This bridges the worlds of narratology and cognitive science (especially mental models) with crystal clarity. Narrative defines a world, and readers understand a story by understanding the underlying model. “This amounts to claiming, rather unspectacularly, that people try to understand a narrative by figuring out what particular interpretation of characters, circumstances, actions, and events informs the design of the story.” (p. 1) This is foundational! Herman’s investigation ties narratology to linguistics and cognitive science, but to him, it is cognitive science that underpins the study.

Existing narrative theory goes from structuralist movements (Todorov, Genette, Barthes, Prince) to more recent narratologists, who focus on generation and emergence (Ryan, Fludernik, Jahn). Here, the target of narrative analysis is the storyworld, which is similar to the concept of the discourse model in linguistics. The focus of these is to explore beyond what is stated in the text, but to extrapolate the knowledge that is implicit or inferred in the discourse or story.

The first part of the book discusses narrative microdesigns, while the latter half is on macrodesigns. Microdesigns are the features defining states, events, and characters, whereas the macrodesigns plot the mood or feel of the model in a broader sense. The features of macrodesigns are issues such as spatiality or temporality, especially with respect to how these map out onto how the story is read and understood.

Herman invokes the critique of story grammars from Wilensky and Johnson-Laird. However, the critique of story grammars requires more care than it is usually given. The real challenge comes from the complexity of language, which is rife with ambiguity and textual cues. “Thus the real task for narrative analysts–a task only begun in the present study–is to chart constraints on the variable patterning of textual cues with the mental representations that make up storyworlds.” (p. 12) A story cannot be fully specified by a structural grammar, because of the importance of cues. Understanding (and adaptation) come from deciphering those cues and using them to reconstruct the storyworld.

The storyworld captures the ecology of narrative interpretation. It is important to capture the environment of a story, not just the events themselves. This shift is further justified by research in narrative understanding.

Herman notes the role of adaptation within story worlds: “Jean Rhys’s Wide Sargasso Sea (1993), for example, does not falsify Charlotte Bronte’s Jane Eyre (1960) but rather supplements it; in this process, Lubomir Dolezel (1998: 199-226) has called ‘literary transduction,’ one fictional world extends the scope of another by sketching a ‘successor world’ that may precede the ‘protoworld’ in time, feature a different constellation of participants, and fill in otherwise irrecoverable gaps in the protoworld.” (p. 16) This treatment explores a storyworld as something open and shared, that may be extended and interpreted. The idea that a world may be extended highlights the plasticity of storyworlds. Other philosophers (Deleuze for example) might claim that disparate storyworlds may be woven together and connected to form broader conceptions of meaning.

Discourse models depend on Emmott’s contextual frames. These operate like Goffman’s frames for interaction. A guiding theme here is whether a storyworld is special in relation to other kinds of models.

States, Events, and Actions

Herman’s focus of story here is on states, events, and actions. Namely, the aspect of storyness that depends on statefulness and transitions. There is a reference here to Mark Turner, on the narrative basis for understanding the world. Turner argues for a kind of conceptual blending (called a “parabolic projection”) wherein one story is projected onto another to help make it more tractable. The theme guiding this chapter is understanding the relationship between the way that states change in stories, and how these are interpreted. One rule used in interpretation is “understand events as actions,” but this proves to be problematic as it does not address the complexity and gray area between events and actions.

The study here is primarily on microdesign, that is, the extra information that word choice and construction play in the meaning of sentences. But, Herman extends the conclusions more broadly. There are a number of things that exist between states and actions, for instance, activities and achievements. Sentences may be constructed to favor one over another, but over the course of a story, this forms a chain of choices, which informs the reading of the story on the whole. Genres have different preferential typologies for how events are presented.

• Epic : Accomplishments > achievements > activities > states
• News reports : Achievements > accomplishments > activities > states
• Psychological novels : States > activities > accomplishments > achievements
• Ghost stories : Activities > states > accomplishments > achievements

This analysis is important because it exposes the way that certain types of genres are fundamentally different. It bears a comparison to the construction of different types of games: a sim game has a different event typology than an action game, for example. It is also remarkable because it skewers Aristotle’s poetics. The hierarchy used by one genre is that genre’s own, and this must be cast as a difference in genre, rather than an issue of superiority or inferiority.

