Ortony, Clore, and Collins define a cognitive approach for looking at emotions. This theory is extremely useful for the project of modeling agents which can experience emotions. The cornerstone of their analysis is that emotions are “valenced reactions.” The authors do not describe events in a way that will cause emotions, but rather, emotions can occur as a result of how people understand events. This approach is surprisingly subtle and nuanced. There are many constraints and caveats, but these are all logical considering the perspective of the model.

The goal of this book is not to claim that the representation of emotion is exactly correct, but that the approach for thinking of them is cognitively viable. Emotional systems, as analyzed, are culturally dependent. There is a claim for generality, but not for universality. Emotions may be understood in terms of eliciting factors and valenced reactions. This is the heart of the theory. The actual emotions that result, including how they are thought of, and the words we use to describe them, are not claimed to be absolute, necessarily dependent on the factors, or universal.

It is extremely challenging to study emotions. There is a conflation between emotions and emotion words. The study here looks at enabling factors and conceptualized situations. The challenge in this study is to determine the relationship between cognition and emotion. Existing theories are: arousal/appraisal, and activation/valence. These theories account for (1) what the emotions are, and (2) their relative intensity. The existing approaches of study tend to return to emotion words, which are problematic because of their cultural and linguistic dependence. Words tie into systems of meaning that surround language, and rarely map one-to-one with emotions themselves. Instead, the authors arrive at the following definition: “Our working characterization views emotions as valenced reactions to events, agents, or objects, with their particular nature being determined by the way in which the eliciting situation is constructed.” (p. 13)

The Structure of the Theory

A question that is introduced are “what are basic types of emotions?” The authors view these as being grouped together by similar eliciting conditions. An idea that is introduced is to test the theory with computer models. In these cases, the computer programs are not thought to experience emotion, but rather, to be able to understand human emotions. There is a concern about the humanistic and phenomenological issue of understanding emotions. It may be argued that experience is necessary to understand emotion. This argument is reasonable, but does not seem to be a problem in the structure, given the way the reasoning works here. The theory describes reactions, valences, and eliciting conditions, but not the actual experiences themselves.

The formulation of the emotion types relate to how the world is understood in terms of agents, objects, and events. How emotions might emerge is very dependent on how individuals actually perceive and interpret the events. The authors give a somewhat distressing example of the emotions one might experience on learning that their neighbor is a child beater (p. 20). The person might think of the neighbor as an agent, which would give rise to reproach because of violation of standards. Thinking of the event might give rise to pity for the neighbor’s children. The person might consider the neighbor as an object, and experience hatred. This is a complex network of emotions that may arise from a relatively straightforward situation, but they may be accommodated within the model. Models in games and other forms of social simulations rarely address the multiple ways that the world may be perceived emotionally.

A predominant approach in cognitive science of emotions has been to view emotions as arising from a palette of “basic emotions.” This has been supported by many authors, including Oatley and Johnson-Laird. These perspectives tend to perceive basic emotions as “low level” feelings such as anger, disgust, fear, joy, sadness, surprise (from Ekman et al., 1982). These are chosen based on actions and behaviors, universal facial expressions, instincts, etc. The view of these emotions as basic is inconsistent with the theory of emotions as valenced reactions. They poke a few holes in the basic emotion theories, especially with the conflation of anger with distress, or anger with aggression, and avoidance with fear. Anger especially is given as a complex and joint reaction: as a combination of distress and reproach, unlike other theories which describe it as basic. There is also a conflation of emotions with mental states, although this is particular to the definition of emotion given by the authors.

Mental states can lead to valenced reactions, but are not necessarily reactions in of themselves. An example given by the authors is abandonment. The state of being abandoned is not an emotion until the individual reacts to that state. Furthermore, the type of reaction can be dramatically different depending on how the individual construes the reception of the state. Mental states can affect emotions, for instance, surprise is a state, but it tends to intensify emotions that react to the surprising event.

The Cognitive Psychology of Appraisal

This section is on appraisal, which is how situations are interpreted, so as to enable valenced reactions. Appraisal operates on three levels: motivation, standards, and attitudes. The authors first discuss appraisal as it connects to motivations (which are generally referred to as goals). Motivation is also a good term, due to the depth given by Maslow. Goals on their own tend to be rather shallow, dwelling on one thing at a time. The focus at the moment is on goals. The authors acknowledge that goals as employed in life tend to be spontaneous as opposed to planned. They suggest that a goal structure as might be imagined by a person is “virtual”, meaning that it is self-perceived. This gives some flexibility, enabling a certain freedom in how individuals might imagine their goals as to construe reactions to them. In this sense, goals are imagined. A virtual goal structure may be improperly formed (subgoals may not lead to completion of supergoals) and the goals themselves may not even be what the individual wants.

The virtual goal structure forms a graph reminiscent of planning systems. Nodes (goals) relate to each other by links that describe necessity, sufficiency, inhibition, and so on. The framework which is used later is borrowed from Schank and Abelson. The different goals are Active Pursuit, Interest, and Replenishment (A, I, R). An active pursuit goal would be something that the agent is engaged in pursuing, an interest goal is something that the agent wants to occur (it may even be something impossible for the agent to achieve on its own!), and a replenishment goal is something which must be renewed with some regularity (such as satisfying hunger). Appraisal of motivation and goals relates to the emotions which are reactions to events. These affect the emotional dimension of desirability. Goals are usually desired, but an agent may have goals for things not to occur, which would make those events be undesired.

Standards, like goals, may not necessarily be consistent. Standards tie into the appraisal of agents, who may conform with the observer’s standards or not. The degree of conforming ties into the emotional variable of approval. Standards are complicated to formulate, but very flexible, especially in consideration of cultural value systems. Some examples of standards given by the authors are “one ought to take care of other people’s things.” So, in fictional domains, for instance, characters might have wildly different morals and standards, and these would affect how characters approve or disapprove of each other. Events which bear on standards can also be reacted to on their own, and yield event related emotions. Attitudes are much more obtuse, and relate to personal tastes. Attitudes affect the attraction emotions, which focus on objects rather than events or agents.

Desirability ties into goals, but also expectations. Appraisal of an event is done in perspective. The authors give an event of an IRS refund of $100, which would be desirable if one expected nothing or to owe money, but would be less desirable than a refund of $300. Praiseworthiness relates to standards, and because it relates to agents, a central variable is responsibility. An agent must be considered responsible in order to be accountable to standards. This perception of responsibility may not be rational (such as blaming the dog that ate your birthday cake, or the computer program that erased your paper), but it is consistent with our understanding of intentionality.

Appealingness reflects attitudes. An attitude is a disposition, which is not an emotion alone. One may have a disposition to like ice cream, but this does not indicate an emotion on its own, rather it indicates the potential for an emotion when ice cream is present. The relation between attitudes, dispositions, and emotions are difficult to express in language because common usage tends to conflate the concepts.

The Intensity of Emotions

There are 4 global variables that affect the intensity of emotion. Local variables are ones that affect the individual emotions themselves. Global variables affect all emotions that one might experience at a given moment. The authors divide between local and global intensity variables based on isolatability. Variables ought to be independent and not modulate each other.

