Overview:

Tomasello’s problem is to understand how humans developed so rapidly in the evolutionary scheme. He suggests that a small genetic change enabled a process of cultural formation. Early primates can use tools, but they must learn individually. Humans have the power to build on top of existing knowledge. The underlying change that Tomasello argues consists primarily of intentionality, but also the qualities of imitation and identification.

Notes:

A Puzzle and a Hypothesis

Tomasello is looking at the anthropological origin of human cognition. He is concerned with how cognition and complex behavior came so quickly the larger evolutionary scheme. He notes 3 categories of human development: Tools, Language (symbols), and Rituals.

“One reasonable hypothesis, then, is that the amazing suite of cognitive skills and products displayed by modern humans is the result of some sort of species-unique mode or modes of cultural transmission.” (p. 4)

The hypothesis provided is that humans have a species unique method of transmission of skills, rather than a biological one. The key element to this is a process that he calls the ratchet effect. Most animals use biologically inherited skills. Primates develop learned skills, but these are individually learned. Humans have the capacity to build skills over the course of development, where skills gained in one generation continue to the next.

Tomasello is looking at development, similarly to Vygotsky. Learning is dependent on others, and culturally mediated. To Tomasello, the key i all of this is identification. “These special powers come directly from the fact that as one human being is learning ‘through’ another, she identifies with that other person and his intentional and sometimes mental states.”

He argues for the uniqueness of human cognition because of traits at three levels. These traits are genetically based, but culturally implemented.

• Phylogenetically (before birth), humans have the ability to identify with others.
• Historiacally, development of artifacts and knowledge accumulates over time, and is does not start from scratch in each generation.
• Ontogenetically (after birth), children develop in atmosphere of skills and signs, internalizing existing symbols and knowledge.

Biological and Cultural Learning

There is development in some animal species that is based on social interaction. This is called cultural transmission, and develops cultural traditions. This is a broad sense of tradition, though. The human difference in cultural transmission is in identification.

One of the differences between primate and other animal cognition is in the ability to recognize intentions. “Nonhuman primates are themselves intentional and causal beings, they just do not understand the world in intentional and causal terms.” (p. 19)

Later, intentionality is something that is attributable or projected onto other beings or individuals. Nonhuman primates fail in identifying causality: The example given on p. 22 shows a primates having a great deal of trouble with the trapped tube.

If we relate the understanding of intentionality as deriving from identification, we can see the influence of Vygotsky here. The essence of this is that “others intend because I intend.” This takes place throughout development, and varies with the developmental capability of the child. The gist is that when the child can have intentions, it can recognize intentions in others. This idea relates very closely to Lacan’s mirror stage, which occurs at around 6 months, where the infant begins to recognize itself. Initially, the infant is in opposition and at rivalry with its own image, but then comes to identify with it. This notion can be extended to identification with others.

Cases of nonhuman primate learning and culture: Tomasello attempts to debunk and critique the projection of social learning onto nonhuman primates. Characteristics of nonhuman primate learning:

• Individual learning (not social)
• Emulation learning (not imitative)
• Ontogenetic ritualization (which is repeated responsive behaviors, not imitation)
• No active teaching
• Situational adaptation (not cultural development)

Human cultural development is intrinsically cumulative. Artifacts, which may be tools, rituals, or symbols, are developed between individuals, instead of within individuals. Thus, artifacts are gradually modified by each generation. This is the cultural ratchet. Imitation is necessary to pick up the existing base of a skill or artifact, and once that is imitated, then further development may occur. The process of ratcheting enables a history.

Another kind of ratcheting occurs between individuals through social interaction, and this is called sociogenesis. Tomasello looks explicitly at the subjects of language and mathematics.

Regarding language, Tomsaello argues that language is a gradual development: “The crucial point for current purposes is that all of the symbols and constructions of a given language are not invented at once, and once invented they often do not stay the same for very long.” (p. 42)

The idea suggested with this is that sociogenesis enables the construction of more and more complex ideas (citing the complex structure and function of languages). But, within communities, the essence of practice is to make complex ideas into simple ones. This can pull back to Lakoff’s notion of metaphor. To a developing individual, learning is about understanding complexities in embodied or familiar terms.

Regarding mathematics, in early civilization there were a large diversity of numeric representations. Eventually, Arabic numerals spread and became widely adopted. This suggests that the cultural ratchet operates on a very broad scale (across continents, even). The spread and adoption of ideas is also addressed by mimetics, where the idea is imitated and spreads. From the mimetic perspective, ideas that are good at being imitated (and utility positively affects this), will spread more readily. This idea is consistent with Tomasello’s emphasis on imitation, and emphasizes the notion that utility of ideas is not universal.

Tomasello makes a further distinction. Instead of the dichotomy of learned vs. innate, the dichotomy of ontogeny vs. phylogeny is more useful, and we should focus on ontogeny. What does that mean? What is the difference between it and phylogeny and learned behavior? In his description, ontogeny (at least in humans) has a special emphasis on imitation and intentionality. Ontogeny extends beyond learned behavior in that it is more than merely environmental adaptation or response. Ontogeny has to do with how behaviors emerge: “… the goal is not to decide whether some structure is or is not ‘innate,’ but rather to determine the process involved in its development.” (p. 51)

Joint Attention and Cultural Learning

There are 3 elements to early infant cognition: Understanding objects: Infants understand some principles behind how objects work, even before their capacity to manipulate them.

Understanding other persons: The have “built-in” facial recognition, and a capacity to imitate facial expressions. This is potentially a root of identification. Understanding self: They understand the limits of the self in manipulation, and will bail out of unachievable tasks. This is the stuff that appears during early development, and is similar to other primates.

At 9 months, a tremendous cognitive change begins to take place. This is manifested as a collection of behaviors that Tomasello calls joint attention. “But at around nine to twelve months of age a new set of behaviors begins to emerge that are not dyadic, like these early behaviors, but are triadic in the sense that they involve a coordination of their interactions with objects and people, resulting in a referential triangle of child, adult, and the object or event to which they share attention.” (p. 62)

Tomasello gives 3 accounts for the 9 month revolution, each of which is flawed in its own way.

1. No strong cognitive changes take place as ability to interact is innate, and they possess some primary intersubjectivity, but infants lack motor capacity to express these interactions (Trevarthen 1979, 1993). This is countered by failure to reproduce results, and studies that reveal sophisticated motor skills.
2. Infants are preprogrammed with capacity to interact socially, but this does not activate until the appropriate time (Baron-Cohen, 1995). The different social skills are separate and become activated one at a time. The data is inconsistent with this conclusion, though.
3. The behavior around the 9-month phase is learned, and activated according to critical stimuli (Moore, 1996; Barresi and Moore, 1996). Again, observed data does not support this conclusion.

A suitable answer to this problem requires answers to the questions: Why do joint attention skills emerge together? Why does this happen at nine months?

The argument that Tomasello makes is that infants have an intrinsic ability to identify with others, and when the infant develops intentionality, then others may be understood as intentional agents as well. This is a projection of the self onto the other. The key element in this explanation is simulation. Infants may understand the other as like the self, simulating the other’s intentions in order to predict them. “Since other persons are ‘like me,’ any new understanding of my own functioning leads immediately to a new understanding of their functioning; I more or less simulate other persons’ psychological functioning by analogy to my own, which is most directly and intimately known to me.” (p. 71)

This example interrelates to the self centricity and absorbtion of toddlers. They use may their selves as a basis of understanding others, but cannot identify themselves as being beholden to the social conventions that others are subject to. This is somewhat at odds with Tomasello’s model.

