Logic and Representation brings together a collection of essays, written over a period of ten years, that apply formal logic and the notion of explicit representation of knowledge to a variety of problems in artificial intelligence, natural language semantics, and the philosophy of mind and language. Particular attention is paid to modeling and reasoning about knowledge and belief, including reasoning about one's own beliefs, and the semantics of sentences about knowledge and belief.

Robert C. Moore begins by exploring the role of logic in artificial intelligence, considering logic as an analytical tool., as a basis for reasoning systems, and as a programming language. He then looks at various logical analyses of propositional attitudes, including possible-world models, syntactic models, and models based on Russellian propositions. Next Moore examines autoepistemic logic, a logic for modeling reasoning about one's own beliefs. Rounding out the volume is a section on the semantics of natural language, including a survey of problems in semantic representation; a detailed study of the relations among events, situations, and adverbs; and a presentation of a unification-based approach to semantic interpretation.

Robert C. Moore is principal scientist of the Artificial Intelligence Center of SRI International.

Part I. Methodological Arguments: 1. The role of logic in artificial intelligence: 2. A cognitivist reply to behaviourism
Part II. Propositional Attitudes: 3. A formal theory of knowledge and action
4. Computational models of belief and the semantics of belief sentences
5. Propositional attitudes and Russellian propositions
Part III. Autoepistemic Logic: 6. Semantical considerations on nonmonotonic logic
7. Possible-world semantics for autoepistemic logic
Part IV. Semantics of Natural Language: 8. Events, situations, and adverbs
9. Unification-based semantic interpretation
Index.