1. Sense of reality. When the eliciting conditions are perceived as real, the emotions are more intense. This has to do with both literal understanding of reality (the plane might be delayed, versus the plane is delayed), as well as a sense of investment. If an aspiring author wants to write a best-selling novel, then the emotions associated with the success of the novel will be relative to whether the author considers the project to be realistic or a fantasy.
2. Proximity (psychological). Proximity relates to factors such as time, so emotions pertaining to remembered events are less strong than the experience of the events. Proximity also relates to psychological nearness, as relates to reactions to consequences for others. Proximity can be an issue in the case of reactions to tragedies in far away places, or good or bad things happening to strangers.
3. Unexpectedness. Unexpectedness relates to both likelihood and suddenness. Reactions to a sudden catastrophe is more intense than one that was forseen (although the emotions themselves may change from shock to self-reproach). The disappointment at losing at the lottery is less severe because loss is expected, than say being rejected from a job application which seemed very likely. The intensity due to unexpectedness has much to do with the perceived normality of the situation.
4. Arousal. Arousal is the total experience of emotions that one has experienced over a period of time. Gradually, arousal dissipates, but successive reactions can increase arousal, which will in turn, increase the intensity of subsequent reactions. The authors give an example of someone who is preparing breakfast for his family, but everything goes wrong. He burns the toast, forgets to start the coffee soon enough, overcooks the eggs, and so on. These events lead to reactions which ultimately cause a great deal of frustration. He might slam cabinet doors or speak rudely to people. The situation may be attributed as events, or as agents (either the cook or the appliances are agents which are behaving irresponsibly), and these reactions may activate scripts about personal failure and inadequacy.

The chief local variables are desirability, praiseworthiness, and appealingness, as discussed in the previous section. The authors introduce further local variables that pertain to other emotion types:

1. Desirability: event based emotions. (pleased/displeased)
2. Praiseworthiness: attribution emotions. (approving/disapproving)
3. Appealingness: attraction emotions. (liking/disliking)
4. Desirability for other: fortunes of others. Whether the event is desirable for the other.
5. Deservingness: fortunes of others. Whether the other “deserves” the event.
6. Liking: fortunes of others. Whether the other is liked or not. These distinguish between: happy-for, pity, gloating (schadenfreude), and resentment.
7. Likelihood: prospect emotions. (hope/fear)
8. Effort: prospect emotions. How much effort the individual invested in the outcome.
9. Realization: prospect emotions. The actual resulting outcome. These distinguish between: relief, disappointment, satisfaction, and fears-confirmed.
10. Strength of identification: attribution emotions. The stronger one identifies with the other, that distinguishes between whether pride or admiration is felt.
11. Expectation of deviation: attribution emotions. Distinguishes whether the other is expected to act in the manner deserving of admiration or reproach. These distinguish between: pride, shame, admiration, reproach.
12. Familiarity: attraction emotions. (love/hate)

Reactions to Events: I

The authors give a fine grain analysis that explores specific context of emotion instances. Loss is a specific instance of distress in this typology, and other emotions, that are kinds of losses derive accordingly. Grief is loss of a loved one, homesick is loss of the comforts of home, loneliness is loss of social contact, lovesick is loss of the object of romantic love, regret is loss of opportunity (p. 91). These may be considered different emotions in the sense of emotion words, but derive from the same kinds of experiences, the same kinds of reactions.

Reactions to Events: II

The authors give a table of relative outcomes matched with prospects and expectations. This lends to a mix of prospect and well being emotions. (p. 129)

Newell and Simon are enormously influential in AI and cognitive science. Their approach to human problem solving has however been a favorite target for criticism among advocates for embodiment, situated action, and activity based approaches to cognition. I have been finding myself taking up the mantle of this group, so I am approaching Newell and Simon from a critical perspective. It is not my aim to reject symbolic approaches to problems and problem solving, but rather to change how symbols are conceived of and used.

This is the text that introduces the General Problem Solver, or GPS. GPS eventually was transformed into Soar, which remains a usable problem solver.

Introduction

Early on, the authors introduce the aim of the book as to develop a theory of cognition. Cognition is framed as a combination of three elements, which are performance, learning, and development. The emphasis in this book is performance, which is how cognition is used. The study of the book is introduced very early: “The present study is concerned with the performance of intelligent adults in our own culture. The tasks discussed are short (half-hour), moderately difficult problems of a symbolic nature. The three main tasks we use–chess, symbolic logic, and algebra-like puzzles (called cryptarithmetic puzzles)–typify this class of problems. The study is concerned with the integrated activities that constitute problem solving. It is not centrally concerned with perception, motor skill, or what are called personality variables.” (p. 3-4) This isolation of the problem is very specific and cuts out a huge class of cognition and activity. We should take Newell and Simon’s conclusions from this study as being applied specifically to this domain of problems, but it often gets conflated with something much greater. Performance and problem solving of chess, logic, and cryptarithmetic puzzles are not at all representative of cognition on the whole.

Performance on problems is compared to learning. Learning is described as a secondary activity, which is primarily dependent on performance. This type of reasoning is directly at odds with work by Vygotsky and Tomassello and other developmental psychologists. The study also omits “hot cognition,” which is cognition that is emotional, reactive, or dependent on personality. These forms of cognition are arguably much more embodied than the “cold” problem solving described by the problem domain. The authors argue that hot cognition should follow and derive from problem solving. This is emblematic of a trend in this form of thought, that other more tricky areas of cognition can just be added on to the architecture.

The study can also be viewed as a theory of psychology. Unlike other forms of theories, this one is content oriented (as opposed to process-oriented). Here the authors explain that a content oriented theory can serve as a model for the content: “The present theory is oriented strongly to content. This is dramatized in the peculiarity that the theory performs the task that it explains. That is, a good information processing theory of a good human chess player can play good chess; a good theory of how humans create novels will create novels; a good theory of how children read will likewise read and understand.” (p. 10-11) What is described here seems to be a generative model, as opposed to an analytic model. However, this authors’ claim is fraught with three counterexamples. Chess programs approach a game of chess very differently than chess players do. Algorithms for story generation (to say nothing of whole novel generation) are leagues behind actual human writers. And text understanding systems are also fraught with difficulty (notably the Bar-Hillel problem for word contextualization).

There is another more fundamental critique with the claim that a content oriented theory will perform the task in question. The issue is that a theory does not actually practice or perform the task that humans do, it merely models it. AI does not think, but it models thinking. It does not solve problems, but solves models of those problems. This distinction is subtle but important. If a problem is easily and non-problematically transformable into a symbolic model, then the solved model should solve the actual problem, but this is only as good as the transformation of reality into the model. Someone may program a computer to solve a model of a problem, such as a disease outbreak, but if the model in the program omits crucial details that arise in the complexity of real life, then the solution is intrinsically flawed.

It is relevant to note the authors’ use of the word “dramatized” in the citation. Dramatization can take on an interesting meaning here when compared to the elements of performance, resemblance, and enactment. A wholly legitimate way to examine AI and problem solving is that the computer dramatically enacts the problem. That is, it represents the problem and the solution dramatically, in the sense of performing to the user meaningfully.

Task Environments

Problem solving takes place in a task environment. The task environment contains the symbolic content necessary to solve the problem. The authors propose using the model of the rational economic man (who maximizes utility). The task (and hence utility) are defined by the task environment: “The term task environment, as we shall use it, refers to an environment coupled with a goal, problem, or task–the one for which the motivation of the subject is presumed.” (p. 55) Performance is inextricably tied to rationality, and the situation is transformed to the task environment. Task environments are internally represented. The internal representation is a symbolic construction which illustrates the problem space: all moves, states, and outcomes.