Herman gives an analysis of Kafka’s The Metamorphosis. There is a relation of narrative traditions, but also important is how certain genre encoding strategies construct and define the tacit logic of the storyworld. The analysis of The Metamorphosis illustrates how it uses genre conventions (of realist fiction) to communicate its message. This logic or model depends on its representation. As an extrapolation: A News report reading of the Odyssey would not have the same model. In order for an adaptation to work, it must be able to preserve the entire model, that includes the model from the genre.

Action Representations

This section is on further distinguishing the gray area between events and actions. Actions are generally attributed as depending on intention and agency. However, the nature of intention in an event is not always clear. Eventness and actionness is also dependent on the observer’s perspective. The narration in a story can make an occurrence seem more like an event or more like an action depending on the representation. For example, in Pride and Prejudice: Darcy and Bingley’s arrival at Netherfield is an event from the perspective of the Bennett family, but is certainly an action on the part of the characters themselves.

In an effort to further explain actions, Herman explores some parameters and categories of actions. The following types are borrowed from Von Wright (1983). These types relate to the intentional and effectual qualities of actions. (p.61):

1. Producing a given state of affairs
2. Leaving the state to continue absent
3. sustaining the state
4. letting the state cease to obtain
5. destroying the state
6. leaving the state to continue present
7. suppressing the state
8. letting the state come to obtain

Another system of parameters is borrowed from Rescher (1966; p. 215), and described on the next page (p. 62):

1. Agent (who did it)
2. Act-type (what did he do)
3. Modality of action (how did he or she do it?)
   a. Modality of manner (in what manner did he or she do it?)
   b. Modality of means (by what means did he or she do it?)
4. Setting of the action (in what context did he or she do it?)
   a. Temporal aspect (when did he or she do it?)
   b. Spatial aspect (where did he or she do it?)
   c. Circumstantial aspect (under what circumstances did he or she do it?)
5. Rationale of action (why did he or she do it?)
   a. Causality (what caused him or her to do it?)
   b. Finality (with what aim did he or she do it?)
   c. Intentionality (in what state of mind did he or she do it?)

This categorization and parameterization is useful as an analytic tool for reading actions in narratives, and also as a constructive tool for planning how actions should be composed and executed.

Scripts, Sequences, and Stories

Herman is attempting to discern here the difference between narrative and non-narrative forms. The difference seems to be in knowledge structures: schemata, scripts, and frames. These emerge from cognitive science, AI, and (I would argue) sociology. Storyness relates to expectations. Ultimately, this must be grounded in an experiential repertoire. Part of a story will trigger something that is activated, which will enable the rest of the story to make sense.

On one hand, this could be considered an instance of classical dramatic structure, but it also makes sense being more broadly understood as an artifact of cognition. The mind functions associatively, and constructs models. Together, these facts suggest that observed information (discourse or story elements) are actively assembled and make meaning when they form a model that is consistent with subsequent information.

Herman is arguing for a more narrow conception of narrative, though. Recipes or syllogisms are not exactly stories, but they do operate as models that make sense when assembled. He realizes this fuzzyness, and argues for a scalar range of narratives. The quality of narrativity depends primarily on a work’s recognition as narrative, but some works (for example Joyce’s Finnegans Wake) cannot be interpreted or recognized easily. This I would argue returns to the experiential basis of recognition. I would say that the capacity to identify a work as narrative is secondary to the capacity to recognize and understand the work in the first place.

Herman ties together elements of storyness, recognition, and originality. Stories are understood by familiarity with models and concepts. There is a conflict between the value of the form versus the content of a story. Herman argues that people use a number of processing strategies to make meaning from a story. These strategies are not elaborated, but I would guess that these strategies could be argued to make significant use of conceptual blending (of form, content, with prior experience and familiarity with other works).

