Search Methods in Artificial Intelligence
Seiten
2024
Cambridge University Press (Verlag)
978-1-009-28432-5 (ISBN)
Cambridge University Press (Verlag)
978-1-009-28432-5 (ISBN)
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 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.
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.
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.
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.
| Erscheinungsdatum | 01.11.2024 |
|---|---|
| Zusatzinfo | Worked examples or Exercises |
| Verlagsort | Cambridge |
| Sprache | englisch |
| Maße | 190 x 248 mm |
| Gewicht | 930 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| ISBN-10 | 1-009-28432-0 / 1009284320 |
| ISBN-13 | 978-1-009-28432-5 / 9781009284325 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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