Constraint-based Reasoning

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Eugene C. Freuder, Alan K. Mackworth
MIT Press, 1994 - Computers - 403 pages
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Constraint-based reasoning is an important area of automated reasoning in artificial intelligence, with many applications. These include configuration and design problems, planning and scheduling, temporal and spatial reasoning, defeasible and causal reasoning, machine vision and language understanding, qualitative and diagnostic reasoning, and expert systems. Constraint-Based Reasoning presents current work in the field at several levels: theory, algorithms, languages, applications, and hardware.

Constraint-based reasoning has connections to a wide variety of fields, including formal logic, graph theory, relational databases, combinatorial algorithms, operations research, neural networks, truth maintenance, and logic programming. The ideal of describing a problem domain in natural, declarative terms and then letting general deductive mechanisms synthesize individual solutions has to some extent been realized, and even embodied, in programming languages.

Contents: "Introduction," E. C. Freuder, A. K. Mackworth. "The Logic of Constraint Satisfaction," A. K. Mackworth. "Partial Constraint Satisfaction," E. C. Freuder, R. J. Wallace. "Constraint Reasoning Based on Interval Arithmetic: The Tolerance Propagation Approach," E. Hyvonen. "Constraint Satisfaction Using Constraint Logic Programming," P. Van Hentenryck, H. Simonis, M. Dincbas. "Minimizing Conflicts: A Heuristic Repair Method for Constraint Satisfaction and Scheduling Problems," S. Minton, M. D. Johnston, A. B. Philips, and P. Laird. "Arc Consistency: Parallelism and Domain Dependence," P. R. Cooper, M. J. Swain. "Structure Identification in Relational Data," R. Dechter, J.Pearl. "Learning to Improve Constraint-Based Scheduling," M. Zweben, E. Davis, B. Daun, E. Drascher, M. Deale, M. Eskey. "Reasoning about Qualitative Temporal Information," P. van Beek. "A Geometric Constraint Engine," G. A. Kramer. "A Theory of Conflict Resolution in Planning," Q. Yang.

A Bradford Book.

  

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Contents

E G Freuder and A K Mackworth
1
Freuder and R J Wallace
21
E Hyvonen
71
P Van Hentenryck H Simonis and M Dincbas
113
S Minton M D Johnston A B Philips and P Laird
161
P R Cooper and M J Swain
207
R Dechter and J Pearl
234
Zweben E Davis B Daun E Drascher M Deale and M
271
P van Beek
297
G A Kramer
327
Q Yang
361
Index
393
Copyright

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About the author (1994)

Alan Mackworth is a Professor of Computer Science and Canada Research Chair in Artificial Intelligence at the University of British Columbia. He is known for his research on constraint-based systems and agents, hybrid systems, and robot soccer. He is a co-author of Computational Intelligence: A Logical Approach. He was President and Trustee of International Joint Conferences on AI (IJCAI) Inc. Mackworth was Vice President and President of the Canadian Society for Computational Studies of Intelligence (CSCSI). He has served as President of the Association for the Advancement of Artificial Intelligence (AAAI). He also served as the founding Director of the UBC Laboratory for Computational Intelligence. He is a Fellow of AAAI, the Canadian Institute for Advanced Research, and the Royal Society of Canada.