Participant Roles and Relations

This section is on the relation between storyworld and participants. Herman generalizes participants from characters, because the term “participant” broadens the study, and focuses on involvementt and actions. The idea of participants (or actants) is borrowed from Greimas. Herman’s concern in this chapter is to differentiate between the participant/actant and circumstances. My intention here is to compare storyworld participants with the idea of the player. In the light that a storry is a representation of a storyworld populated by participants, the narrative to game comparison seems less stark and surprisingly natural.

There is a concern here over what sorts of roles and positions participants have. An example here is the distinction between processes and roles. Another genre typology compares some preferences: (p. 147)

1. Epic : Actor > Behaver > Sayer > Experiencer
2. Allegory : Identified > Actor > Sayer > Experiencer
3. 19th century realistic novel : Actor > Carrier > Sayer > Behaver
4. Psychological novel : Experiencer > Behaver > Carrier > Sayer
5. Detective novel : Experiencer > Actor
6. Ghost story : Experiencer > Sayer

In a game adaptation of a narrative, the player must be a participant, and be put into these roles, as appropriate for the particular genre or story.

This is liable to be a multi-part post, because it seems like there is a lot of ground to cover. I have a lot to say about The Sims. It bears noting first that the game I am most familiar with is not the original, but rather its sequel The Sims 2, which is also broadened by a variety of expansion packs. Generally, when I talk about The Sims, I am thinking of the whole franchise. As a game it is extremely notable, but also relevant to my research because of several factors:

1. It is a people simulator. Its subject matter is mundane and domestic, about people going about their lives in a day to day manner.
2. The AI that controls the Sims is ferociously dumb. The Sims act according to a hill climbing algorithm in relation to the world around them. The technical implementation of this is called “smart terrain” and all the logic is encoded within the objects with which the Sims interact.
3. The game is exceptionally evocative. The setting and characters are believable in a way that makes them engaging and fun to play with.
4. It broke the gender barrier: More than half the players of the Sims are female. This is especially true of the machinima community. (A citation would be helpful here)
5. The Sims has a powerful modular architecture that enables it to be modded easily, and is supplementable through expansion packs.
6. The Sims is the best selling PC game of all time.

All of these factors make the game extremely significant in the landscape of PC games everywhere, especially given the immense popularity and uniqueness of The Sims franchise. I want to explain here why it is so relevant to the work I am doing now.

The first and foremost reason why The Sims is relevant is because of the AI. The Sims themselves are believable, but not realistic. Characters have a state that is built around specific domain models (relationships, needs, “skills”, etc) rather than propositional models. What is fascinating about this is the sheer lack of material that could have been encoded into the model, what is more, the game works better because of this absence. Consider some of the things normally important to AI that have been left out. Beliefs and world knowledge is one example. Sims are totally autonomous. They can behave fine in one space just as well as another. Instead, all of the real intelligence is representational. The Sims are not believable because of an accurate or realistic model, but rather because of an evocative representational model.

There is an intricate balance in the game between simulation and representation. But, before it is possible to explore that in more detail, it is necessary to examine what is actually being simulated. The Sims is a people simulator. It represents domestic life, but as is the case with all Maxis games, it is a specific flavor of domestic life. The original game of the Sims presented a model of a materialistic suburban life. However, this model has been expanded in subsequent expansion packs. These expansions expand the complexity of the underlying model by introducing new logical elements. The Sims 2: Seasons is about how weather affects people’s moods and lives. The Sims 2: Free Time explores the social and personal dimensions of interests and hobbies. It will require a careful analysis to examine exactly what is being modeled, but some insight can be gained by looking into how the modeling works.

The original game of The Sims was heavily influenced by the logic of Maslow’s heirarchy of needs. The implementation in The Sims places each element: needs, relationships, skills in terms of sliding numeric values. This approach of representing things numerically can be considered The Sims modeling strategy. This approach is effective but also leaves out a great amount of detail. The strategy can convey simple relationships (between entities and concepts) in a domain. Notably, this representation strategy cannot represent complex relationships where there is a formal structure between entities. An example of this sort of complexity is in human relationships when there is internal complexity and occasional self contradictions. Another example of this flaw can be seen in the single/dual axis representations of morality in games (Fable, D&D).

