Constraint-based reasoning

Author(s)

• Freuder, Eugene C.
• Mackworth, Alan K.

Bibliographic Information

Constraint-based reasoning

edited by Eugene C. Freuder and Alan K. Mackworth

MIT Press, 1994, c1992

Note

"A Bradford book."

Reprinted from Artificial intelligence, volume 58, numbers 1-3, 1992

Includes bibliographical references and index

Description and Table of Contents

Description

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.

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.

by "Nielsen BookData"

Details

• NCID: BA22550632
• ISBN:
  • 0262560755
• LCCN: 93021600
• Country Code: us
• Title Language Code: eng
• Text Language Code: eng
• Place of Publication: Cambridge, Mass.
• Pages/Volumes: 403 p.
• Size: 26 cm
• Classification:
  • LCC : Q340
  • DC20 : 006.3
• Subject Headings:
  • LCSH : Constraints (Artificial intelligence)
  • LCSH : Reasoning