Internal representations are tied to linguistic structure (which is inherently semiotic). For transcribing problem solving into an information processing system, objects are mapped to symbols. This is unproblematic in the examples given (chess moves, symbolic logic problems), but is much more troublesome in other situations. Even in the example of a chessboard, there are many ways to look at the positions of pieces and encode them symbolically. For example, a pattern would probably be treated as a symbol by a grandmaster. It is obvious to represent piece coordinates as symbols, but it is not the only approach. In domains where the units are less obvious, the symbolic transformation is even more fraught with complexity.

Newell and Simon give their definition for a problem: “A person is confronted with a problem when he wants something and does not know immediately what series of actions he can perform to get it.” (p. 72) This definition alone is rather interesting. Here, a problem is tied to desire as well as possession and attainment. These are very embodied qualities. Given this definition, it is far from obvious what it would mean for a computer to be confronted with a problem. The answer the authors give is that problems can be represented using symbols, as constructed from set or 1st order logic.

Problem Solving

The problem solving process given resembles the architecture of Soar. (p. 88)

1. An initial process, here called the input translation, produces inside the problem solver an internal representation of the external environment, at the same time selecting a problem space. The problem solving then proceeds in the framework of the internal representation thus produced–a representation that may render solutions obvious, obscure, or perhaps unattainable.
2. Once a problem is represented internally, the system responds by selecting a particular problem solving method. A method is a process that bears some rational relation to attaining a problem solution, as formulated and seen in terms of the internal representation.
3. The selected method is applied: which is to say, it comes to control the behavior, both internal and external, of the problem solver. At any moment, as the outcome either of processes incorporated in the method itself or of more general processes that monitor its application, the execution of the method may be halted.
4. When a method is terminated, three options are open to the problem solver: (a) another method may be attempted, (b) a different internal representation may be selected and the problem reformulated, or (c) the attempt to solve the problem may be abandoned.
5. During its operation, a method may produce new problems–i.e., subgoals–and the problem solver may elect to attempt one of these. The problem solver may also have the option of setting aside a new subgoal, continuing instead with another branch of the original method.

Logic: GPS and Human Behavior

Work here shows students solving problems and their actions written in the formal logic of GPS. Experimental subjects are either Yale or CMU students. The question of what the students are doing seems to trace back to their formal logic training. The problem domain is still a highly symbolic one to begin with. The problem solving approach is thus not really a representation of how humans solve problems, but how problems tend to be solved within the formal structure of this problem domain.

The Theory of Human Problem Solving

This section is where GPS (and Information Processing Systems in general) are translated into human problem solving. Obviously, my scruples are with the assumptions. The propositions which pose the questions for human problem solving (the assumptions) are these: (p. 788)

1. Humans, when engaged in problem solving in the kinds of tasks we have considered, are representable as information processing systems.
2. This representation can be carried to great detail with fidelity in any specific instance of person or task.
3. Substantial subject differences exist among programs, which are not simply parametric variations but involve differences of structure and content.
4. The task environment (plus the intelligence of the problem solver) determines to a large extent the behavior of the problem solver, independently of the detailed internal structure of his information processing system.

The propositions to be answered by the chapter are as follows: (p. 788-789)

1. A few, and only a few, gross characteristics of the human IPS are invariant over task and problem solver.
2. These characteristics are sufficient to determine that a task environment is represented (in the IPS) as a problem space, and that problem solving takes place in a problem space.
3. The structure of the task environment determines the possible structures of the problem space.
4. The structure of the problem space determines the possible programs that can be used for problem solving.

External memory is discussed, but affordances and cognitive extension into situation or environment are not discussed. This has a very mentalistic approach, where symbolic structure of environment is not addressed. The only symbols are in the problem space itself.

This book is about an approach to commonsense reasoning that is implemented using formal logic. Mueller does not make the claim that humans make use of formal logic structures in understanding the physical world, but rather that this is a way for commonsense physical phenomena to be understood computationally. The approach does not replicate or even simulate the human method of cognition or understanding, but rather gives a formal account of relationships. Commonsense systems could be applied towards making predictions, performing diagnostics, or analysis within a simulated or artificial environment. Mueller uses classical first-order logic, and every element of commonsense reasoning takes the form of axioms that work within that space.

Mueller lays out a set of four assumptions that guide the rest of the investigation. These assumptions are certainly contestible, but they can be seen as a basis on which the rest of the work can be derived. (p. xx)

• I assume, along with most cognitive scientists, that commonsense reasoning involves the use of representations and computational processes that operate on those representations.
• I assume along with researchers in symbolic artificial intelligence, that the representations are symbolic.
• I assume, along with researchers in logic-based artificial intelligence, that commonsense knowledge is best represented declaratively rather than procedurally.
• I use the declarative language of many-sorted first order logic.

The formulation of commonsense reasoning accounts for a number of specific properties of real world objects. This contains the vocabulary and the elements that will be formalized into axioms of the commonsense reasoning logic. One noteworthy flaw within this is the element of perspective. For someone to have common sense, that individual must have a perspective. Mathematical logic in abstract does not have a perspective that is readily apparent. Even thought this logic can make commonsense conclusions, it still has a view from nowhere. (p. 7-8)

1. Representation. The method must represent scenarios in the world and must represent commonsense knowledge about the world.
2. Commonsense entities. The method must represent objects, agents, time varying properties, events, and time.
3. Commonsense domains. The method must represent and reason about time, space, and mental states. The method must deal with object identity.
4. Commonsense phenomena. The method must address the commonsense law of inertia, release from the commonsense law of inertia, concurrent events with cumulative and canceling effects, context-sensitive effects, continuous change, delayed effects, indirect effects, nondetermnistic effects, preconditions and triggered events.
5. Reasoning. The method must specify processes for reasoning using representations of scenarios and representations of commonsense knowledge. The method must support default reasoning, temporal projection, abduction, and postdiction.

Commonsense logic originated with situation calculus as created by John McCarthy and Patrick Hayes in the 1960s. This was the inspiration for Robert Kowalski and Marek Sergot to develop event calculus, which is the method of Mueller’s investigation. The foundation of event calculus relies on the understanding of events and properties that change over time. Time dependent properties are called fluents, which could be typed variables or true-false values. Events are any occurrence that can happen within the world. Time in the event calculus is linear, and can be either discrete or continuous.

There are four main predicates that work on the event calculus (p. 11). Note that these are not elements of a “new” logical structure, but are rather constructions within the framework of first order logic.

1. HoldsAt(f, t) represents that fluent f is true at timepoint t.
2. Happens(e, t) represents that event e occurs at timepoint t.
3. Initiates(e, f, t) represents that, if event e occurs at timepoint t, then fluent f will be true after t.
4. Terminates(e, f, t) represents that, if event e occurs at timepoint t, then fluent f will be false after t.

Using these elements, many axioms can be declared. These define the ordering of time, how effects may be defined or triggered, how events may be preconditions, what cumulative effects are, what abnormal states are, and so on. These are elaborated in detail throughout the book. They work together to form a representation of commonsense reasoning within a domain. In addition to these axioms, a domain must include observations of the world’s properties at various times, and a narrative of the known events in the world (p. 35). Mueller gives a formal definition for a domain description (p. 37):

• Positive effect axioms, negative effect axioms, release axioms, effect constraints, positive cumulative effect axioms, and negative cumulative effect axioms.
• Event occurrence formulas, temporal ordering formulas (the narrative).
• Trigger axioms, causal constraints, and disjunctive event axioms.
• Cancellation axioms.
• Unique names axioms.
• State constraints, action precondition axioms, and event occurrence constraints.
• Trajectory and antitrajectory axioms.
• Observations.
• Event calculus axioms.