The capacity to simulate is something that has been expressed by other cognitive scientists as important elements to cognition, but its development is not usually explained. For instance: Keith Oatley on interpretation of fiction.

The 9 month revolution occurs because at that point, the child becomes intentional (supported by Piaget), and it is able to identify that others are intentional as well.

Simulation is not an explicit conscious process, but rather an innate, embodied one. “My hypothesis is simply that children make the categorical judgment that others are ‘like me’ and so they should work like me as well.” (p. 75-76) Others are understood in an analogical relationship to the self. Intentional simulation is closely related to the construction of causal models, as relates to observations of physical phenomena. The intentional simulation hypothesis is supported by confirmed predictions with autistic children.

Behavior after 9 months has mimicry of intentional behavior, and further incorporation of intention to general engagement. “That is, whereas in early infancy there was some face-to-face dyadic mimicking of behavior, at nine months the infant begins to reproduce the adult’s intentional actions on outside objects.” (p. 81)

An interesting conflict occurs with playful behavior, which is construed as oppositional to intentional behavior. In play, intentional affordances are decoupled from the artifact. This is in conflict with Vygotsky, who suggest that playful artifacts are projections of unachievable desires. It seems that play would be a further example of projection and analogy, rather than decopuling.

Linguistic Communication and Symbolic Representation

Where did language come from? Symbolic representation is important because it is 1) intersubjective, and 2) perspectival. Language emerges from 1) joint attentional scenes, 2) communicative interaction, and 3) role-reversal imitation.

Language learning, and especially learning of the meaning of words comes from an identification of intentions within a joint attentional scene. “To acquire the conventional use of a linguistic symbol, the child must be able to determine the adult’s communicative intentions (the adult’s intentions toward her attention), and then engage in a process of role-reversal imitation in which she uses the new symbol toward the adult in the same way and for the same communicative purpose that the adult used it toward her.” (p. 117)

Joint attention is internalized into symbolic representation. This looks like the beginning of the internalization of social models or cultural identities. Objects are used as symbols, and this idea relates to the sense of pivoting. (p. 126)

Linguistic Constructions and Event Cognition

Children abstract from the concrete. They hear only concrete utterances, but are able to abstract them and understand linguistic structures from these. Tomasello explains that this process is very important for understanding how events are conceptualized. This idea goes back to models. Given concrete phenomena, children will develop models (intentional and causal) of how these phenomena work. There are inherent abstracting principles in model formation. The discussion here focuses on linguistic structures, suggesting that model formation depends on language.

Verbs are understood as embodied (kinematic and kinaesthetic) intentional experiences. Nouns are substitutable. This follows from joint attention: activity is intentional, but objects are targets for attention and may be interchanged. Here this level of structure is expressed in language.

Abstraction and schematization are the processes by which children form structures and categories in language. Concepts are formed and generalized (and overgeneralized) and later focused and refined. This relates back to Lakoff and Johnson. Concepts, models, linguistic constructions are developed, expanded, and used to match observed information. More interestingly, Tomassello hints (but does not address thoroughly) the idea of model divergence and refinement. This connects to conceptual blending, which explores the construction of new concepts from old ones.

Language is a tool for interpretation and conceptualization, that is, for forming and developing models. This supports the linguistic model of thought, and with intentionality, counters propositional models. However, Tomasello did hint earlier that models do occur before language. This suggests that humans have an inherent power for using models, but it is though language that these models can be most readily changed and manipulated.

Discourse and Representational Redescription

“The current hypothesis is that the perspectival nature of linguistic symbols, and the use of linguistic symbols in discourse interactions in which different perspectives are explicitly contrasted and shared, provide the raw material out of which the children of all cultures construct the flexible and multi-perspecitval–perhaps even dialogical–cognitive representations that give human cogniition much of its awesome and unique power.” (p. 163)

The interesting element here is the multi-perspectival nature of using language. This echoes back to the issue of identification. Dialogical cognitive representations seems related to the idea of simulation. Tomasello is saying here that cognition is powerful because of multi-perspectival ability.

The function of discourse: negotiating the form of an utterance from its content. This adopts a symbolic view, but one that is not propositional. Tomasello argues for a model based view of communication. The feedback in discourse enables feedback on model construction. Reconciling differences relates to synthesizing and blending models. (p. 171)

There is a question posed here: Intentional agency versus mental/belief/moral agency. He contrasts between theory-theory and simulation theory. Both are rationalizations for how children understand others as having varying beliefs. Tomasello explains the understanding of varying beliefs as a natural and gradual consequence of development. (p. 174)

Last Tuesday, Janet gave a good spiel on bookwriting. It is intended for us upcoming PhD students, and blends work on dissertations with actually writing a real honest to goodness book. I took pretty detailed notes, and, with her permission, figured I would put them online for safe keeping and for the world to see. Here is what I’ve got:

You should think of your PhD thesis as your first book. In humanities, you usually publish your dissertation, generally as a book, but sometimes through articles. You can think of chapters as papers. But, the worst thing to do is to publish other papers while working on your dissertation, because you should be investing your full time into writing the thesis itself.

When you think about your thesis as a book, the first thing to consider is: what other books are out there that are like the one you are writing? This should be easy because you’ve probably been reading tons of them. This is a good way to find a publisher. Also, when you read the books, make a note of who the author thanks in the preface. The author might thank an agent, but probably will thank an editor.

You should look for an agent or an editor. When you first publish, you will generally do so with an academic press, but when you have tenure, you should publish more generally.

In terms of contracts and proposals, for your first book, the publisher will expect you to have the book written. But, later, the process is a little different. After your first book, you will want to sign a contract to write the book. You will want to send a book proposal and one to three chapters. Explain in the proposal: what is new about what you are doing, who is your audience, and what other books are in this category.  When you articulate an audience, explain what categories of people might be interested in this book, for example: digital media students, people developing digital tabletops, people teaching and studying game design. The proposal should have some example chapters, but also an overview of the table of contents and a couple of sentences to describe each chapter.

It is important to look at what books have been published, and consider the editor who is responsible for those. You do not need to look at sales figures.

The first hurdle for publishing a book is to see the book as a business decision. The decision to accept something is different in the academic press than, for instance, the popular press or Hollywood. You should look at your book in terms of its value and who is likely to buy it. For example, libraries might buy it, school courses might buy it, it may be appropriate for certain conferences. Demographics are different intellectual groups: people who might teach courses or attend conferences. Some books in digital media have an interdisciplinary dimension, so they might be important for both an art schol and MIT.

Conferences are a great place to chat up publishers. Often times, the editor may actually be there personally. If someone from marketing is there, you should ask what is selling and make contacts.

You want to be fresh and new, but also grounded in an intellectual tradition. You want to appeal to the editor, and have the editor fight for you. You should show yourself as someone who can lay out a multi-chapter product. The book is a way for you to show your credentials as both a writer and an academic. Usually you will not make money from your first book. You should not have any expectation that book writing will be lucrative. You are doing this for the advancement of knowledge and to show yourself as a distinguished scholar.

