Search methods in artificial intelligence

https://www.cambridge.org/core/books/search-methods-in-artificial-intelligence/F0F13F0F4AD2551378E970BDDB64C994

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.

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