A Theory of Heuristic Information in Game-Tree Search (Symbolic Computation)

Tzeng, Chun-Hung

ISBN 10: 3642648126 / ISBN 13: 9783642648120

Published by Springer, 2011

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Seller Inventory # ERICA79036426481266

Bibliographic Details

• Title: A Theory of Heuristic Information in Game-Tree Search (Symbolic Computation)
• Publisher: Springer
• Publication Date: 2011
• Language: English
• ISBN 10: 3642648126
• ISBN 13: 9783642648120
• Binding: Paperback
• Condition: Like New
• Book Type: book

About this title

Synopsis

Searching is an important process in most AI systems, especially in those AI production systems consisting of a global database, a set of production rules, and a control system. Because of the intractability of uninformed search procedures, the use of heuristic information is necessary in most searching processes of AI systems. This important concept of heuristic informatioD is the central topic of this book. We first use the 8-puzzle and the game tic-tac-toe (noughts and crosses) as examples to help our discussion. The 8-puzzle consists of eight numbered movable tiles set in a 3 x 3 frame. One cell of the frame is empty so that it is possible to move an adjacent numbered tile into the empty cell. Given two tile configurations, initial and goal, an 8-puzzle problem consists of changing the initial configuration into the goal configuration, as illustrated in Fig. 1.1. A solution to this problem is a sequence of moves leading from the initial configuration to the goal configuration, and an optimal solution is a solution having the smallest number of moves. Not all problems have solutions; for example, in Fig. 1.1, Problem 1 has many solutions while Problem 2 has no solution at all.

Product Description

A Theory of Heuristic Information in Game-tree Search This book presents the use of imperfect information (called heuristic information) in game-tree search. Its purpose is to investigate the theoretical background of the use of heuristic information in game-tree search. Computer programs playing games usually search the game-tree to a reasonable depth with a static evaluation function and make decisions based upon backed-up values. Since the information in either the backed-up values or the values returned directly by the static evaluation function is often imperfect, decision making is usually not optimal. Also, pathological cases show why intuition about game-tree search is not always correct. This book intr...