Search Methods in Artificial Intelligence

This book is a complete guide to search methods in artificial intelligence, for students pursuing courses in computer science.

Deepak Khemani (Author)

9781009284325, Cambridge University Press

Hardback, published 24 October 2024

480 pages
24.8 x 19 x 2.6 cm, 0.93 kg

This book is designed to provide in-depth knowledge on how search plays a fundamental role in problem solving. Meant for undergraduate and graduate students pursuing courses in computer science and artificial intelligence, it covers a wide spectrum of search methods. Readers will be able to begin with simple approaches and gradually progress to more complex algorithms applied to a variety of problems. It demonstrates that search is all pervasive in artificial intelligence and equips the reader with the relevant skills. The text starts with an introduction to intelligent agents and search spaces. Basic search algorithms like depth first search and breadth first search are the starting points. Then, it proceeds to discuss heuristic search algorithms, stochastic local search, algorithm A*, and problem decomposition. It also examines how search is used in playing board games, deduction in logic and automated planning. The book concludes with a coverage on constraint satisfaction.

Preface
Chapter 1: Introduction
Chapter 2: Search Spaces
Chapter 3: Blind Search
Chapter 4: Heuristic Search
Chapter 5: Stochastic Local Search
Chapter 6: Algorithm A* and Variations
Chapter 7: Problem Decomposition
Chapter 8: Chess and Other Games
Chapter 9: Automated Planning
Chapter 10: Deduction as Search
Chapter 11: Search in Machine Learning
Chapter 12: Constraint Satisfaction
References
Appendix
Index.

Subject Areas: Artificial intelligence [UYQ]