This is an extensive list, but composed together it represents what would completely define a domain within the calculus. This is actually quite contestible when compared with human reasoning. Human reasoning is necessarily incomplete, and much of the logical formulations are never explicit. For the purposes of logical reasoning, it still seems somewhat rigid and inflexible. It is severely dependent on total objective knowledge. With missing or incorrect knowledge, the logic might be crippled.

Later on, Mueller gives a chapter on the Mental States of Agents. This too gives an external and objective perspective on the modeled phenomena. It necessarily has an external omnitient view inside the minds of the emotional agents. The ostensible goal of this is to develop a system which can reason about emotions, but that too depends on issues of understanding and perception. Agents themselves, as modeled, have beliefs, and thus are subject to some perspective, but the logic will reason about those beliefs without perspective.

Mueller first gives a version of the Beliefs, Desires, and Intentions framework (listed as Beliefs, Goals, and Plans). This gives a clear logical account for conclusions that may be derived from BDI agents and environments. This reasoning is still very complex, but could be made more rapid though computational implementation.

Next, there is a logical formulation of the emotion theory developed by Ortony, Clore, and Collins. The formulation uses the system of eliciting conditions. The goal is to make logical conclusions about the emotions of agents when events occur. This work creates definitions for the predicates, Joy(a, e), meaning that agent a is joyful about event e, and goes to more complicated predicates such as Appreciation(a1, a2, e), which means that agent a1 is appreciative of agent a2 for performing action e. Following this is a large series of axioms which formally defines the relationships between the various predicates of deirability, belief, joy, distress, hope, resentment, and so on.

Default reasoning is constructed using vanilla 1st order logic, not with any messy nonmonotonic logic, or probabilistic reasoning. The perspective here relies on a total account of abnormal conditions, and a total knowledge of the states of objects. This formulation is especially problematic from a sociological perpective because of its emphasis on the cases of normality. An example given is that apples are red, unless some abnormal condition applies, such as that the apple is a Granny Smith, or is rotten. Of course, the claim of normal or default conditions is highly contestible, and an architecture that encourages defaults could lead to problematic assumptions.

I made a mistake in my posts on Tristram Shandy and If on a Winter’s Night a Traveler. These two unconventional narratives have a playful element, and I was describing this as ludic. That actually was not the word I was looking for. I was digging through some notes the other day and found some notes that I took when Marie-Laure Ryan visited, and found a comparison between paidia and ludus. Paidia represents uncontrolled play, whereas ludus is structured and goal oriented. So, the comparison that I meant to make earlier is that both Sterne and Calvino embraced paidia, whereas most narratives and novels have a form that more resembles ludus.

The distinction between paidia and ludus are outlined by Callois. Chris Bateman gives an excellent analysis of the complexity between the two.

The title is a bit misleading, it is actually “The Life and Opinions of Tristram Shandy, Gentleman”

Sterne’s work is important in understanding one of the borderline cases of narrative. Despite being published six decades before Austen’s Pride and Prejudice, it is a work that seems deceptively modern, or even postmodern. It would be very easy to draw comparisons between Sterne’s writing and the “lines of flight” described by Deleuze and Guattari.

As a work, Tristram Shandy is erratic and nonlinear, circular even. The premise is that the book documents the life of the eponymous subject, who is the narrator, but the main subjects of the book are his father, Walter Shandy, and his uncle Toby. There are a number of other characters who come into play, as well, but the focus is on those two. In the first volume, the narrator is trying to tell the story of his life, but really, he can’t begin to do that before accounting for his birth, and then his conception, and then the life of his parents before hand. The narrative is endlessly digressive, and draws connections between all manner of works of philosophy, science (of the time, of course), and history. Essentially, as the narrator is trying to tell a complete story of his life, he cannot do so without expanding to include more than could ever be written within his lifetime.

One of the reasons for this is that philosophy and science, especially the eclectic, have an essential role in making sense of everyday life. The living world connects to many disparate systems of meaning. Thus, there is a sort of art of connecting, in drawing allusions between everyday life and works of science and philosophy. This idea of naturalism works in contrast to the literary movement of realism (which in itself was a very particular type of narrative), which focused on life alone without connections to other realms. Sterne was interested in parodying this, and exposing a paradox of literary fiction: To capture anything in its true depth will exceed the time of the thing being described. Eventually, when all approaches are exhausted, time changes from exposition, to instead moment by moment direct communication.

The reading of the book seems like it might be well equated with hypertext. Wikipedia is an invaluable aid of making sense of the many connections and allusions drawn within the writing, and with all of his analogies, Sterne is drawing the reader through what really feels like a hypertext experience. The connections are not directed, but demonstrative. The characters are not really driven to achieve specific goals, but rather, understand themselves and the world around them. Most other novels are framed by some sort of goal or obstacle, especially in the bildungsroman tradition. The result of this shift in emphasis is that Tristram Shany has a ludic quality. I mentioned the term “ludic” in reference to If on a Winter’s Night a Traveler, and the essence of that comparison is that both the reader’s engagement as well as the characters’ activities are playful.

In Tristram Shandy, the reader must be active. The reader is required to make creative interpretation in order to get meaning out of the text. Because the experience is nonlinear, cut up, even, the reader is responsible for gathering the pieces and putting them together into a coherent whole. Sterne’s writing illustrates the connections to many parts of his world, and these connections must be brought and woven together to put that world together.

Some final notes from Ian Watt’s introduction: The book is not a novel. It fails at that because it is incomplete. Similarly, its system, and there certainly is one, must come off as playful, rather than gamelike explicitly. There are virtues of exploration and balance. It connects the deepness of nature and philosophy to the triviality of life.

Italo Calvino is an important figure in narrative. Calvino’s fiction can be described as modern or postmodern, in that it pushes some conventional boundaries of fiction. Despite this, unlike many other postmodern writers, Calvino is accessible and deeply enjoyable, without being any less profound. Because my work is on adaptation of fiction, and my particular approach is modeling of fictional worlds, it is important to see how my theories hold when pushed to some of the boundary cases of fiction and literature.

If on a Winter’s Night a Traveller is important because of its reflexivity. When asked what it is about, the clearest answer is to say that it is a book about reading. Specifically, it is about the experience of reading, the pleasure of reading, and the relationship between reading and writing. At times, it reads like Calvino is poking a great deal of fun at Barthes’ Death of the Author. I normally think that writing is about building worlds, and to some extent, building dramatic structures, but to Calvino it comes down to experience and imagination.

The book spells out a great many scenarios. It is almost like a laboratory, to see as many takes on reading and writing that can be explored within its pages. The protagonist of the book is the Reader (who is explicitly male). There is imaginative speculation of the reader fatasizing about the Other Reader (who is explicitly female), who is reading the same book. The Reader imagines the experience of the Other Reader as she reads the same pages that he reads. Later on, narration shifts to the perspective of a writer who watches a woman reading from his balcony, and voyeuristically fantasizes that she is reading the book that he is writing.

These scenarios are important because they playfully illustrate the complex relationships between reading and writing, as human dimensions. It is important too because it exposes a broader model. Beyond the model of a story world itself, Calvino exposes the model between authorship and readership. Because the novel is written so reflexively (but playfully so) the nature of this model is made very visible, so that the real reader can think and reflect upon it. Play is a central element in Calvino’s novels, and gives the story a ludic quality, rather than a formally structured one.

