Uncertainty in artificial intelligence 5
Author(s)
Bibliographic Information
Uncertainty in artificial intelligence 5
（Machine intelligence and pattern recognition, v. 10）
North-Holland , Distributors for the U.S. and Canada, Elsevier Science Pub. Co., c1990
- pbk.
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
This volume, like its predecessors, reflects the cutting edge of research on the automation of reasoning under uncertainty. A more pragmatic emphasis is evident, for although some papers address fundamental issues, the majority address practical issues. Topics include the relations between alternative formalisms (including possibilistic reasoning), Dempster-Shafer belief functions, non-monotonic reasoning, Bayesian and decision theoretic schemes, and new inference techniques for belief nets. New techniques are applied to important problems in medicine, vision, robotics, and natural language understanding.
Table of Contents
Fundamental Issues. Defeasible Reasoning and Uncertainty. Algorithms for Inference in Belief Nets. Software Tools for Uncertain Reasoning. Knowledge Acquisition, Modelling, and Explanation. Applications to Vision and Recognition. Comparing Approaches to Uncertain Reasoning. Author Index.
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