Uncertainty in Artificial Intelligence 5

Uncertainty in Artificial Intelligence 5

1st Edition - July 10, 1990

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  • Editors: R.D. Shachter, L.N. Kanal, M. Henrion, J.F. Lemmer
  • eBook ISBN: 9781483296555

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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.

Product details

  • No. of pages: 456
  • Language: English
  • Copyright: © North Holland 1990
  • Published: July 10, 1990
  • Imprint: North Holland
  • eBook ISBN: 9781483296555

About the Editors

R.D. Shachter

Affiliations and Expertise

Stanford University, Stanford, CA, USA

L.N. Kanal

Affiliations and Expertise

University of Maryland, Department of Computer Science, College Park, MD, USA

M. Henrion

Affiliations and Expertise

Rockwell International Science Center, Palo Alto, CA, USA

J.F. Lemmer

Affiliations and Expertise

CTA, Inc., Rome, NY USA

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