Knowledge-Free and Learning-Based Methods in Intelligent Game Playing

First Edition. Hardcover. 9 1/2" X 6 1/2". xviii, 254pp. First edition, with full number line indicating first printing. Very mild shelf wear to covers and edges of paper over boards. Bumps to corners. Pages are clean and unmarked. Binding is firm, tight, and sound. ABOUT THIS BOOK: Humans and machines are very dfferent in their approaches to game playing. Humans use intuition, perception mechanisms, selective search, creativity, abstraction, heuristic abilities and other cognitive skills to compensate their (comparably) slow information processing speed, relatively low memory capacity, and limited search abilities. Machines, on the other hand, are extremely fast and infallible in calculations, capable of effective brute-force type search, use "unlimited" memory resources, but at the same time are poor at using reasoning-based approaches and abstraction-based methods. The above major discrepancies in the human and machine problem solving methods underlined the development of traditional machine game playing as being focused mainly on engineering advances rather than cognitive or psychological developments. In other words, as described by Winkler and F urnkranz [347, 348] with respect to chess, human and machine axes of game playing development are perpendicular, but the most interesting, most promising, and probably also most diffcult research area lies on the junction between human-compatible knowledge and machine compatible processing. I undoubtedly share this point of view and strongly believe that the future of machine game playing lies in implementation of human-type abilities (abstraction, intuition, creativity, selective attention, and others) while still taking advantage of intrinsic machine skills.(Publisher).