This comprehensive book is aimed at undergraduate and graduate students pursuing courses in computer science and artificial intelligence. It comprises detailed descriptions of a variety of search methods with examples and illustrations. It begins with simple approaches and progresses to more complex algorithms applied to problems.
This comprehensive book is aimed at undergraduate and graduate students pursuing courses in computer science and artificial intelligence. It comprises detailed descriptions of a variety of search methods with examples and illustrations. It begins with simple approaches and progresses to more complex algorithms applied to problems.
Deepak Khemani is a professor at IIT Madras. He has been working in AI for four decades, with a focus on knowledge representation and problem-solving. He is the author of the textbook, A First Course in Artificial Intelligence (2008), and has three popular online courses on Swayam.
Inhaltsangabe
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.