The work that I am doing uses a very different modeling strategy. My strategy is much more symbolically oriented and structural, because my goal is to represent the sorts of relationships that are impossible with numerical sliders. Specifically, human behavior and relationships are modeled using Goffman’s framework revolving around roles and performance, which are fuzzy and complex. The real issue at steak is how to increase logical complexity without undermining representational power.

Overview:

This collection was released in 1983, the same year as Jonson-Laird’s publishing of a book with the same name. While Johnson-Laird is concerned with developing a linguistic theory of mental models grounded in computational theory, Gentner and Stevens present a collection of papers on how mental models are used in numerous applications. There is a strong theme of using models in science, especially science education and expert reasoning.

My concern with mental models is twofold: I want to understand how to model characters within simulation, and I also want to understand how users will form models after interacting with a simulation. I am not as concerned with the instruction and dissemination of a specific model, but rather, I want to find ways of provoking introspection and criticism of models.

In these essays, individuals have and use models, often conflicting models. With so many conflicting models it seems almost a wonder that people can think at all. Model use is often ingrained and automatic, but only when the model appears to be inconsistent with the subject to which the model is applied, does the model become suddenly a conscious jumble of ideas and rules. My reading of Gentner and Stevens is going to primarily be oriented towards examining these areas of model formation, use, and critique.

Notes:

Mental models, as argued here, are how we understand the world. Research on them is about furthering and deepening self understanding. Applied use of mental models is pedagogical, teaching better models, and teaching models better, for applied use. Mental models research tends to have three dimensions. These are good guidelines for considering models of fictional domains.

1. Domains. In mental models research, the problem domains should be something tractable, where it is possible to discern an expert from a novice. Thus, a domain such as fluid dynamics is more tractable than interpersonal dynamics. It is easier to distinguish an expert in a scientific domain than a humanistic one.
2. Theoretical Approach. The research should have a formal representation of the models to be used. Representations are usually made with computational semantics. I would argue that not all domains will have the same representations, but some formalization is necessary.
3. Methodology. The methodologies used are highly varied and eclectic. This can be anything from protocol analysis, to psychological experiments, to simulation and comparison with experts.

This is priceless: “From what we have said so far, it is clear that the ideal mental-models researcher would be a combination of cognitive psychologist, artificial intelligence researcher, anthropologist, linguist, and philosopher, and certainly a knowledgable practitioner of the domain being studied.” The suite of skills is very reminiscent of the artist/programmer and theorist/practitioner interdisciplinary hybrids.

Donald Norman: Some Observations on Mental Models

Norman’s paper is to essentially extend the introduction and explain a little bit more about what mental models are and what sort of properties they have. Norman explains that his goal is to partly belabour the obvious. He gives a few useful bullet points about how he sees mental models (p. 8):

1. Mental models are incomplete.
2. People’s abilities to “run” their models are severely limited.
3. Mental models are unstable: People forget the details of the system they are using, especially when those details (or the whole system) have not been used for some period.
4. Mental models do not have firm boundaries: similar devices and operations get confused with one another.
5. Mental models are “unscientific”: people maintain “superstitious” behavior patterns even when they know they are unneeded because they cost little in physical effort and save mental effort.
6. Mental models are parsimonious: Often people do extra physical operations rather than the mental planning that would allow them to avoid those actions; they are willing to trade-off extra physical action for reduced mental complexity. This is especially ture where the extra actions allow one simplified rule to apply to a variety of devices, thus minimizing the chances for confusion.

Norman also explains some formalizations of models. A system is t, the conceptualization is C, and the model M. The conceptualization, as defined, is the scientific or expert model of the system. Four elements may be observed: t, the system itself. C(t), the expert model of the system. M(t), the user’s model of the system. Finally, C(M(t)) is the researcher’s understanding of the user’s mental model. There are three issues related to understanding models: beliefs, observability, and predictive power.

The formulation of conceptual models is as tools for teaching a system. This phrasing privleges it to other kinds of models. It suggests thtat ideally, M(t) = C(t). This is the notion of classic authorship, privleging the author’s interpretation, precisely the sort of thing that Barthes rebelled against. The idea is necessarily that the expert’s understanding is the ideal way, and that a user’s model is wrong if it does not line up. This makes sense when the subject matter is something like a Nuclear reactor, where it is important for users have a strong and correct model that reflects the system itself, but it is less explicable when dealing with everyday artifacts that may be used toward a variety of ends, as opposed to original stated goals.

