An edition of Programming with constraints
(1998)
Programming with constraints
an introduction
by Kim Marriott
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A comprehensive, self-contained introduction to constraint programming, in which programs are represented as relational equations between values and variables, and execution consists of assigning values to the variables that maintain the relational equations.
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Programming with constraints: an introduction
1998, MIT Press
Hardcover
in English
0262133415 9780262133418
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Book Details
Table of Contents
Table of Contents
Preface
Introduction
Notes
I. Constraints
1. Constraints
1.1. Constraints and Valuations
1.2. Modelling with Constraints
1.3. Constraint Satisfaction
1.4. Tree Constraints
1.5. Other Constraint Domains
1.6. Properties of Constraint Solvers
1.7. (*) Determined Variables and Local Propagation
1.8. Summary
1.9. Exercises
1.10. Practical Exercises
1.11. Notes
2. Simplification, Optimization and Implication
2.1. Constraint Simplification
2.2. Projection
2.3. Constraint Simplifiers
2.4. Optimization
2.5. The Simplex Algorithm
2.6. (*) Canonical Form Simplifiers
2.7. (*) Implication and Equivalence
2.8. Summary
2.9. Exercises
2.10. Practical Exercises
2.11. Notes
3. Finite Constraint Domains
3.1. Constraint Satisfaction Problems
3.2. A Simple Backtracking Solver
3.3. Node and Arc Consistency
3.4. Bounds Consistency
3.5. Generalized Consistency
3.6. Optimization for Arithmetic CSPs
3.7. Summary
3.8. Exercises
3.9. Practical Exercises
3.10. Notes
II. Constraint Logic Programming
4. Constraint Logic Programs
4.1. User-Defined Constraints
4.2. Programming with Rules
4.3. Evaluation
4.4. Derivation Trees and Finite Failure
4.5. Goal Evaluation
4.6. Simplified Derivation Trees
4.7. The CLP Scheme
4.8. (*) Independence from Rule Ordering and Literal Selection
4.9. Summary
4.10. Exercises
4.11. Practical Exercises
4.12. Notes
5. Simple Modelling
5.1. Simple Modelling
5.2. Modelling Choice
5.3. Iteration
5.4. Optimization
5.5. Summary
5.6. Practical Exercises
5.7. Notes
6. Using Data Structures
6.1. Records
6.2. Lists
6.3. Association Lists
6.4. Binary Trees
6.5. Hierarchical Modelling
6.6. Tree Layout
6.7. Summary
6.8. Practical Exercises
6.9. Notes
7. Controlling Search
7.1. Estimating the Efficiency of a CLP Program
7.2. Controlling Search: An Example
7.3. Rule Ordering
7.4. Literal Ordering
7.5. Adding Redundant Constraints
7.6. Minimization
7.7. Identifying Deterministic Subgoals
7.8. An Extended Example: Bridge Building
7.9. Summary
7.10. Exercises
7.11. Practical Exercises
7.12. Notes
8. Modelling with Finite Domain Constraints
8.1. Domains and Labelling
8.2. Complex Constraints
8.3. Labelling
8.4. Different Problem Modellings
8.5. An Extended Example: Scheduling
8.6. (*) Arc Consistency
8.7. (*) Library Predicates
8.8. Summary
8.9. Practical Exercises
8.10. Notes
9. Advanced Programming Techniques
9.1. Extending the Constraint Solver
9.2. Combined Symbolic and Arithmetic Reasoning
9.3. Programming Optimization
9.4. Higher-order Predicates
9.5. Negation
9.6. CLP Languages with Dynamic Scheduling
9.7. (*) Meta Programming
9.8. (*) Library Predicates
9.9. Summary
9.10. Practical Exercises
9.11. Notes
10. CLP Systems
10.1. Simple Backtracking Goal Evaluation
10.2. Incremental Constraint Solving
10.3. Efficient Saving and Restoring of the Constraint Store
10.4. Implementing If-Then-Else, Once and Negation
10.5. Optimization
10.6. Other Incremental Constraint Solvers
10.7. (*) Incremental Real Arithmetic Solving
10.8. Summary
10.9. Exercises
10.10. Notes
III. Other Constraint Programming Languages
11. Constraint Databases
11.1. Modelling with Constraint Databases
11.2. Bottom Up Evaluation
11.3. Bottom-Up versus Top-Down
11.4. Mimicking Top-Down Evaluation Bottom-Up
11.5. (*) Improving Termination
11.6. (*) Relationship with Relational Databases
11.7. Summary
11.8. Exercises
11.9. Practical Exercises
11.10. Notes
12. Other Constraint Programming Languages
12.1. The CLP Paradigm
12.2. Concurrent Constraint Programming Languages
12.3. Constraint Handling Rules
12.4. Functional Languages
12.5. Term Rewriting
12.6. Imperative Programming Languages
12.7. Constraint Solving Toolkits
12.8. Mathematical Languages
12.9. Notes
References
Index
Edition Notes
Includes bibliographical references and index.
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