Heuristic Search: Theory and Applications

Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed.

Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us.

PART I Heuristic Search Primer Chapter 1 Introduction Chapter 2 Basic Search Algorithms Chapter 3 Dictionary Data Structures Chapter 4 Automatically Created Heuristics

PART II Heuristic Search under Memory Constraints Chapter 5 Linear-Space Search Chapter 6 Memory Restricted Search Chapter 7 Symbolic Search Chapter 8 External Search

PART III Heuristic Search under Time Constraints Chapter 9 Distributed Search Chapter 10 State Space Pruning Chapter 11 Real-Time Search by Sven Koenig

PART IV Heuristic Search Variants Chapter 12 Adversary Search Chapter 13 Constraint Search Chapter 14 Selective Search

PART V Heurstic Search Applications Chapter 15 Action Planning Chapter 16 Automated System Verification Chapter 17 Vehicle Navigation Chapter 18 Computational Biology Chapter 19 Robotics by Sven Koenig