There is a difference between academic and popular styles of writing. When you write more readably, the book will be more popular, but this invites criticism as an academic product. There is a recent trend among academics that has rewarded poor writing, but I think the fashion of obscurity and unreadability is going out of style. Similarly, you don’t want to write ham-handedly in an imitation of French playfulness. You don’t want to write like Marshall McLuhan in sound bytes.

Usually dissertations are written defensively, to show that you have read everything and thought of every possible objection imaginable. It is a credentializing ritual. This style of writing is far too paranoid and defensive for a book.  Publishers will usually reject a book proposal if it is a dissertation. Definitely do not tell the academic press that your book is your dissertation!! Or, if you do, say that it has been thoroughly rewritten!

Think about scope. What is a book sized chunk, versus what is a dissertation sized chunk, versus what is 10 years worth of work. For a book, you need to answer the question: why is this important for the world to know? For a dissertation, the question is more personal: what would I like to obsess about for four or five years? Your dissertation must be a contribution to knowledge that will not go out of date. The book is a work of scholarship, but asks a question meaningful to a wiser circle and it should be relevant beyond the degree.

You should not worry about someone else publishing the same research topic ahead of you. Your topic should not be so narrow or answerable that someone could beat you to it. If someone does publish ahead of you, you can build off their work, and use them as an example of why this field is so important. But it is unlikely that you will be working in the same way with the same approaches or conclusions.

A rough size metric for a book is 100,000 words, although there has been a trend recently to publish shorter and shorter books. Size really does not matter for books. Your book should have an integrity of argumentation. It should have a balance. The first chapter should be foundational (that is, the rest of your argument builds from it). Chapter titles should be precise. A common mistake is to make the chapter titles catchy and appealing, but this makes it seem like your argument is not well though out.

Writing is about design. Especially, work in our field is about clarifying design values. You should justify and contextualize elements of design. Be clear about what your values are. Understand that others will value things in your writing that you do not anticipate, or people from other backgrounds might get different meaning out of your work. Keep in mind your use of values and how you express those values. You are participating in a discourse of value.

Acknowledge the way a term is used in another discourse if you appropriate that term. When you use terms, you should define them. For instance, what do you mean by game or narrative? You should explain what gives you the authority to assign a definition to a term. You should acknowledge the definitions that others have given to the terms you use. A lot of academic terms have been monitized or abused to the point where they become meaningless. For example, emergence means “good,” given the way that it has been used recently. Carefully define terms if they are important for your work.

Steven Johnson is a good example of a writer who is popular, but also suitably academic. His writing is not tenurable, but it is academically sophisticated. Another example is the articles in the New Yorker, which is an educated and sophisticated discourse. For example, their article on John Stuart Mill.

Regarding the process of writing the thing: For a book, you can’t do an all nighter, or an all weeker. You need a sustained process. A writer’s group would help. You can meet to mark progress, or just to unwind. Writing is a lonely activity, so a social goup helps. What is best is to write every day. Research shows that success is more likely if you write every day than in long isolated periods over each month. You should write in short periods over time to sustain continuity. Write no more than four hours at maximum. Keep a journal to keep track of yourself. Self tracking is important.

But the most crucial bit is this: When you stop writing for the day, write down notes for where you are and what you are going to do next. This will help you from getting lost when you start back up again.

The best writing comes from throwing out your most cherished phrases. If you cut something, you can paste it into a new file, and just save everything that has been cut so that it is not lost. This dull the pain from having to throw out your ideas. This way, you might be able to refer back to the things that you cut, but in practice you probably won’t after a couple of days.

Often, when you’re writing, you come up with a great idea that you want to come back to. What you should do is to put in an asterisk which you can search for later. Start a new document, or write separately as another project. When you are writing it is much more important to continue and finish rather than generating new ideas. So, you should keep track of your new ideas, but you do not want to explore those ideas within the book you are already writing. Sometimes it is useful to have multiple projects going at once, so when you are blocked on one, you can move on to another. Sometimes when you write, you will encounter some question that makes it seem like you cannot continue until that question is resolved. When you get blocked, you should put the blocking forces into their own space. Then turn back and continue on what you need to finish.

Well, we did some testing for the InTEL project today. The good news is that it is a lot more easy going than it has been in the past. The bad news is that there are quite a lot of bugs and a handful of aggravating UI glitches. Whenever we change something under the hood, we’re usually able to iron it out so that it works smoothly on the surface, but today a few nasty issues reared their heads. We’re deploying the tested exercises next week, so there isn’t much time to fix everything, but we will try our best.

Java XML persistence remains difficult and puzzling. I am finally beginning to wrap my head around the twisted internal logic that governs it. I still spend much of my time confused, but the situation is improving. We should be able to have things both save and load in a couple of weeks.

In the meanwhile, Janet gave a lecture at the PhD colloquium yesterday on how to write a book. She had some very useful advice. I’m going to write it up and put it online when I get the chance.

Finally, because I have some sort of dementia, I am working on a small independent project to visualize the parameter spaces for strange attractors. It was something that I was wanting to work on a long time ago, but now I know much much more about UI and application development than I ever dreamed was knowable. So, the project is actually not all that much work, at least not at this stage.

Is it odd that when you are used to programming most of the time, you can come to acknowledge the different types and dimensions of programming, and it eventually can become a leisure activity under certain circumstances?

Overview

The authors are interested in looking at identity as a process rather than a product. The study descends from Vygotsky and Bakhtin, both of whom belong to a particular school of Russian Cultural Theory. What is unusual about this perspective, as compared to a great deal of cultural theory, is that it presents a very complex perspective on the development of identity, and frames identity as something that is both culturally affected, but something that individuals have agency over.

Notes

The Woman Who Climbed up the House

Identity is partially a cultural product, and relates to self-interpretation. This idea of acting to become an identity strongly resembles Goffman: The self is elusive, but ultimately is a performance, even internally. Mead (who was a significant influence on Goffman) is referenced, and remains a strong influence on the discussion throughout the book. Identity is something that is proactive, put forward as an active force within an individual’s behavior and actions.

“It is not that we have an inclination to the idea of a unified subject; we conceive persons as composites of many, often contradictory, self-understandings and identities, whose loci are often not confined to the body but ‘spread over the material and social environment,’ and few of which are completely durable.” (p. 8) The study is spread over different cultural worlds, which enable different modes of understanding. These are worlds of meaning and conflicting value systems.

Holland recollects an example that occurred during field work in Nepal. The culture system in Nepal involves a strict caste system, where lower classes cannot transgress onto the upper classes in a number of ways. Specifically, it is culturally offensive for a lower class person to go into the kitchen of a higher class person. The incident occurred when Holland was going to interview a woman belonging to one of the lower classes, who would need to pass through the kitchen of the household (which belonged to an upper class family), in order to reach the balcony where the interview would take place. The woman instead chose to climb up the side of the house to reach the balcony.

Climbing the house can be thought of as a certain kind of conceptual blend. It is an emergent property of cultural conditions and this particular frame of interaction, the interview. There are two perspectives to this situation. The first is the theme of cultural logic, which uses a theme of embodiment, where individuals are compelled via forces operating according to history. A second possibility is subject position theory, which looks at subjects as being forced into explict positions, and this is supported by a constructivist approach (Irvine). Another possibility is that agents are forward planning and perform some sort of explicit planning and optimization strategy, but this lacks much of the subtlety and depth that is put forth by the other theories.