The introduction by Peter Washington yields some important notes. “By Presenting possible worlds, he can remind us that there are alternatives to the present order of reality. Most important of all, he can practice the negative but essential virtue of encouraging his readers to take nothing on trust.” (p. xiii)

Calvino was inspired by texts outside the Leavisite “Great Tradition”: Cervantes, Sterne, Stevenson, the Decameron, and the Arabian Nights. It is worth noting that the novels of the great tradition can probably be seen as having an explicitly formal structure, specifically, one that could be expressed in rules with a clear objective. The form of the novel itself is not necessarily intrinsically gamelike, but novels frequently have a structures that resemble those commonly used in games (notably progression and bildungsroman, as well as Cambell’s hero’s journey). Works outside the “Great Tradition” tend to be nonlinear, multiform, self-referential, and so on. These have a format which is much less gamelike, because they lack that sort of formal structure. Instead, they are ludic, abstractly playful. Calvino’s writing is like this: it is inherently joyful and delightful and rich with play.

Over the course of the book, the protagonist is the Reader, but the Reader remains an ambiguous character. Presumably, the reader is initially the actual person reading the book, Calvino speculates on what the Reader’s habits and situation might be, but then the Reader becomes more active and more specific. The sections about the Reader are written in the second person, much like roleplaying narration.

Neil Postman is an interesting figure. His book “Amusing Ourselves to Death” can be read not only as a vicious attack on television, but also on any form of media or mass communication. The style and tone of his writing makes him seem old fashioned and stuffy. He comes off as hostile towards media and dismissive of anything that takes people away from that nostalgic golden age where people actually read books. It is easy for those of us who grew up with television, video games, and, more recently, the internet, to read Postman and imagine counterexamples to all of his arguments. No, we might say, media has a positive role in our lives, and we have been made stronger for it. Such an argument is valid, certainly, but it is reacting against Postman’s words alone and not some of the deeper themes that lie underneath them. Postman might say that television affects us negatively, we might claim that it affects us positively, but the point is that it affects us nonetheless.

The claims about affect fall within the larger frame of technological determinism, but there is something more present in Postman’s book. In order to take control over media, so that we can use it positively, we must understand its agenda. Following from McLuhan, Postman argues that each medium has an agenda. To not be manipulated by this agenda, we must be aware and critical of it. This concept has been called media literacy. Digital media is not only a medium of its own, but is a conduit, a channel for many other media and systems, each of which have their own agendas. Specifically I am interested in simulation, and thinking about the agendas of simulations, which are often closed, like television, concealing their agenda beneath their surfaces. I want to consider a practice of simulation literacy, where the methods, assumptions, and epistemology of a simulation can all be put under scrutiny.

The Medium is the Metaphor

Before the book begins, Postman presents an analogy which sets the tone and climate for the rest of the book. He compares two authors, Orwell and Huxley, who wrote of terrible dystopias. Their visions both present worlds where people are controlled, but through very different means. Orwell is generally more widely recognized, and his dystopia 1984, presents a world where books are burned and history is rewritten. Huxley’s Brave New World is one in which there is no need to burn books or rewrite history, because no one reads anyway. Postman sums them up neatly: “In short, Orwell feared that what we hate will ruin us, Huxley feared that what we love will ruin us.” One of these worlds is implicitly the direction that the future is heading. The underlying assumption behind this is that we are slouching toward some dystopia anyway.

Postman’s writing comes across as extremely dated, as though he is appealing to some idyllic period in which spectacle was never a factor in communication. There are a couple of examples of how media has restricted the range of what is possible. A presidential candidate must necessarily now be telegenic. This is definitely true, though. Once media has been introduced, it must be accounted for. By virtue of this, media affordances have restricted what is or may be possible. Behind the moralizing, this restrictive nature of media is still real.

There is a religious element to Postman’s objections to television which is hardly surprising. The relationship between the iconography of media and the religious sin of idolatry reveals a deep spiritual unease with the representational power of media. By virtue of its semiotic nature, media and technology have the power to transform icons and images, and this has a profound affect on thinking and conceptualization.

Media as Epistemology

Postman gives a review of the requirements of reading and print culture. This idea translates directly into the notion of print literacy. The first of these requirements are physical and very basic, but they give way into deeper and deeper requirements of comprehension and analysis, which are not even verifiable. It is impossible to measure whether someone truly understands a text, especially when connected to the vast cultural network of meaning. This is literary intelligence at its highest level, and it is by no means easy. To claim that someone is literate means to go beyond the basic ability to understand sentences, but to also go to these deeper roots of making sense of the text, and knowing how to make sense of the text. The practice of meaning making has no set measure or procedure.

I raise these issues because they expose that print-intelligence or print-literacy is not some simple or easy idea. This direction undercuts Postman’s work somewhat, as he means to explain that this form of intelligence was common before television. It is arguable that this may be the case historically, but it is not the case generally. Thus, instead of being a conflict between types of media, we can view Postman’s argument as a conflict over literacy.

The Typographic Mind

The key characteristic of the typographic medium is exposition. Exposition is a mode and methodology. It is the epistemology of the literary medium. “Exposition is a mode of thought, a method of learning, and a means of expression. Almost all of the characteristics we associate with mature discourse were amplified by typography, which has the strongest possible bias toward exposition: a sophisticated ability to think conceptually, deductively and sequentially; a high valuation of reason and order; an abhorrence of contradiction; a large capacity for detachment and objectivity; a tolerance for delayed response.” (p. 63)

I would argue that the idealization of this is somewhat fallacious. The “era of print” certainly had its share of spectacle, irrationality, and logical falsehoods. The ideas here are still important, though. Exposition is still a value of print, and it is an affordance.

The Peek-a-Boo World

Telegraphy enabled instantaneous communication, but also came with decontextualization of information. Postman argues that it inflicts a kind of impotence on the communicated content. Because it is deprived of context, he claims that the new information ceases to be meaningful or relevant. This is unfair. If we were impotent in the age of the telegraph, then we were impotent before. This also comes with the implicit assumptions that the receivers of information are wholly passive. Postman argues that the information-action ratio was greatly diminished after telegraphy, which may be true, but a diminished ratio does not indicate a reduction in the actual action itself.

The heart of the matter is that television has become a myth in the sense of Barthes. It is invisible, unquestioned, and only accepted. Postman’s idea is that the communicated artifacts of television should seem bizarre and not natural. The world seen through television seems natural, even though it is false. Postman’s goal is to make visible the epistemology of television, to expose the transformational process so that it is denaturalized. This reverberates with Barthes agenda in Mythologies, to reveal how mythologies are present and prevalent and influential even though they are invisible.

We can make a comparison to games and internet culture, but by virtue of being new media, they are perpetually under analysis and criticism. They have not yet become totally naturalized, but, some conventions are moving in that direction. Postman’s analysis of television is holistic and reductive, but exposing epistemology is key in developing new literacy.

The Age of Show Business

Good sound byte here: “Each technology has an agenda of its own. It is, as I have suggested, a metaphor waiting to unfold.” (p. 84) Later, “Entertainment is the supra-ideology of all discourse on television. No matter what is depicted, or from what point of view, the overarching presumption is that it is there for our amusement and pleasure.” (p. 87) This is in comparison to print, whose supra-ideology would be exposition. It is ambiguous what, if any, supra-ideology computation must have.

