Reasoning Under Incomplete Information in Artificial Intelligence
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Reasoning Under Incomplete Information in Artificial Intelligence

Reasoning Under Incomplete Information in Artificial Intelligence

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About the Book

The formalization of "revisable reasoning" has been the object of numerous works, developed independently and using diverse approaches - approaches that are purely symbolic, that use numbers to quantify uncertainty, and that are close to formal logic or less formalized. This work presents and compares several of these revisable (incomplete) reasoning methods used in artificial intelligence. Each method is systematically evaluated with a single example to give the reader an appreciation of the rationale and use of each formulation. Topics considered include: default logic, non-monotonic modal logics, the supposition-based logic, and the conditional logics of uncertainty. The book also discusses the contribution of works on truth maintenance and the logic of action.

Table of Contents:
Why New Logics Are Needed. Default Logic. Nonmonotonic Modal Logics. Closed World Assumption and Circumscription. A Nonmonotonic Logic Based on Suppositions. Conditional Logics and ''Rough'' Implications. Logics of Uncertainty. Fuzzy Logic. Numerical Quantifiers and Conditional Probabilities. Causal Models. Reasoning by Analogy. Truth-Maintenance Systems. Theories of Action and the Frame Problem. Revision Theory. A Tentative Conclusion. References. Index.


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Product Details
  • ISBN-13: 9780471529798
  • Publisher: John Wiley and Sons Ltd
  • Publisher Imprint: John Wiley & Sons Inc
  • Height: 260 mm
  • Returnable: N
  • Width: 185 mm
  • ISBN-10: 0471529796
  • Publisher Date: 10 Sep 1990
  • Binding: Hardback
  • Language: English
  • Weight: 510 gr


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Reasoning Under Incomplete Information in Artificial Intelligence
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Reasoning Under Incomplete Information in Artificial Intelligence
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