This book is about problem-solving. In particular it is about heuristic state-space search for combinatorial optimization - one of the fundamental problems of computer science. Its two central themes are the average-case complexity of state-space search algorithms and the applications of the results notably to branch-and-bound techniques. These include best-first search, depth-first branch-and- bound, iterative deepening, recursive best-first search, and constant- space best-first search. Primarily written for researchers in computer science, the author presupposes a basic familiarity with complexity theory. In addition, it is assumed that the reader is familiar with the basic concepts of random variables and recursive functions. Two succesful applications are presented in depth: one is a set of state-space transformation methods which can be used to find approximate solutions qwuickly, and the second is a method called forward estimation for constructing more informative evaluation functions.
|Search for problem solving|
|Algorithms for state-space search|
|Complexity of state-space search|
|State-space transformation for approximate and flexible computation|
|Forward estimation for game search|
|A retrospective view|
|Table of Contents provided by Publisher. All Rights Reserved.|
Number Of Pages: 201
Published: 14th October 1999
Publisher: Springer-Verlag New York Inc.
Country of Publication: US
Dimensions (cm): 23.5 x 15.5 x 1.27
Weight (kg): 1.1