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    Uncertainty in Artificial Intelligence 5: 010 (Machine Intelligence and Pattern Recognition)

    By Max Henrion

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    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.

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