Overview

Constraint-based reasoning is an important area of automated reasoning with many applications in artificial intelligence. 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. This text 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.

Full Product Details

Author:   Eugene C. Freuder ,  Alan K. Mackworth
Publisher:   MIT Press Ltd
Imprint:   MIT Press
Dimensions:   Width: 19.60cm , Height: 2.30cm , Length: 25.10cm
Weight:   0.953kg
ISBN:  

9780262560757

ISBN 10:   0262560755
Pages:   409
Publication Date:   04 February 1994
Recommended Age:   From 18 years
Audience:   Professional and scholarly ,  General/trade ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock  
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Table of Contents

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 et al; minimizing conflicts - a heuristic repair method for constraint satisfaction and scheduling problems, S. Minton et al; arc consistency - parallelism and domain dependence, P.R. Cooper and M.J. Swain; structure identification in relational data, R. Dechter and J. Pearl; learning to improve constraint-based scheduling, M. Zweben et al; reasoning about qualitative temporal information, P. van Beek; a geometric constraint engine, G.A. Kramer; a theory of conflict resolution in planning, Q. Yang.

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