The culturalist theory: Humans are products of culture and cultural forces. Constructivisim: Individual negotiation of subject positions. Resolution: Use both perspectives, but focus on the emergent phenomena themselves. Focus on improvisation and spontaneous behavior because of or in spite of cultural context.

A Practice Theory of Self and Identity

A great deal of challenge to conventional theories of identity (individual/relational, as relates to the interaction of self and culture) comes from Foucault. The above theories of identity require an unproblematic relationship between the individual and culture. Foucault is highly critical of ordinary subjectification, which would enable such a relationship. His criticism is used to expose the complexities of subjectification.

The authors move in the direction of using activity theory. It is used as a way to understanding identity. The perspective here does not look at the self as completely autonomous, or completely socially or culturally driven, but rather: looks at a complex dialogue between the two, and this is activity. Sources: Leontiev (Vygotsky’s student) and Bourdieu. The focus here is on what people do, and that defines identity as a matter of practice.

Figured Worlds

The human understanding of cultural worlds is figured. The idea is that all understanding of the world is imagined. Essentially: meaning only exists within certain domains of understanding. This idea rejects that understanding works at a whole or total level, but instead asserts that meaning can only exist within focused domains or systems: figured worlds. Some of this hinges on Vygotsky’s notion of play, where symbols are substituted for objects. The argument can be that substitution is an every day, adult phenomenon. Figured worlds resemble Goffman’s notion of framing.

Artifacts relate to the construction of figured worlds. They are symbolically endowed, pivots for opening the conceptual space of a world. This relates to Tomasello’s cultural ratcheting. Artifacts enable history. Also, recollect the use of artifacts in The Sims. Artifacts are keys for enabling certain kinds of activities, and certain structures of meaning. They are lenses and keys that let us view the world through the figured world that they unlock. An artifact may be more than a physical object, but can also be certain kinds of words, symbols, or ideas. (p. 61)

Personal Stories in Alcoholics Anonymous

AA is a figured world, associated with the identity of the alcoholic. Along with this identity is a large set of symbolic values and meanings particular to this world. One major artifact in the process of understanding the alcoholic’s identity is the personal story. The figured world of AA is limiting and in conflict with other worlds, specifically to the world before the individual’s introduction to AA. This section focuses on the agency of individuals via personal stories.

The alcoholic identity is defined by drinking. Acceptance of identity requires a reformulation of self-perception in AA’s terms. Instead of one’s neurosis leading to drinking, the drinking is seen to cause the neurosis. The personal story is a structured narrative for perpetuating this figured world, which redefines the world in the terms of alcohol.

How Figured Worlds of Romance Become Desire

This section is on the world of romance among college students. Formulation here is a sort of narrative (or model) defined by this figured world of romance. The active question is how the figured world leads to desire or compulsion to act in its terms. A figured world is more than just a means of interpretation, but it also an active model, which compels and encourages the individual to act in the world’s terms. Romance is seen as a sort of modeled world, where individuals are cast in terms of concepts of “attractiveness,” a sort of value or capital for this world.

The issue with romantic identity: The romantic or relationship-going identity is one that individuals may devote time to. Each identity comes bundled with a world of meanings and internal logics. What is the relationship between identity and role? Varying degrees of commitment to an identity relates to the figured world’s salience.

There is a reference to Dreyfus: The authors compare Dreyfus’s approach to the types of experience and knowledge, and the states of learning and mastery as applies to the figured world of romance. According to Dreyfus, knowledge and mastery is gained from experience and pattern matching, and thus becomes known as higher level symbols. Melford Spiro: Symbols are motivating. The authors use Dreyfus’s account of expert knowledge to be a formation of identity. “The individual comes to experience herself not as following rules or maxims taught by others but as devising her own moves. Dreyfus describes this change as obtaining a sense of responsibility in the system. Perhaps a better phrasing would be that the individual gains a sense of being in the system–understanding herself in terms of the activity.” (p. 118)

Positional Identities

Social position is important within figured worlds. It becomes incorporated into ones own identity within the world, and becomes a disposition.

The Sexual Auction Block

Figured worlds may also be used as tools to leverage power against others. Through invoking pivots, one can shift a situation to one in which they have power over another. In this point of view, values formed by different figured worlds may become forms of capital to exert influence in different figured worlds. The examples provided in this chapter focus around sexual abuses and harassment, but the principle of leveraging power extends beyond gender and sexuality.

Authoring Selves

The self is a variable, not just constructed, but actively formed. From Bakhtin, it is dialogue, from Levi-Strauss, it is a bricoleur. Referencing Mead, the self is built in relation to others.

Forming the self in relation to other worlds, one can imagine the frames defining the other figured worlds as taking on the voices of others. The self can be considered to be authored dialogically between these voices. For example: one can imagine the figured world of the good citizen taking on the voice of a parent or teacher.

Play Worlds, Liberatory Worlds, and Fantasy Resources

Play is a means for the emergence of new figured worlds. Play is also a domain of mastery. This ties together experimentation with sociological roles (think Goffman and Turkle), development of practices (Bakhtin), and internalization of discourse (Foucault). Play originates as a ground for experimentation and adaptation to roles, but can lead to indoctrination and immersion.

“Courtly Love” reflects a socially shared imagined world. Not exactly a fictional setting, but rather a fictional figured world. This is expressed as an ongoing literary tradition. In some conceptions, courtly love might be considered a genre, which as I understand, is a model in of itself, but here it is expressed as a world.

On Thursday, distinguished cognitive scientist Mark Turner visited campus and gave a great lecture on conceptual blending. I was a little familiar with this from Fox Harell’s work, but Turner’s lecture was very revealing on the cognitive roots of conceptual blending.

The gist of it works like this: Human cultural development only really began recently in our evolutionary development. For 800,000 years on earth, biological humans used the same stone tools in the same way without variation. It is only extremely recently, in the past 50,000 years, that our range of potential behaviors began to expand. But: it began to expand dramatically. Turner’s point of interest is that humans began to develop culture and language, but it is bewildering to understand how and why they exist.

So, the real question is how we form new concepts, and create new behaviors. Turner’s solution to this is conceptual blending, specifically double-scope blending, which can combine two conceptual domains (which are in conflict), and produce a new and unique conceptual domain, where new meanings can be made. This idea is great, but it is necessary to pull back to a couple of interesting ideas that are touched on.

One is that a conceptual domain, or a frame, can be much more broad and general. Turner gave examples of memories, structured expressions in language, and also physical engagement. These have the properties of conceptual models. The other thing about models is that the types of models represented here are not abstract and propositional, but they are embodied (generally) and procedural. Thought involves running a model, or simulating it. Mammals have the capacity to simulate models: think of playing fetch with a dog. A dog can catch all manner of objects flying through the air. Some sort of mental calculation is taking place, and it is easily argued that this is an execution of an embodied model. so this modeling is a very basic and intrinsic ability.

A conceptual blend occurs when there are two conflicting conceptual frames or models at work in a situation. Turner noted that there is a capacity for humans to hold two different frames of thought in mind simultaneously. When he did this, I immediately thought back to AI and cognitive architectures focused around planning. Generally, these only define one sort of cognitive frame, and have difficulty when modeling two thoughts at once. Examples of multiple thoughts are thinking of memories and going about everyday tasks. Some work has been done regarding this recently, but I’ll get into that later. The point is that it is a complete departure from the models of commonly used AI.

