Formalizations of Commonsense Psychology Authored By: Andrew Gordon & Jerry Hobbs Presented By: G. Ryan Anderson

Introduction to Commonsense Psychology Concerns all of the aspects of the way people think they think Plans, goals, threats, emotions, memories, and all other mental states that can exist Central in our ability to reason and make deep inferences More informed by the field of cognitive psychology than by AI

How could this be useful to AI? Systems that can successfully reason about people are likely to be much more useful than systems grounded in the natural sciences

How can this be used in AI? Formal axioms for commonsense knowledge representation Theories with adequate competence Theories with adequate coverage

Representational Requirements Group aspects and characteristics of various domains into a manageable set of representational areas 48 total representational areas

Representational Requirements Sample set of representational areas below Representation somewhat incomplete, and more elaboration is necessary

Using Natural Language for Commonsense Representation Natural language is very effective in making conceptual distinctions Language-based methodology for elaborating on the previously mentioned representational areas

Step One: Expression Elicitation Acquire an initial set of words, expressions, and sentences used to relate to a given representational area

Step Two: Lexical Expansion Take our set of expressions from step one Search for related words and expressions, using linguistic resources Builds up the quantity of expressions for a given area, thus giving a deeper degree of coverage

Step Three: Corpus Analysis Collection of a large database of examples of language use in the representational area

Step Four: Model Building Review the results of step three to understand the distinctions made in real language use Clustering of sentences, words, and other expressions into sets where they are synonymously used

Building a Commonsense Theory of Memory Having built a set of representational constructs, we can now axiomize our data into formal theories Memory Retrieval is one of the 48 areas mentioned earlier

Concepts in Memory

Accessibility of Concepts

Association of Memories

Association of Memories (cont.) Example of formal axiom for concept association

Other Aspects of Memory Remembering Forgetting Repressing

Conclusions Development of theories with adequate coverage and competency Sorted into manageable amount of domains Elaborate on domains using natural language tactics Results can be moulded into more formal axioms

Conclusions (cont.) Memory is one of 48 representational areas Challenge lies in integrating all 48 areas Overall goal is to construct AI systems that have a solid representation of human commonsense models to more effectively reason the way humans do

Questions? Paper can be found at http://people.ict.usc.edu/~gordon/AIMAG04.PDF