“Now . . . This”

The argument here goes to support the literacy theme. Things viewed on television, the news specifically, seem implicitly credible. Because things are presented accurately, they are understood as truth. Books still can and do this, using all manner of fallacies. Postman seems to imply that, as television is new and immediate, it is more credible. Maybe this relates to media maturity. Alternately, the argument seems to be that since entertainment is the content of television, truth is irrelevant. This reverberates with McLuhan and Raymond Williams.

The Huxleyan Warning

There is an argument here, not for literacy exactly, but for awareness and skepticism. Technology is ideology. “To be unaware that a technology comes equipped with a program for social change, to maintain that technology is neutral, to make the assumption that technology is always a friend to culture is, at this late hour, stupidity plain and simple.” (p. 157) The argument is steeped with technological determinism, but is still compelling. Introduction of the alphabet changes culture at a cognitive level, and instantaneous communication produces a social and cultural revolution. This claim sounds like the types of claims, alternating between doomsaying and social revolution, that the internet would have on culture. An argument against Postman is that culture has motivational and self regulating forces of its own. While it may be affected, it still works to regulate itself. This counterargument is also valid, but the culture is still changed. Without awareness, it may not regulate itself positively.

To produce this awareness, Postman explains that we must change how we engage with television. “The problem, in any case, does not reside in what people watch. The problem is in that we watch. The solution must be found in how we watch. For I believe it may be fairly said that we have yet to learn what television is.” The focus on information brings Postman’s critique straight into digital media.

Further: “In any case, the point I am trying to make is that only through a deep and unfailing awarenss of the structure and effects of information, though a demystification of media, is there any hope of our gaining some measure of control over television, or the computer, or any other medium.”

This book is about a shift in the study of cognition into the idea of practice. Lave’s book is the construction of a complex argument to free the understanding of cognition from the limits imposed by traditional methods of study. As far as this goes, Lave asserts that the use of the laboratory and theory impose certain values into the study of cognition, classifying some uses of cognition as superior to others. Additionally, these approaches also yield incorrect results. For example, the first part of the book challenges the idea of learning transfer, which would be valid if we the functionalist theory of cognition held. Lave demonstrates that learning transfer clearly does not occur in practice.

A lot of ground is covered in this book, and Lave makes some very progressive and compelling arguments. Her work can be considered a criticism of functionalism in all its forms, which would include mental model theory. Having found model theory useful for many purposes, I would posit that practice can be understood in terms of models. This requires a subtle understanding of what a model is: a consistent system of meaning that comes with a way to interpret and translate things in the world into symbols in the model. Lave’s argument could easily be extended to argue that all theories are practices, but I would extend this further and say that theories and practices are both models in turn.

Psychology and Anthropology I

An opening example is how arithmetic is used in everyday life. Problems that ordinary people face are very unlike problems that might be specified in a classroom sort of setting. In the introduction, Lave gives an example of a shopper who is buying apples, and rationalizing how many apples to buy. As presented, arithmetic is a tool that is used in everyday life, not as an explicit approach, but rather as something like duct tape, to be used for estimations than exact calculations. Classical mathematics studies math as an artifact, a whole subject, rather than a tool.

Lave gives a solid critique of functionalist theory. This is characterized by several points (p. 8):

• Passivity of learner: The learner is passive and receives knowledge without having an active role in its learning or use.
• Isolation of skills: Skills may be separated and understood atomically. Separation is unproblematic, and usage is not dependent on context.
• Leads to meritocracy: The use and adeptness at arbitrary skills leads to a value system where proficiency at one skill indicates general superiority.
• Stress on rationality and cognitive life: This is as opposed to usage and practice.
• Cultural uniformity: If the functionalist theory holds, then skills and functions transcend culture, meaning that culture must have uniform basis.

The book is organized into two parts: The first is a critique of the practice of cognitive theory. This challenges the functionalist emphasis on learning transfer, and the artificiality of the laboratory method. The theme of this argument is around the idea of ecological validity, where a theory is ecologically invalid if it fails to be supported in a diversity of settings. The latter half of the book explores and emphasizes the study of practice in of itself.

Missionaries and Cannibals (Indoors)

The section here is trying to understand the role and concept of knowledge transfer, the process by which knowledge from one domain is transferred to another. Presumably this happens analogically. The actual results of experiments about knowledge transfer obtained mixed conclusions. These experiments give students a math problem, which may be solved algorithmically, and give the students other problems which are isomorphic in some way. Students do not make the necessary leaps in these sorts of problems, and generally seem very confused. A functionalist theory would support a sort of reductive understanding and transfer, but this does not hold. Incidentally, this type of transfer is exactly the sort of mechanism by which Newell’s GPS worked.

Lave gives a critique of the method by which students were presented with problems in the learning transfer studies. “A number of problem characteristics are common to all four papers and by extension to the genre more broadly. The puzzles or problems are assumed to be objective and factual. They are constructed ‘off-stage’ by experimenters, for, not by, problem solvers.” (p. 35) Thus, the problems are presented as tests, and come replete with the values of producing a correct solution. These have an overall trend of disempowering the subjects, depriving them of suitable context or situation.

The learning transfer experiments rely on a sense of knowledge as component based or modular. In this point of view, knowledge is put into domains, which function like disconnected islands. However, this point of view, and the problems themselves, are cultural artifacts.

Life After School

To find an alternative to traditional problem solving, Lave conducted a study called the Adult Math Project, which studied how ordinary people use mathematics in everyday life, and more specifically, grocery shopping. This study found that people are remarkably successful at math problems, (framed both on paper, as well as in the store) but they use dramatically different methods than those taught in school.

A problem I found with her study, though, is that it is placing supermarket decisions primarily in terms of cost. This relates back to the fallacious idea of the rational consumer. Supermarket choices may factor in cost, but also have a great deal to do with social and class awareness and attitudes, preferences, and identity.

Psychology and Anthropology II

Lave is attempting to undermine the false dichotomy of scientific and “everyday” thought. This descends from dualism and cultural colonialism. The central theme in this is that science itself is a practice, and that it is culturally constructed.

Inside the Supermarket (Outdoors) and From the Veranda

The goal in this section is to develop a theory of practice. The first part of this is to distinguish between practice and formal knowledge domains, or conceptual spaces. A primary difference is that practice occurs simultaneously within other activities, and may be synchronized with them to some degree. An example of this that Lave gives is knitting and reading. Instead of taking place individually, they are situated within each other and affect each other.

There is a concern over the form of scientific inquiry. This may be seen as a concern over model building. How do we decide what to model, or decide what is important or relevant? This is an authorial judgement, and comes in part with judgement of value. Lave asks, “Further, who is to decide what cognitive phenomena are significant objects of study, and how? Are guidelines to be found in normative models of cognition, in an investigation of the activities of peoples’ lives, in some combination, or in other sources altogether?”

To address this concern, she introduces the idea of ecological validity. Experiments are ecologically valid if they get the same results regardless of situation. This is important for the study of cognitive science, because the way people think within a laboratory setting may be different in some ways than how they think outside. If a cognitive experiment yields one set of results within the laboratory, but totally breaks down outside, then the theory on which that experiment is based must be questioned.