What is interesting about conflicts in models is that they are not mentally discouraged, they instead trigger thought. This is especially the case in children, who learn concepts and combine them very rapidly during development. In a double-scope blend, the two domains must be in conflict. For instance, a good example that Turner mentioned is Harold and the Purple Crayon. The story combines two domains: drawing with a crayon, and the physical world. The trick is that anything Harold draws becomes real. So, these domains are immediately in conflict, because, we know (and kids know too) that things that are drawn do not become real. That is the blend that occurs in this domain, though. Elements from the domain of drawing, and from the domain the physical world are selectively combined. New meanings and properties emerge that are totally new, for example: Harold wants to get home, and sees the moon in the sky, and remembers that he can see the moon from his window. When he draws a window around the moon, suddenly he is home. This logic is magical, but it is absolutely consistent with the model formed by the blend.

The topic of conceptual blending is of limited use in the simulation work that I am trying to do, but it is very useful from the perspective of understand how real people might make sense of models represented within a simulation game, and apply those to the external world. It also does something to explain the value of adaptations in general. You can think of a fictional artifact as defined by a model, which is a blend of two things: the model of the medium, and the underlying model that defines the work. An adaptation should take that underlying model, and combine it with a new model that is the new medium. An individual’s interpretation of a work is going to form a new blend, though, which will be between the individual’s experience, and the perceived work. When we account for the idea of individual and cultural interpretations, we can have a new model, which is a blend of the interpretations of a community. This idea is running away with the idea of conceptual frames that Turner originally defined, which are all internal, much smaller and more precise, but it is a reasonable direction for thought.

It would be good to think more about formal and computational models for conceptual blending. I kept wanting to ask Mark Turner about computational models when he was taking questions, and then realized that is exactly what Fox Harrell‘s dissertation is all about. That would be good reading material. Relating blending to AI, is a major topic in Jichen Zhu‘s dissertation as well.

Every so often, I get the urge to do raytracing. Generally when this happens I’ll go to povray.org, or to Giles Tran’s Oyonale, and feel either inspired or inadequate, as the case may be. I found a link today to a film called Dimensions, which a beautifully rendered film about math released under the Creative Commons license.

What is remarkable about this is that it is a free, two-hour length, documentary style film about how math is beautiful, put together by three people, being distributed over the internet. What’s more, it’s uses POV-Ray, my favorite raytracer. The resulting video is impeccably crisp, and the animations are elegant and smooth. It is narrated quite well by someone with a pleasant Dutch accent, told over pleasing cello music.

It’s not perfect of course, but still, it’s pretty amazing.

Overview:

Johnson-Laird gives an overview an account of mental models that originally is derived from Kenneth Craik. Craik’s use of models was originally directed towards an account of explanation. The review Johnson-Laird gives is to find a mechanism for formalizing meaning in language that explains cognition. The formulation is strongly tied in the notion of computation, and models are represented as computationally formalizable. This puts Johnson-Laird at odds with proponents of embodiment, but his theory nonetheless gives a formal strategy for forming and understanding mental models.

Notes:

The prologue introduces a set of questions which is good for characterizing the investigation. Here are a couple of them (p. ix):

• Why is it that we cannot think everything at once but are forced to have one thought after another? Our memories exist together, yet we cannot call them to mind all at once, but only one at a time.
• Why are there silences when we think aloud? Aren’t we thinking at those moments, or are we unable to put our thoughts into words? It seems unlikely that thoughts should be grossly intermittent, so what barrier prevents them from being articulated?
• What happens when we understand a sentence? We are aware of understanding it, and are more aware of having failed to do so. Why can’t we follow the mental processes of comprehension as we can follow the action of tying a shoelace?

The concept of mental models derives from Craik. Johnson-Laird notes Weizenbaum’s ELIZA, but claims that it is not a simulation, but rather a dissimulation. It does not have a process of thought, but conjures thought instead. This distinction raises the contrasting idea that ELIZA matches and responds to the interactor’s model, rather than having a model of its own.

The Nature of Explanation

Most theories of cognition consist of description, and lack are not formal (in the sense of algorithmic). Johnson-Laird asks what the criteria is for a definition of cognition. This criteria, he explains, should describe theory in the form of an effective procedure. Theory must be in the form of an algorithm. This should not be a limitation in what exists in the world, but rather, what constitutes a theory that describes the world.

Later in the chapter, there is an extensive discussion of Turing machines, and explaining their universality. He is very impressed by and fascinated with the capacity for Turing machines to do any computation, and furthermore represent each other. If theories are algorithms, then they must be computable. That assertion is the claim of functionalism, to which Johnson-Laird ascribes.

The Doctrine of Mental Logic

Models are intended to replace the doctrine of mental logic, which is the propositional model of cognition. Propositional logic is a fallacious as a model for cognition because of the many logical mistakes that people make on a daily baisis. If our brains worked according to mental propositional logic, then we would be able to more readily correctly answer certain logical problems, which is clearly not the case. Johnson-Laird is not attempting to argue against logic, but rather, that there are multiple kinds of logic.

The logical problem demonstrated is case where the subjects are shown a set of cards with the symbols: [E, K, 4, 7], and told that every card has a number on one side, and a letter on the other. The subject given the generalization, “If a card has a vowel on one side then it has an even number on the other side.” The subject is then asked what cards to turn over to find out whether the generalization is true or false. (p. 30)

These simple logic problems are strongly affected by context. Context affects inference. Changing context in logical problems leads to variable results in whether people can solve the problem correctly. Certain formulations of equivalent problems are frequently solved correctly, while other formulations are frequently solved incorrectly. Familiarity generally helps performance. This argument surfaces when making the connection to embodiment and associative reasoning.

The conclusion of this section presents 6 bullet points (p. 39):

1. People make fallacious inferences.
2. Which logic is found in the mind?
3. How is logic formulated in the mind?
4. How does logic arise in the mind? (development)
5. Deduction depends on the content of the premises. When an individual is familiar with (or has a model of) a situation, they are more likely to reason about it correctly.
6. “People follow extra-logical heuristics in making inferences. They appear to be guided by the principle of maintaining the semantic content of the premises but expressing it with greater linguistic economy.” That is, when presented with propositions p and not-p or q, they are likely to conclude q, instead of p and q.

Theories of the Syllogism

Propositional logic is psychologically flawed. A more accurate logic occurs in syllogisms. Syllogisms are first order declarations: All X are Y, or some X are Y, no X are Y, etc. Johson-Laird puts forth several goals for a theory of reasoning (p. 65-66), and will later deduce that syllogisms satisfy these goals.

1. “A descriptively adequate theory must account for the evaluation of conclusions, the relative difficulty of different inferences, and the systematic errors and biases that occur in drawing spontaneous conclusions.”
2. “The theory should explain the differences in inferential ability from one individual to another.”
3. “The theory should be extensible in a natural way to related varieties of inference rather than apply solely to a narrow class of deductions.”
4. “The theory should explain how children acquire the ability to make valid inferences.”
5. “The theory must allow that people are capable of making valid inferences, that is, they are potentially rational.”
6. “The theory should shed some light on why formal logic was invented and how it was developed.”
7. “The theory should ideally have practical applications to the teaching of reasoning skills.”

