- Cover Image
- Table of Contents
- Front Matter
- Copyright
- List of Algorithms
- Preface
- Chapter 1. Introduction
- Chapter 2. Basic Search Algorithms
- Chapter 3. *Dictionary Data Structures
- Chapter 4. Automatically Created Heuristics
- Chapter 5. Linear-Space Search
- 5.1. *Logarithmic Space Algorithms
- 5.2. Exploring the Search Tree
- 5.3. Branch-and-Bound
- 5.4. Iterative-Deepening Search
- 5.5. Iterative-Deepening A*
- 5.6. Prediction of IDA* Search
- 5.7. *Refined Threshold Determination
- 5.8. *Recursive Best-First Search
- 5.9. Summary
- 5.10. Exercises
- 5.11. Bibliographic Notes
- Chapter 6. Memory-Restricted Search
- Chapter 7. Symbolic Search
- 7.1. Boolean Encodings for Set of States
- 7.2. Binary Decision Diagrams
- 7.3. Computing the Image for a State Set
- 7.4. Symbolic Blind Search
- 7.5. Limits and Possibilities of BDDs
- 7.6. Symbolic Heuristic Search
- 7.7. * Refinements
- 7.8. Symbolic Algorithms for Explicit Graphs
- 7.9. Summary
- 7.10. Exercises
- 7.11. Bibliographic Notes
- Chapter 8. External Search
- Chapter 9. Distributed Search
- Chapter 10. State Space Pruning
- Chapter 11. Real-Time Search
- Chapter 12. Adversary Search
- Chapter 13. Constraint Search
- Chapter 14. Selective Search
- 14.1. From State Space Search to Minimization
- 14.2. Hill-Climbing Search
- 14.3. Simulated Annealing
- 14.4. Tabu Search
- 14.5. Evolutionary Algorithms
- 14.6. Approximate Search
- 14.7. Randomized Search
- 14.8. Ant Algorithms
- 14.9. * Lagrange Multipliers
- 14.10. * No-Free-Lunch
- 14.11. Summary
- 14.12. Exercises
- 14.13. Bibliographic Notes
- Chapter 15. Action Planning
- Chapter 16. Automated System Verification
- Chapter 17. Vehicle Navigation
- Chapter 18. Computational Biology
- Chapter 19. Robotics
- Bibliography
Front Matter
Heuristic Search
Heuristic Search
Theory and Applications
Stefan Edelkamp
Stefan Schrödl
AMSTERDAM • BOSTON • HEIDELBERG • LONDON • NEW YORK • OXFORD • PARIS • SAN DIEGO • SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO 
Morgan Kaufmann is an imprint of Elsevier
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