![]() ![]() Hans Berliner, Gordon Goetsch, Murray Campbell, Carl Ebeling ( 1989).Alexander Szabo, Barbara Szabo ( 1988).Proceedings of the Fifth Annual International Conference of the Center, Elsevier Evolution, Games and Learning: Models for Adaptation in Machines and Nature. Doyne Farmer, Alan Lapedes, Norman Packard, Burton Wendroff (Ed.) ( 1986). Algorithmic Strategies for Improving the Performance of Game-Playing Programs. A Hypothesis Concerning the Strength of Chess Programs. How to Bracket the Truth in Playing Strength. Thesis, University of British Columbia, pdf Danny Kopec, Enrique Irazoqui, Ivan Bratko ( 1983).The Bratko-Kopec experiment: a comparison of human and computer performance in chess. A Test for Comparison of Human and Computer Performance in Chess. Six Test Problems for Chess Playing Machines. 77 » CAPS II, Chess Problems, Compositions and Studies The Rating of Chessplayers, Past and Present. Report CMU-CS-78-189, Carnegie Mellon University, CMU-CS-77 pdf » Tech Performance Analysis of the Technology Chess Program. Pawn Advantage, Win Percentage, and Elo.Matej Guid - Computer Analysis of World Chess Champions.Playing strength might be improved over the (playing) time due to learning algorithms. Time used is roughly proportional to the number of visited nodes of the common depth-first search inside an iterative deepening frame, which grows exponentially by its effective branching factor raised to the power of search depth. The strength of a chess program depends on many things, the quality and efficiency of the algorithms involved to determine the best move of a position, the balance of the so called search versus knowledge tradeoff to evaluate or compare leaf nodes of a search tree, how to shape that tree and to propagate a score up to the root, and time management, that is how to allocate time for searching a move under time control requirements. While relative playing strength of chess engines is not strictly transmissive over various time controls, the number of games played is more relevant than their duration, the todays de facto standard in measuring playing strength is parallel playing fast chess with (ultra) short time control, such as blitz, bullet or even lightning chess, as for instance used in the Fishtest framework of Stockfish. Players' rating depend on the ratings of their opponents, and the results scored against them. Performance isn't measured absolutely it is inferred from wins, losses, and draws against other players or engines. A statistical valid method to measure playing strength within a defined confidence interval is to play an appropriate huge number of games with both sides versus a wide range of different opponents with symmetric time constraints, and to apply match statistics.
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