An experiment that Lave critiques a great deal in this section is another supermarket math experience, conducted by Capon and Kuhn. Their experiment is intrinsically biased towards the knowledge domain understanding of math. The experiment was set at a grocery store, but still carried the structure of laboratory problems: answers were right or wrong, and the type of reasoning was intended to be proportional. Instead of asking “what sort of math occurs in grocery shopping?” they tested whether subjects could perform a certain kind of math.

Out of Trees of Knowledge into Fields for Activity

This chapter frames the complexity in problem solving. Instead of problem solving existing at one small and discrete domain, it is situated within a broader context. “People experience ‘problems’ subjectively in the form of dilemmas and, so motivated, ‘problem-solving’ actively often leads to more or less enduring resolutions than precise solutions.” (p. 124)

An example that Lave focuses on is a study of practitioners of Weight Watchers, who incorporate the goals of Weight Watchers into their daily routines of shopping and food preparation. Thus, these activities are recast with a new set of motivations. I would argue that these practices are totally consistent with model theory. Weight Watchers has a model with one underlying principle: the quantization of food. This causes activities involving food to be understood as systems of quantities. These models and motivations are necessarily in conflict with others.

Outdoors: A Social Anthropology of Cognition in Practice

In the opening to her concluding chapter, Lave overviews some of the elements of her study of practice (p. 171):

1. The context of a study is important, (for example, in the supermarket), but the context surrounding the situation is also important. The supermarket is also contextualized in peoples’ lives, in which the shoppers’ dilemmas are construed.
2. Conventional premises and analytic questions must be understood critically. This book can be seen as a project which makes these assumptions to be objects of study.
3. The study focuses on “whole-person activity” rather than attempting to understand cognitive functions in isolation. This places cognition as dependent on on time and setting, within culture.
4. Accepting that activity is situated, then those activities are placed within some point in history and culture, and must be understood in that context. Thus, the dilemmas of the shopper (and hence the form of math and cognition used) in 1950s America may be different from those found in contemporary Beirut.

Lave’s final conclusion has a good review of her project as a whole: “I have tried to move the investigation of ‘cognition’ outdoors in several senses: out of the laboratory, out of the head, out of a confusion with a rationalistic ‘culture,’ out of conflation with conventional ‘knowledge structures,’ and out of the role of order-producing, primary constraints on activity in the world.” (p. 189-190)

I found myself discussing Michael Mateas‘s paper Semiotic Considerations with Audrey a week or two ago, and it occurred to me to put the paper on my reading lists. It is an important work, and also ties in very nicely to some of my focus on models. Reading his essay in detail, now that I have a much more substantial backing in cognitive science and structuralist theory, I came to realize that we are approaching similar regions of focus, but from coming to them from very different perspectives.

Mateas’s actual paper is breathtakingly short, a mere four pages of 18 very explicitly defined points. This deceptively clear organizational structure conceals the real depth at play in the paper. The paper is roughly divided into three regions of focus, and I will explore these and summarize these sections in context. His paper has the form of a poetics of Expressive AI, rather than an aesthetics, or an approach for criticism of such works.

One of my interests here, although I’m not going to have the chance to get into it, is the relationship between model and simulation, as compared to Mateas’s rhetorical and computational machines.

One: The Experiences of AI and Art

Mateas’s paper is on the practice of creating AI based art, which he calls Expressive AI. In Mateas’s perspective, art is fundamentally semiotic in nature. Art involves negotiating flows of meaning or semiosis, which is very situationally dependent. Some examples of situations are “a busy freeway, an office in a large bureaucratic organization, a party, a riot, or, perhaps, an art gallery,” these all are both recipients to artistic intervention, and they turn around and affect the flow of meaning given by the art itself.

Art in this case is a proactive and assertive force, engaging with the world and reconfiguring it. Art is  intrinsically participatory, as semiosis requires active observers and interpreters. Art is dynamic, as it is subject to influence by the context in which it is situated, and necessarily affected by the flows of its participants. Even the term flow communicates dynamism.

Connected with AI practice, expressive AI is the combination of AI and  injects not only the affordances of participating or simulated computer controlled characters, but also a unique intersection of rhetoric and semiotic functions that are unavailable in other forms of art practice. An AI based artwork becomes itself an active participant in semiosis, and may engage in working with flows of meaning. In this sense, the AI based work shares the situation with the human participants or observers.

Because Expressive AI operates at this unique intersection, Mateas argues that we should think of it in a new light. We must use special rhetorical strategies for understanding the relationship between the computational and artistic dimensions of the artwork. We must share a language to address these different domains, which operate on very different symbolic terms, but Expressive AI is interesting precisely because it exists at this intersection. The issue then becomes how to understand and negotiate these two critical components of AI practice.

Two: The Computational and Rhetorical Machines

Computational artifacts, and AI especially, are subject to a set of semiotic properties that are unique to the computational form. Specifically, computation enables automatic symbolic processing. This is the property of the computer heralded by Turing and popularized by Herbert Simon and Alan Newell. In this tradition, symbol systems exist in a domain of pure or abstract reasoning, much like abstract sign systems in the semiotic tradition. What is interesting about symbols and signs, is that, in principle anyway, they are intrinsically arbitrary and meaningless. One sign or symbol may be used to denote or connote anything.

Rhetorical meaning derives from and requires human interpretation. The human observer is necessary for connecting signs to referents, and for extracting meaning from an arbitrary configuration or conglomeration of symbols. Interpretation is necessary for categorizing a program as intelligent in any form. The role of interpretation imposes a new complexity in the otherwise ideal symbolic world, because human observation involves partial observers and the revelation of functional values which may be intrinsically encoded within the symbolic systems.

The technical operation of the AI system involves a computational machine, which is responsible for the processing of symbols. However, under the lens of human interpretation the AI system becomes part of something else, a rhetorical machine, wherein the system is coupled with the world of meanings and referents. “Every system is doubled, consisting of both a computational and rhetorical machine.”

This doubling affects how AI systems are created and interpreted. A developer of an AI based artifact must be aware of the relationship between the rhetorical and computational machines, as technical decisions will ultimately reflect rhetoric. A creator of Expressive AI must construct not only an artifact which engages as a participant in semiosis and flows of meaning making, the creator must also inscribe artistic intentions into the dual machines in order to affect the possible outcomes of interaction with the system. This lays out new artistic affordances and challenges, the scope and breadth of which is not yet clear.

Three: Systems of Code and Execution

All computational programs work using two systems or planes of meaning. The first plane is the space of the written program. This is what is actually authored, and its content is not the artifact, but rather the set of meanings that will enable or allow the artifact. It signifies the space of all possible executions. The second plane is the actual plane of execution, on which the artifact may actually be engaged and may participate in the semiotic processes described above. Mateas calls the first system, the code system, system1; and the second system, the execution system, system2.

The division between these two planes is deeper than their functional dimensions, but extends to the rhetorical strategies for interpreting, understanding, and manipulating the artifact on those planes. The two systems share signs, and we use similar language for discussing them. They are paired with their own matching rhetorical systems, which are different, but interact closely with each other.

Both of these systems have what Mateas calls “iterpretive surpluses.” The system1 has an interpretive surplus for the author, and the system2 has an interpretive for the audience. The author’s surplus comes with a freedom to embed strategies and approaches into the system, and interpret the composition of the system creatively. This leads to (especially in Mateas’s own projects) new terminology for constructing content in the system1. The audience’s surplus is one that resembles more closely the interpretive surplus afforded by interaction with works of art and other artifacts. The domain of execution can (and must) make use of other established media strategies and traditions for expressivity, that can be used for the audience to better glean meaning from the work.

