literature and new media, Katherine Hayles visited us in LCC last Thursday. Her presentation was about electronic literature, and about the practice of academic study of the humanities. The presentation was posed as a conflict between traditional and digital humanities. The traditional humanities are slow to understand the digital, but the digital must be able to build from the foundation of traditional. There are tacit and implicit differences between the two disciplines, indicating shifts and differences in modes of thinking. The primary differences occur along the lines of scale, visualization, collaboration, database structures, language and codes, as well as a few others. Hayles’ research was conducted by interviewing several new digital humanities scholars.

The most notable difference is the idea of scale. This relates to the sheer physical limitations in the capacity of the researcher to read the domain of study. Digital technology enables a broad, but shallow, analysis of a broad corpus of text. The example is of 19th century fiction. A scholar will have read around 300 to 500 texts, but these texts are atypical, notable works, which are read because they are outstanding, the ones that stand out. The nature of research, the questions, and conclusions change when a quantative analysis is possible. When it is possible to look at thousands of texts at a distance.

Franco Moretti poses reading texts at the greatest distance possible. Hayles described this as “throwing down the gauntlet to traditional humanities,” whose approach has been to do deep reading, looking within texts to understand psychology, allusions, and connections. Moretti attempts to read texts as assemblies, breaking them into pieces, without ever reading a whole text. This is a dramatic change in method, and comes across as wildly controversial. It is notable that Moretti does have experience of practice, and is well read and familiar with the corpus. He is able to employ this approach precisely because of this familiarity. Moretti focuses on analyzing texts in terms of devices, themes, tropes, genres, or systems. The practice of analysis amounts to a kind of distant statistical profiling. Moretti analyzes how genres are born and die, tracing genres which have passed, such as epistolary and gothic novels. Moretti’s conclusion is that genres die because their readers die (not necessarily literally, but in the sense that they move on to other material).

Another question is how do you tell when technology platforms emerge. Hayles’ example is Tim Lenoir. He makes the claim that algorithmic processing of text counts as a form of reading. Lenoir’s project traces citations among a set of scientific papers. This network develops and defines a relationship of connections. This is interesting because the analysis is of material entirely contained within the texts themselves, and does not actually analyze works in terms of some external system of values. The claim that this analysis is reading is inflammatory in the traditional humanities, where reading is a hermeneutic activitiy focused on interpretation. The problem is that the traditional understanding of reading is wedded to comprehension. Lenoir argues that, at a wide scale, textual meaning is less important, but what is really interesting are the data streams.

In common with Moretti, Lenoir is interested in finding patterns. Patterns do not require primary investment in meaning. The traditional humanities is instead intereested in hermeneutic interpreatation, which is bound tightly to meaning. These two perspectives are mutually opposed, but Hayles is interested in linking patterns with hermeneutic reading, finding some form of common ground from which these may build from each other.

One such example of a work which uses both strategies is Tanya Clement‘s analysis of Gertrude Stein’s “The Making of Americans.” This text is a traditional narrative through half of the text, but at some point in the middle, the narrative breaks down and becomes virtually unreadable. The text at that point is composed of frequently repeated phrases, content which is essentially an anti-narrative. A deep reading of such a text is difficult or impossible because of the very structure of the text itself. An analysis of pattern is necessary to deduce meaningful conclusions. Clement’s analysis finds that texts contains repeated 490 word sequences, where only a few words within these sequences vary. The analogy is made to the notion of character, as character is repitition with only slight variation. This is a way  of understanding the text which is arguably very valuable, but would be impossible without pattern analysis.

The traditional humanities is usually solitary, involving a deep communion between the reader and the text. Networked culture is interested in collaborative approaches to study, and when applied to study of texts and narrative, comes with a shift of assumptions in how to approach a text. One way of looking at this is in scale of participation, but another approach is to break up a text and treat it as a database. David Lloyd’s project “Irish Mobility” which chops up prose to remove references of subordination and cooperation. Then the resulting material is embedded into a database. This allows the user to “refactor” the content. The resulting piece becomes harder to read, but arguably the content is more meaningful. The resulting form is fragmentary hypertext, and enables the user control over the narrative.

Hayles gives a few examples of database projects used in education, wehre students build from each others’ work, and is published. Thus, their work continues to live beyond the class, and is valuable for sharing and feedback. These projects are less interested in representation, and more interested in communication and distribution.

Regarding language and code, Hayles gives a few examples. A succinct quote comes from Tanya Clement: “Software is an exterioralization of desire.” The writer of software must have an exact  articulation of what the computer must do, without tacit knowledge. Modifying code is generally easier than modifying tacit knowledge, and once created, it is also easier to observe because it is actually written and visible. Tacit assumptions are by their very nature concealed. This is not to say that digital systems are always explicit about their values, but they more clearly formulate their models, and thus the values are more concretely established within the system.

Disciplines are formed by the violence of exclusion, according to Weber. Disciplines achieve legitimacy by constructing boundaries. On one side of this boundary is placed the material which “belongs” in the discipline, and the other side is that which is excluded. This process occurs with astronomy and astrology: One side is given legitimacy while the other is denied it. The legitimacy of traditional humanities is threatened by digital humanities which is outside of the boundaries of the traditional in many senses.

We were not able to extensively discuss the relationship between language and code because the presentation was beginning to run out of time. The relationship between digital and traditional humanities is construed as a conflict. Hayles’ goal is to find a reconciliation between these two. However, the examples described are primarily data oriented approaches to texts and literature. The approaches of pattern analysis and interpretive hermeneutics presuppose a inherent content related difference in the reading of texts. I think that it would be useful to have a more process oriented approach, that focuses on the system rather than the structure of narrative. A common ground might be found in considering that both hermeneutics and the digital are dependent on process.