How to Reason Syllogistically

In giving a description for how people might reason using syllogisms, Johnson-Laird gives an example of how syllogisms might be visualized by an individual. The syllogism is of the form, “All the artists are beekeepers, and all the beekeepers are chemists.” A way to visualise syllogisms without using a Euler circle or Venn diagram is to imagine a tableau of actors who play the parts of artists, beekeepers, and chemists. Thus, there would be artist-beekeeper-chemists, beekeeper-chemists, and a lone chemist. (p. 94) The metaphor of the tableau is useful for representing mental representations of the situation, but more telling is the use of the troupe of actors who enact these roles. This representation covertly emphasizes the cultural and embodied manner by which the syllogism is understood.

Going a step further, though. Johnson-Laird produces an algorithm for how to reason syllogistically. However, syllogistic logic is still not a complete representation of the logic that humans follow when reasoning, because we still make reasoning mistakes in complex syllogistic problems, for example: “Some B are A, no C are B” yields incorrect conclusions in almost all cases. (p. 74)

Inference and Mental Models

The key to this chapter is how to reason without rules of inference. Both propositional and syllogistic logic define rules for drawing inferences, but they do not line up to natural everyday reason. Mental models are introduced with relational expressions. These may all take the form of predicates or relational expressions. Relations are a bit heavier than ordinary propositions, but still work on the same level. At this point, all mental models are of the form of tableaus.

With the focus on tableaus, mental models can be understood as devices for association, and defining relationships. Both of these can be addressed by non-symbolic and embodied means (Lakoff and Johnson), so even though Johsnon-Laird’s formulation is intended to be computational in nature, it can be more than that.

There are some final bullet points regarding mental models:

1. The theory embraces both implicit and explicit inferences. This means that they should be able to represent all arguments.
2. Children can learn to reason before understanding rules of inference, because reason is possible without logic.
3. The theory is compatible with the fact that people can use logic.
4. It is also compatible with the historical origin of logic.

Images, Propositions, and Models

There is a conflict over how images fit into cognition and psychology. The two sides are the ‘imagists’ (Paivio, Shepard, and Kosslyn) and ‘propositionalists’ (Baylor, Pylyshyn, Palmer). Johnson-Laird argues for the encoding of images in the mind, and goes for a functional account of mental processing. This does liken the mind to a computer: it can procedurally transform images into systems of symbols.

Johnson-Laird describes the relationship between mental models and propositions. “The crucial problem for the mental language is the nature of its semantics. Propositions can refer to the world. Human beings, of course, do not apprehend the world directly; they posess an internal representation of it, because perception is the construction of a model of the world.” Thus, the mental model operates between the individual’s logic and the world itself. Any propositions in that individual’s mind must act on the model, rather than on the world directly. Models work via analogy, and images are views of models.

Meaning in Model-Theoretic Semantics

This section describes how meaning is constructed and composed (in the sense of built compositionally) in model theory. Johnson-Laird references Tarski here, in terms of understanding truth values. A big bit of this is still in terms of truth vs falsehoods. The discussion raises the issue of worlds, and how models connote not only existing meaning, but a set of potential configurations that are enabled by that model. The world of meaning enabled by a model is called its extension.

There is some discussion of Montague grammar, which is an attempted formalization of natural language. This segues into a model-based formulation of meaning, which derives neatly from mathematical logic. The following passage is dearly familiar to the theory of models in logic. “The power of model-theoretic semantics resides in its explicit and rigorous approach to the composition of meanings. It provides a theory of semantic properties and relations, e.g., a set of premises entails a conclusion if and only if the conclusion is true in every model in which the premises is true.” (p. 180)

What Is Meaning?

The discussion of meaning traverses from psychology to word meanings. THere is a great deal of philosophy and squabbling over where meanings come from, or what concepts like “water” or “jade” are, intrinsically. This entire discussion neglects the use of practice, where words and other signs may hold different meanings to different observers, under different circumstances. The importance of language meaning is critical in this treatment of mental models, because the models are based on language.

The conflict in this is between meaning Psychologism and Realism, which respectively attest that meaning is in the mind or outside of the mind. Johnson-Laird is attempting to find a middle ground in this, and looks to an encoding of meaning that allows for intersections and vagueness. However, fuzzy logic exposes the same problem. Propositions, even with values of confidence, are divorced from a knower. For language to work, the knower must have a context and a state of mind. The relative values of “tallness” (given in his example on p. 200) are only meaningful in context.

To address the question of meaning, the psychological perspective asserts that meaning is wholly in the mind, whereas the realistic perspective asserts that meaning is wholly outside of it. Johnson-Laird seems to claim that meaning works within a model, which is grounded in language, which has elements that are both inside and outside the mind. There is an added dimension of culture, though which is extremely relevant. Meanings (and models) are shared between individuals in a culture, so meaning exists beyond the individual, but also beyond the literalism of language. I would argue that it is instead a consensus. This position is not incompatible with models, but requires a reppropriation of Johnson-Laird’s use of models.

The Psychology of Meaning

Models are procedural structures that may be adjusted over time or through discourse according to some rules. There is a set of bullet points describing these:

1. “The processes by which fictitious discourse is understood are not essentially different from those that occur with true assertions.” Thus we use the same logic for processing information into models, even if we know the information is fictional or false.
2. “In understanding a discourse, you construct a single model of it.”
3. “The interpretation of discourse depends on both the model and the processes that construct, extend, and evaluate it.” The model for discourse can vary over time.
4. “The functions that construct, extend, evaluate, and revise mental models, unlike the interpretation functions of model-theoretic semantics, cannot be treated in an abstract way.” There must be some formal algorithms for changing mental models.
5. “A discourse is true if it has at least one mental model that satisfies its truth conditions that can be embedded in a model corresponding to the world.”

~~Intermezzo~~

The next couple of chapters deal with the understanding of grammar and the parsing of language into propositional expressions. There is a great deal of noun-phrase, verb-phrase stuff. The analysis of grammar is heavily extended from Chomsky.

The Coherence of Discourse

Johnson-Laird gives a surprising interjection regarding story grammars. This makes some sense given the focus in the preceeding chapters on the relationship between language grammar and models. The challenge to story grammars can be seen as a critique of a particular kind of structuralism. Earlier pages compare blocks of text that form coherent paragraphs versus those that do not. Coherency relates to consistency and discourse history, which is a type of context. Models have the formal power to use this context in a way that grammar lacks.

The Nature of Mental Models

Some properties of mental models:

1. Computability. Mental models are computable, and so are the tools for manipulating them.
2. Finitism. A mental model must be finite, and cannot directly represent an infinite domain.
3. Constructivism. A model is constructed from symbolic tokens and structurally composed.

A typology/heirarchy of models:

1. Relational. This is a finite set of tokens representing entities, a finite set of properties, and a finite set of relations connecting entities to properties.
2. Spatial. This is a relational model where the relations are spatial.
3. Temporal. A temporal model consists of frames of spatial models, that occur in a temporal order.
4. Kinematic. This is a temporal model that is psychologically continuous, there are no temporal discontinuities.
5. Dynamic. A kinematic model which relates causal relations between frames.
6. Image. The image is a viewer-centric representation of a spatial or kinematic model.

It seems to me that this formulation reverts to computational models, and begins to become severely detached from underlying psychology.

