Overview
- Editors:
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Laveen Kanal
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Department of Computer Science, University of Maryland, College Park, USA
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Vipin Kumar
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Computer Science Department, University of Texas at Austin, Austin, USA
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Table of contents (13 chapters)
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- Vipin Kumar, Laveen N. Kanal
Pages 1-27
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- Vipin Kumar, Dana S. Nau, Laveen N. Kanal
Pages 91-130
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- Rina Dechter, Judea Pearl
Pages 166-199
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- Ranan B. Banerji, George W. Ernst
Pages 268-286
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- Rina Dechter, Judea Pearl
Pages 370-425
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- Ugo Montanari, Francesca Rossi
Pages 426-449
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- Ping-Chung Chi, Dana S. Nau
Pages 450-471
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Back Matter
Pages 473-482
About this book
Search is an important component of problem solving in artificial intelligence (AI) and, more generally, in computer science, engineering and operations research. Combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics and theorem proving are some of the areas in which search algbrithms playa key role. Less than a decade ago the conventional wisdom in artificial intelligence was that the best search algorithms had already been invented and the likelihood of finding new results in this area was very small. Since then many new insights and results have been obtained. For example, new algorithms for state space, AND/OR graph, and game tree search were discovered. Articles on new theoretical developments and experimental results on backtracking, heuristic search and constraint propaga tion were published. The relationships among various search and combinatorial algorithms in AI, Operations Research, and other fields were clarified. This volume brings together some of this recent work in a manner designed to be accessible to students and professionals interested in these new insights and developments.
Editors and Affiliations
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Department of Computer Science, University of Maryland, College Park, USA
Laveen Kanal
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Computer Science Department, University of Texas at Austin, Austin, USA
Vipin Kumar