The arrangement so far presents a portrait of Expressive AI as a practice of negotiating and manipulating many flows of meaning, and many complex and interdependent systems. The issue of rhetoric and language is extremely important, and provides a methodology according to which one may author works of Expressive AI. Mateas does not lay down any specific language that he thinks should be used, but rather, examines the role which he thinks rhetoric and language should play in the development of such artifacts. Furthermore, because the systems are so intrinsically connected, he argues against the approach of AI as a means to an end. To achieve a system with certain rhetorical goals, it must employ a computational machine that mirrors that rhetoric.

Kenneth Burke was an American philosopher and literary critic writing in the mid 20th century. His principles have had influence on a great number of others: Edward Said, Clifford Geertz, Frederic Jameson, and Erving Goffman. The introduction to this book poses his investigation as similar to some standard sociological questions, but his inquiry is much more philosophical in nature.

Burke’s opening also gives a straightforward overview of the principles of dramatism: The explicit topic is understanding everyday action and motive. Burke’s solution is to pose a dramatic approach. This uses five key elements, which he calls the pentad: Act, Scene, Agent, Agency, and Purpose. Act represents the nature of the deed or action took place. Scene is the situation and background wherein the act takes place. The agent is the performer who enacted the act. Agency is the means and manner by which the agent could perform the act. Purpose is the most ambiguous term, reflecting why the agent performed the act in the first place.

Burke explains the challenge in using a particular philosophical idiom. Originally, the grammar of motives was intended to be a theory of comedy, and more precisely a rhetoric, but eventually became clear as a grammar. The idea behind creating the grammar is not to shoehorn all experience into the rigid structure of the grammar, but rather, expose and understand ambiguity.

A perfectionist might seek to evolve terms free of ambiguity and inconsistency (as with the terministic ideals of symbolic logic and logical positivism). But we have a different purpose in view, one that probably retains traces of its “comic” origin. We take it for granted that, insofar as men cannot themselves create the universe, there must remain something essentially enigmatic about the problem of motives, and that this underlying enigma will manifest istself in inevitable ambiguities and inconsistenceis among the terms for motives. Accordingly, what we want is not terms that avoid ambiguity, but terms that clearly reveal the strategic spots at which ambiguities necessarily arise. (p. xvii)

There may be overlap between the categories. For example: war may be seen as agency, act, purpose, scene, or agent, if personified. One feature of this categorization is that issues of the border between agent and instrument are disposed of. Relationships between an actor and an instrument, such as “the chisel is an instrument,” versus “the hand is an instrument,” cause problems in comparison to cognitive extension. Burke’s fomulation here encompasses these under the broad stroke of “agents,” whereas the term agency has a significantly more separate role. This approach reflects the idea of symbolic action as posed by Mead.

The Container and Thing Contained

Grammar implies a structure, and the first element of structure is containment. The scene contains the act, and it contains the agents. The idea here is that the scene encompasses and reflects the act dramatically. This is best evident in drama, but can be found in fiction as well as in real life. We reconstruct and recast scenes to reflect the nature of our actions within them. One of Burke’s goals in this section is to examine the ratios between scene, act, and agent. These ratios are the degrees of emphasis or dependency belonging to the elements in given actions. Burke’s postulate seems to be that acts may be analyzed dramatistically in terms of the ratios involved.

Any verb can be an act if it is willed. Verb and intention defines an act. This has significant ramifications for how we might read acts and intentionality with respect to agents. “As for ‘act,’ any verb, no matter how specific or how general, that has connotations of consciousness or purpose falls under this category.” (p. 14)

The ratios are not means of measurement, but rather a tool of analysis. Burke gives an example of examining nations and “democracy.” Employing different ratios yields different perspectives on the relations between the two. A scene-act ratio would cast nations as scenes or situations and these situations would enable acts that are democratic or otherwise. With an act-agent ratio, the people of nations would perform “democratic acts.” This example is a little convoluted, but presents an inherent ambiguity and ambivalence of the ratios as investigative tools.

Antinomies of Definition

The matter of definition exposes a paradox at the heart of trying to understand something. Definition requires context, but requires a differentiation from that context. “To tell what a thing is, you place it in terms of something else. This idea of locating or placing, is implicit in our very word for definition itself: to define or determine a thing, is to mark its boundaries, hence to use terms that posess, implicitly at least, contextual reference.” (p. 24) Here, Burke is borrowing significantly from Spinoza, who was critical that things could be observed alone in themselves. This idea resurfaces again in Stafford’s theory of likeness.

One central element of Burke’s analysis is the notion of dialectics. There is a necessity of opposition in dialectics. Rivals are at opposite banks of the same stream. This sense of opposition is one in which adversaries share the same scene or model. In these situations, the opposing parties on each side of the dielectic may vehemently disagree regarding their issue at stake, but they do necessarily agree that there is a world consistent save for this issue. An opposing view to the dialectic perspective is one in which differences arise from the use of different models. In these situations, no common ground may even be found for taking up opposition for argument.

Scope and Reduction

There is an interesting opening here, which applies very neatly to the construction of models. Forming a cohesive vocabulary is a similar (if not the same) process as constructing a model. Burke’s goal with dramatism is to form a procedure for developing a terminology (or calculus) of any given domain. The key here is the idea of a representative anecdote. In a model based perspective, a representative anecdote might be compared to some sort of representative or essential element.

Men seek for vocabularies that will be faithful reflections of reality. To this end, they must develop vocabularies that are selections of reality. Any selection of reality must, in certain circumstances, function as a deflection of reality. Insofar as the vocabulary meets the needs of reflection, we can say that it has the necessary scope. In its selectivity, it is a reduction. Its scope and reduction become a deflection when the given terminology, or calculus, is not suited to the subject matter which it is designed to calculate. (p. 59)

There is a focus on the nature and effects of reduction. Divisions, distinctions, measurements, quantifications, comparisons, and metaphors, are all reductions.

Understanding a scene in terms of reductions: The scene must reflect only the reduced domain when a reduction is at hand. Any scene that reflects elements that do not belong to the reduction will fail to make sense when the reduction is in place. The idea that seems to be here is the importance of consistency. The grammar of drama is invariant under reductions (even though it is a reduction itself), and accounts for the transformed nature of content. A motive is a reduction, and can be understood as an analytic tool that is consistent as long as the dramatistic elements are consistent under that motive. For instance: if the motive is power, then acts must be power related acts, scenes must be scenes where power is at play, agents must be making use of power, agency is how power is played, and purpose is necessarily the pursuit of power.

A reduction, model, or term, is a way for interpreting the world, but is also a way to generating new worlds, which are dependent on these interpretations. Burke explains:

In sum: In any term we can posit a world, in the sense that we can treat the world in terms of it, seeing as all emanations, near or far, of its light. Such reduction to a simplicity being technically reduction to a summarizing title or “God term,” when we confront a simplicty we must forthwith as ourselves what complexities are subsumed beneath it. For a simplicity of motive being a perfection or purity of motive, the paradox of the absolute would admonish us that it cannot prevail in the “imperfect world” of everyday experience. It exist not actually, but only “in principle,” “substantially.” (p. 105)

Four Master Tropes

Burke explains the four master tropes: metaphor, metonymy, synechdoche, irony. He reformulates these in terms of other formats: Metaphor is perspective, metonymy is reduction, synechdoche is representation, and irony is dialectic. (p. 503)