Search in Artificial Intelligence
By: edited by Laveen Kanal, Vipin Kumar
Contributors: Kumar, Vipin
Series: Symbolic Computation, Artificial Intelligence; Symbolic computation
Publisher: Springer New York
Published: 1988
Place of publication: New York, NY
Language: eng
Format: [electronic resource] /
Number of pages: 482
ISBN-13: 9781461387886
Description: This book brings together some new insights and recent developments on the topics of search procedures in Artificial Intelligence and the relationships among search methods in Artificial Intelligence, Operations Research, and Engineering. The purpose of the book is to present these new insights and recent developments in a manner accessible to students and professionals in Computer Science, Engineering, Operations Research, and Applied Mathematics. The articles should provide the reader with a broad view of recent developments on search in AI and some of the relationships among branch and bound, heuristic search, and dynamic programming. New models for discrete optimization problems, new results on the average case of complexity of the well known A* algorithm, new results on the conditions under which A* is optimal over other search algorithms, use of different sources of knowledge in heuristic search, new results on the constraint satisfaction problem, and a result showing the minimax back up rule does not do as well as the product rule in some real games.