Consciousness and Computation

The final chapter works to give a formal and procedural account for consciousness. Essentially, consciousness is already computational, when understood as processing of mental models. An excuse is given here, that while cognition may be computational, other human traits, such as spirituality, morality, and imagination cannot be modeled and will “remain forever inexplicable.” This is a cop out. Johnson-Laird cannot introduce a hulking device for representing psychology and then blow off its application to other psychological traits.

There are significant critiques to be had with the computational formulation of mental models. I would argue that the computational imposition is severely flawed, but models remain invaluable as a tool for understanding cognition. The use of modeling is especially important in the representations of spirituality (cultural beliefs), morality, and imagination.

So, one thing that has emerged in recent thought experiments about simulation of characters, is that the plan based model of behavior is really problematic. A lot of times, most of the time, characters do not have plans. I would argue that furthermore, people don’t have plans, and that a plan is something that is generally interpreted from everyday behavior, rather than something at the root of it. AI is big on planning. Most AI research on simulated characters focuses strongly on character plans. What is even more ridiculous about this is that character plans are always rational.

I want to look at an alternative model to planning, which is situation. Then, I want to look at something embedded deeper in plans, which is the notion of goals. I would take the critique of planning even further and extend that to the notion of goals. I believe that much of character (and human in general) behavior is goal oriented, a lot of behavior is without goals, and simply reactive. Emotional response tends to be without goals, as does casual conversation. The notion of goal also fails to account for the element of motivation. A condition might be a character’s goal, but it belies the driving motivation behind that goal. To account for this, I will introduce a subtle variant, which is purpose.

Plans are fallacious as a general model of behavior, because they impose a heirarchical structure on thought, and fail to account for human versatility. Furthermore, plans also have tremendous difficulty modeling very straightforward situations, especially as relates to communication and interaction. Plans to not account for a great deal of contextual or situated behavior, the importance of which has been stressed in recent work in cognitive science.

An alternative to planning incorporates elements of plans into an agent’s state. The matter no longer becomes one of top-down organization, but of bottom-up emergent behavior. Characters and people are not entirely reactive, but our behaviors and modes of action are largely context dependent. This is especially the case in terms of social interaction. There is a particular code of conduct that an agent should abide by while in a meeting, as opposed to at dinner, or walking down the street. The situated nature of behavior removes the demand for planning to use a single root goal that informs all other behaviors. Instead, in my situated model, the task specified by a plan becomes part of the agent’s state. Metaphorically, the difference is instead of action happening at the character’s mind, it originates in the character’s identity. A character who is a student has a goal, “graduate,” but this is a long term goal, and is not considered at every decision, but is something that is a part of the character’s being. Similarly, “going to the grocery store,” is a similar state, which informs later actions, but does not prevent the character from stopping for coffee, or having a conversation.

Planning has a deeper anchor in the notion of goals. The first mistake is to assume that goals are the driving force behind all behavior. This is an outright falsehood. Many times, people, and characters in particular, will act at a purely automatic or emotional level, responsively. Goals implicitly endorse the rationality of human behavior, because without rationality, goals could never be met, and without goals, rationality would be meaningless. No character is ever fully rational, though. People might act against their own goals, not even knowing that this action is harmful. What motivates the action, then? Good examples of this are situations when a character is in an explicitly “irrational” state, such as intoxication or being “overwhelmed” with emotion. However, it is hard to imagine that anyone is ever truly rational at any other time. Potential responses to this from the AI perspective are to devise different standards of rationality.

Changing the standard of rationality is a step in the right direction, but it does not account some other situations, particularly, the relative ease at which people respond to emotions or have conversations. I doubt what is taking place in these situations is rapid revision of goals and intentions, but rather some behaviors and states are induced naturally by circumstance, without the character ever needing to formulate a goal explicitly.

While two characters may have the same goal at a given moment, they may not have the same purpose, and the difference in purpose will tell a great deal about how the character’s actions may be executed. Consider, for instance, the airplane safety checklist executed by a pilot before takeoff. The immediate goal of the pilot’s actions is certainly to correctly do the check and respond appropriately. However, the deeper implications of that goal are less clear. Who is the pilot performing the check for? Is it because of genuine concern about safety? Is it to correctly satisfy the safety check ritual for the purpose of regulations? A lot of different theories could explain the form of the pilot’s actions: ritual, performance, practice, directed action, etc. However, the immediate goal is the same, but the purpose, the contextual goal, may be different. Purpose transcends goal, involves meaning, and dismantles the discrete, abstract nature that comes with goals. Purpose is intrinsically situated and linked to identity rather than symbolic mind alone.

This is a collection of essays in honor of Philip Johnson-Laird, one of the founding figures in mental models. These essays represent application of his theory to several particular domains.

George Miller: Contextuality

This essay is about handling words and stituations with multiple meanings. The process of figuring out these meanings is contextualization, described as a basic cognitive process. This is closely related to Goffman’s frame analysis. The goal of contextualization is to resolve ambiguity that is heavily present in interpretation of everyday language and knowledge.

Computational linguistics is a tricky area in cognitive science and computation. It is deeply affected by the issue of context. Miller’s analysis focuses on linguistics exclusively (mirroring Johnson-Laird), as opposed to other sorts of ambiguous circumstances. Computational linguistics involves processing language and attempting to identify and process the correct word meanings from that language. Miller mentions Bar-Hillel (1960), who finds that this sort of language processing can identify correct meanings about 80% of the time. He estimates that this last bit could never be achieved without significant advances in AI.

Expert systems, which are the general approach for working with specialized knowledge, limit the domain of word meanings to a significant degree, but this still does not absolve the “Curse of Bar-Hillel.” Miller theorizes that context identification is the key to unlocking this last bit of meaning.

An aside to note is that Miller is a collaborator on WordNet.

Alan Garnham: The Other Side of Mental Models: Theories of Language Comprehension

This essay looks at language comprehension by examining issues of reference and inference. One key element to inference and communication is instantiation. Where an abstract idea is replaced by a more concrete (or other known) one. However, Garnham is concerned with the communication of abstracts, and notes that we communicate information about abstracts without instantiation.

Propositional relations are a strategy used frequently in AI for world modeling, and relate to information as discrete facts. Garnham gives an example which uses locational prepositions, things of the form: “The lamp is in front of the candle,” etcetera. In terms of these locational structure here, it seems dubious. There is a suggestion that mental models use a more analog depiction and representation of spatial relations.

It is true that we do use abstracts in communication, but models of communication that have emerged from Vygotsky indicate that communication emerges in development when social interaction transforms from something embodied and physical to something symbolic. If we follow Lakoff and Johson, then relations are all metaphorical and based ultimately in the body.

Paolo Legrenzi and Vittorio Girotto: Mental Models in Reasoning and Decision-making Processes

This essay discusses decision making according to psychological studies, and explained in terms of mental models. The interesting thing here is that totally rational decision making is not present, rather, decision making is based on the matter of focusing. This sounds a lot like priming and activation (related to neural networks). Models illustrate the construction of ideas, but neglect to factor how the focusing works intrinsically.

David Green: Models, Arguments, and Decisions

Green builds a theory of decisions (as derived from Craik, 1943) based on argument. Argument is done through warrants, which are bits of relevant information.This work is built from Toulmin’s scheme. Further, the goal here is to analyze argument through mental models. The interplay between observation and model mirrors warrant and argument. Warrants also relate to beliefs, which may be connectable to the belief, desire, and intention scheme in AI. We can also apply warrants to causal models.