Jill Larkin: The Role of Problem Representation in Physics

The problem here is the relationship between ordinary human prediction with formal physics. A naive representation or model uses objects in the real world, but an expert will construct a special model in addition, that replaces objects with physical objects (that have special properties), and also includes fictitious entities, such as forces and moments.

Physicists use several schemas for producing physical representations. The schemas are the “forces schema” and the “work-energy schema.” Both of these have internally consistent sets of rules and operations. They are consistent with each other, but require very different understandings of the underlying problems. Representations have rules for construction and extension, and these are very different between the two schemas.

Larkin examines how several users of varying proficiency apply these schemas in problem solving, from easy problems, to hard, and then very hard problems. Harder problems require the solver to make use of multiple schemas and translate between them. In the very hard problem, the subjects will form a model with a schema, attempt to work with it, and then discard it if it is inconsistent. The very hard problem can be solved using one of the schemas, but the translation from the given information in the problem cannot be filled in directly. Expert subjects quickly select a schema and then spend time constructing the model itself.

Novice problem solvers, specifically students, quickly match problems to quantitative models, without constructing a physical representation. This seems to be done via pattern matching, identifying elements in the problem that fit into to learned formulas.

Williams, Hollan, Stevens: Human Reasoning About a Simple Physical System

The goal here is to understand reasoning with mental models. A model is a tool used in reasoning. Understanding a model and how it is used informs understanding of human mistakes and reasoning. The authors give an extremely useful formalization of models. A model is runnable, with autonomous objects with some internal topology. An autonomous object has an explicit state, relations, parameters, and rules. The model is a collection of autonomous objects. (p. 133-134)

The concept of an autonomous object is extremely important to the author’s formalization of models here. It further strongly resembles the way to construct a system for simulation. If objects are autonomous, the model can simply be run by gathering the objects together and applying the rules of the system over time. According to the description given, autonomous objects are generally opaque, but may themselves be deconstructed into models themselves. Generally, they will only have 3 to 4 ports with which to interact with other objects.

The rest of the chapter explores the applications of this theory of mental models to subjects understanding of a heat exchanger. The exchanger is the simple physical system, and the authors examine the models that subjects form while trying to answer questions about the system. There are about three models used, which are inconsistent with each other and thus exclusive. The way subjects form the models is analyzed according to inference diagrams. Models are shifted rapidly, and subjects uses multiple models to answer questions. New models are only created when some form of inconsistency occurs.

Each of the models also appear to be grounded in some sort of metaphorical analogy. For example, the pipes in the exchanger are containers: they contain heat. Thus, the subject reasons about the pipes as they would reason about containers.

Michael McCloskey: Naive Theories of Motion

This section is concerned with understanding students naive theories of motion. Many students make very similar mistakes regarding the motion of objects. What is startling is that the naive theoriy of motion is internally conistent, and shared very consistently among the observed subjects. That means that most incorrect responses are of the same inherent type, and stem from a single misconception about objects.

The naive theory of physics is essentially “impetus” theory, which has roots in pre-Newtonian science. The idea with impetus theory is an object that is moving has some internal force that keeps it going. Without extra effort spent pushing the object, the impetus will eventually subside and the object will stop. This is fascinating because it relates back to emobodiment and self-analogy: Young learners will understand objects as they understand themselves: “I have to expend effort to keep moving, so other objects moving must do that as well.” This model is pervasive, and even knowledgable subjects who understand the principles of energy and momentum will explain those concepts in terms of impetus.

There is a brief discussion on education. We should think here about exploring more complex models (that do not have a necessarily correct solution to every problem). What is revealing is that for dispersal of impetus theory, it is not enough to simulate the real models, but rather deconstruct the faulty ones. This is important in situations where models are ambiguous or complicated. There is an emphasis here on exposure. It is of utmost importance to expose the internal workings of flawed or faulty models.

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.