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Logic and Representationcover

Logic and Representation

Robert C. Moore

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.


  • Acknowledgements
  • Introduction
  • Part I Methodological Arguments
  • 1 The Role of Logic in Artificial Intelligence
    • 1.1 Logic as an Analytical Tool
    • 1.2 Logic as a Knowledge Representation and Reasoning System
    • 1.3 Logic as a Programming Language
    • 1.4 Conclusions

  • 2 A Cognitivist Reply Behaviorism
  • Part II Methodological Arguments
  • 3 A Formal Theory of Knowledge and Action
    • 3.1 The Interplay of Knowledge and Action
    • 3.2 Formal Theories of Knowledge
    • 3.3 Formalizing the Possible-World Analysis of Knowledge
    • 3.4 A Possible-Worlds Analysis of Action
    • 3.5 An Integrated Theory of Knowledge and Action

  • 4 Computational Models of Belief and the Semantics of Belief Sentences
    with G.G. Hendrix
    • 4.1 Computional Theories and Computational Models
    • 4.2 Internal Languages
    • 4.3 A Computational Model of Belief
    • 4.4 The Semantics of Belief Sentences
    • 4.5 Conclusion

  • 5 Propositional Attitudes and Russellian Propositions
    • 5.1 Introduction
    • 5.2 The Problem of Attitude Reports
    • 5.3 How Fine-Grained Must Propositions Be?
    • 5.4 Could Propostions Be Syntactic?
    • 5.5 The Russellian Theory
    • 5.6 Russellian Logic
    • 5.7 Why Propositional Functions?
    • 5.8 Proper Names
    • 5.9 Conclusion

  • Part III Autoepistemic Logic
  • 6 Semantical Considerations on Nonmonotonic Logic
    • 6.1 Introduction
    • 6.2 Nonmonotonic Logic and Autoepistemic Reasoning
    • 6.3 The Formalization of Autoepistemic Logic
    • 6.4 Analysis of Nonmonotonic Logic
    • 6.5 Conclusion

  • 7 Possible-World Semantics for Autosepistemic Logic
    • 7.1 Introduction
    • 7.2 Summary of Autosepistemic Logic
    • 7.3 An Alternative Semantics for Autoepistemic Logic
    • 7.4 Applications of Possible-World Semantics

  • 8 Autoepistemic Logic Revisited
  • Part IV Semantics of Natural Language
  • 9 Events, Situations, and Adverbs
    • 9.1 Introduction
    • 9.2 Some Facts about Adverbs and Event Sententences
    • 9.3 Situations and Events
    • 9.4 The Analysis
    • 9.5 Conclusions

  • 10 Unification-Based Semantic Interpretation
    • 10.1 Introduction
    • 10.2 Functional Application vs. Unification
    • 10.3 Are Lambda Expressions Ever Necessary
    • 10.4 Theoretical Foundations of Unification-Based Semantics
    • 10.5 Semantics of Long-Distance Dependencies
    • 10.6 Conclusions

  • References
  • Index


ISBN (Paperback): 1881526151 (9781881526155)
ISBN (Cloth): 188152616X (9781881526162)
ISBN (Electronic): 1575868180 (9781575868189)

Subject: Logic; Language and Logic; Semantics

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