Knowledge representation

Draft

Introduction

Adopting a cognitivist stance one can describe cognitive processes as operations carried out on symbol structures.

Some cognitivists I -> PS -> R model (as opposed to the behaviorist S->R model)

    I  ---------------->    PS    ---------------->   R

 Interpretation of    principle-oriented         Complex Reaction
 complex situation      problem solving
 

In order to model this kind of behavior, one must assume that knowledge is structured, i.e. composed of distinguishable elements which are interconnected in a well defined way.

Knowledge representation is a very difficult matter, but to start with and in modeling terms, one can think of it as combination of data-structures and interpretive procedures that will lead to knowledgable behavior. (The Handbook of AI:143).

For some authors knowledge is stored either in episodic or semantic memory. The further is organized in spacio-temporal dimensions, the second according semantic content-oriented principles, e.g. networks of concepts.

Semantic Networks

See semantic networks

Schemas and similar structures

Much human knowledge is probably organized in large organized chunks as many research in text understanding points out. Experimental research on story recall (Bartlett 32) already in 1932 convincingly demonstrated that subjects confronted with new information (a unkown story) try to relate it to already known knowledge in a particular and systematic way. Of a given story, many elements were deleted, deformed and new elements were added. This wouldn't be surprising, if it wouldn't happen in a systematic way:

1. Strange unknown elements of the story are translated into more well known concepts,
2. difficult concepts are skipped,
3. the story is reorganized in order gain (subjective) meaning.

We can generalize these observation which since then have been replicated many times. Processing of "narrative" input relies heavily on stereotypical knowledge we have on social episodes. Furthermore, input is integrated into canonical structures that help organize the story and its memorization. Research on the understanding of other textual structures suggest that similar hypothesis can be made about objects such as typical roles of persons, institutions, etc.

Some experimental research in more traditional cognitive science concerned so called "natural kinds", they way in which people classify real objects. The simplest theories state that normally all encountered objects are compared to proto-types, detailed desctiptions of a kind (type), and understood in terms of allowable deviation. We think that the more sophisticated "feature-set" theory better fits reality: Individuals have a high sensibility for the correlations of charateristics they encounter in the environment. Furthermore they have the tendency to build abstractions for the set of characteristics that define a category. Of course, they also memorize sometimes specific examples. Consequently, when people encounter an objects it will be compared to the set of important characteristics defining classes of objects, but also to specific exemplaries which can serve as negative of positive proto-types. Such, more traditional research, works with simple objects. Generalizations could be attempted only for single objects and concepts.

Unfortunately is is much harder to test how more complex structures might be represented. It is even worse to know how they might intervene and be what in a problem-solving process such as the understanding of "narrative" text. It can be convincingly shown, however, that people do "frame" perception in certain systematic ways (e.g. Tverski and Kahnemann ???). Such global patterns are probably not only the result of search, but they would be stored as complete chunks. Consequently, cognitive science proposes several forms of knowledge organizations which we would like to sketch out by given the definition of DeBeaugrande (81:90):

Frames are global patterns that contain commonsense knowledge about come central concept.

Frames state what things belong together in principle, but

not in what order things will be done or mentionned.

Schemas are global patterns of events and states in ordered sequencies linked by time proximity and causality.

Unlike frames, schemas are always arrayed in a progression,

so that hypotheses can be set up about what will be done or mentionned next in a textual world.

Plans are global patterns of events and states leading up to an intended

Plans differ from schemas in that a planner [...] evaluates all elements in terms of how they advance toward the planner's goal.

Scripts are stabilized plans called up very frequently to specify the roles of participants and their expected actions.

Scripts thus differ from plans be having a pre-established routine.

Using such global patterns people can greatly reduce complexity in inference processes. They also allow to retain much more information in active storage at the time, i.e. one can understand very complex situations by integrating the information into these coherent knowledge structures instead of building up coherent meaning by manipulating small "local" concepts. The structures we cited are not the only one discussed, but they illustrate very nicely the general idea. It is important to realize that these structures not only represent hooked up information, but that they have processing knowledge attached activated when used. Know-what and know-how is intrinsically related.