The final conclusion in this section is that there is an interplay between argument and simulation, as well as decisions and commitment.

Keith Oatley: Emotions, Rationality, and Informal Reasoning.

Oatley’s focus here is on informal reasoning as it relates to emotions. Informal is opposed to logical or day-to-day. Oatley argues that emotion is critical to this sort of everyday conventional reasoning.

He opens with an analysis of Aristotle’s rhetoric, which discusses two types of reason. There is absolute mathematical reasoning, and also persuaded reasoning, where there is no demonstrable truth. Persuasion instead aims to achieve the best truth possible. The interesting example with this is that Aristotle’s writing is based on the sort of rhetoric used in his day, where law is extremely dependent on performance and dramatic emotional appeal.

Oatley makes some notes on Aristotle’s Rhetoric: The first is that persuasion applies to the imperfectly knowable, and the field of the imperfectly knowable is huge. AI, on the other hand, seeks to only understand that which is perfectly knowable, or that which can be logically concluded or deduced. The second point is that Aristotle explains emotion as a tool of judgement, as opposed to something that is bestial or irrational. Furthermore, there are three impediments to making rational decisions:

1. Limited knowledge and resources. Our mental models are incomplete to fully predict the effects of our actions.
2. Multiple goals. Multiple goals cannot always all be satisfied rationally.
3. Distributed agency. Actions are performed in relation to others, planning must occur among multiple agents, where the problem of limited knowledge becomes especially difficult.

Rationality depends on environment and context. Emotion is used as a form of feedback for goals. Oatley describes emotion as a heuristic function for potential actions.

Oatley makes a connection to Vygotsky and Hutchins. Emotions play a role in the distribution and extension of cognition. There is a connection between Aristotle and the Roman historian Quintillian, who documents the practice of law in the Roman court. This is an argument for the theatricality of reason, relating to the ideas of performance. The performance of law is an enactment and exaggeration of events. The social nature of the audience is essential.

Oatley follows this with the analysis of two experiments, where individuals change behavior based on emotional priming. Emotional induction proved to be immensely relevant in both examples. One of which consisted of examining decision making in judgement of evidence of a trial (after having viewed a happy or a sad film clip), and the other examined forward or reverse reasoning (after reading an angry or sad short story). The experimental corrolation was immensely strong in both examples.

Ciuliano Geminiani, Antonella Carassa, Bruno Bara: Causality by Contact

This essay is about the role of causality in reasoning. Causality is related to the construction of scientific models, but also is relevant from the perspective of narrative. Using causality implies the use of simulation mentally. Causality has an evolutionary basis that is associative (for instance, a rat who smells a type of food on a dead rat will not eat that type of food). This associative logic is also imaginably present in humans, but humans also do use causal reasoning, which comes with the demand for knowing why something occurs. This connects well to Vygotsky and development. The why relates to the narrative/linguistic model of thought.

An interesting note: In developmental study, causality is dependent on contact. Touching is necessary for causality to be interpreted by infants. Gradually, though, causality becomes analogically based. Causal models are a subset of dynamic models. The authors give a funny example of two narrative segments: “Cleopatra was bitten by an asp, Cleopatra died” versus “Cleopatra was bitten by an asp, a tourniquet was applied to her arm, Cleopatra was saved.” This example is a little strange, but is used to understand how people might model what happens to the poison. Mental imagery and metaphors are especially important: poison is a particle, poison is like paint, etc. The important thing to note here is that the example is fundamentally a narrative one.

To understand how models are formed and used, the authors give a three part theory for development of causal models: Construction, comparison, falsification. The construction phase involves taking the components (as a pre-model) and understanding them quantitatively. This is literally formulated as collecting symbols and describing them qualitatively. Next, qualities are quantified, fixing values and times. Finally, the model is simulated dynamically at a sub-cognitive level. The sub-cognitive simulation involves 1) activation of implicit knowledge, 2) generation of instantaneous changes in quantities according to the simulation, and 3) simulation of the temporal evolution of the model.

At the comparison phase, the effects of the mental model with the base model are compared. In this context, the base model is imaginably the observed phenomenon, which is the original story. This comparison intiates revisitations and inferences. Finally, in the falsification phase, plausibility and counterexamples are considered. This sort of analysis derives from Qualitative Process Theory (Forbus 1984), which seems like a good place to check the connection between narrative and models.

This approach is useful in looking at models of fiction as pertains to adaptation, especially in terms of emotional value and responses.

This was written as a problem formulation for one of my courses with Nancy Nersessian. I thought it was handy and relevant, so decided to put it up.

To open, let us consider an argument made by Keith Oatley (in “The Science of Fiction,” New Scientist, 2008): “Fiction is a simulation that runs on the software of our minds.” Oatley’s argument is based on studies of readers of fiction who demonstrate better emotional interpretation skills after reading fiction. The interpretation that he gives is that readers mentally predict the emotions of the fictional characters, and can compare the prediction with the result that actually plays out. This can be seen as either modeling and conceptual change, or a sort of psychological activation of emotional parts of the brain. It is hard to tell for certain, but let this contextualize what follows:

My personal research is in the adaptation of fiction though simulation of the fictional characters and worlds. When the characters themselves are embedded in an electronic simulation, the problem immediately rises of how to develop emotional responses of the characters. Previous work in simulating characters (Perlin, Crawford, and many others) have given varying approaches to modeling characters and communicating states. Game studies (from which my work is emerging) has borrowed significantly from the theories of cinema and theatre for how to represent appealing and believable characters. Much of what has emerged from this is centered on the issue of providing more visible, clearer characters. A great deal of attention is paid to faces (and the movement from text, to image, to animation), which are, admittedly important. Everything boils down to dramatic presentation, which comes from drama, which may be embodied and visceral, but is not an interactive medium.

A simulated fictional world, in which the player is a participant, must look beyond interaction, though. The player must be able to communicate with other agents, for the fictional experience to be enacted. Many times in games, players are in opposition to the game world and its designers, a situation that does not satisfy the potential for emotional relevance. Despite the significant advances in character depiction in many contemporary games, this issue remains a problem. Bonnie Nardi does not give a solution, but provides a way to understand the failure of graphical technology in developing emotional experiences.

In Bonnie Nardi’s ethnography, she studies the methods of communications of business employees, investigating specifically how they use mediated communication. She finds that there are three dimensions to communication: affinity, commitment, and attention. These are explained to make sense within the business model, but are all grounded in sociology and anthropology. Expressions of each of these elements can be seen in every form of communication, and they seem almost tribal. Clearly, there is some deep importance to these channels. Individuals make use of the affordances of mediated communication to work with these elements, but the elements are still deeply embodied. The reliance on information bandwidth is insufficient to operate on these channels.

With Nardi’s Beyond Bandwidth in mind, developments in technology in games are clearly matters of attempting to increase bandwidth. For an interactive experience with fictional characters to succeed, communication must be necessary, and this depends on the relationship of the player to other characters. This does explain why emotional experiences in games work independently of technology. Nardi’s dimensions are a starting point, and open a suite of complex issues: Mediated communication has affordances for the elements of communication, but what are those affordances in games and simulation? How can affinity, commitment, and attention be represented in an artificial world?