Ten years of intensive effort on computer chess have produced notable progress. Although the background information and technical details that were written in 1975 for the first edition of this book are still valid in most essential points, hardware and software refinements have had a major impact on the effectiveness of these ideas. The current crop of chess machines are performing at unexpectedly high levels. The approach epitomized by the series of programs developed by David Slate and Larry Atkin at Northwestern in the middle 1970s (i. e., a sophisticated search algorithm using very little chess knowledge) was expected to reach an asymptbtic level of performance no higher than that of a class A player (USCF rating between 1800 and 2000). This perspective was argued quite vigorously by Eliot Hearst in Chapter 8 of the first edition and was held at that time by many chess experts. Subsequent events have clearly demonstrated that the asymptotic performance level for this type of pro gram it at least as high as the master level (USCF rating between 2200 and 2400). Current discussions now focus upon whether the earlier reser vations were wrong in principle or simply underestimated the asymptote. If there is a real barrier which will prevent this type of program from attaining a world championship level of performance, it is not evident from the steady progress which has been observed during the last decade."

Chess Skill in Man and Machine

This chapter provides an overview of research into chess expertise. After an historical background and a brief description of the game and the rating system, it discusses the information processes enabling players to choose good moves, and in particular the trade-offs between knowledge and search. Other topics include blindfold chess, talent, and the role of deliberate practice and tournament experience.

Expertise in chess

: Selected recent developments and promising directions for improving the quality of models of human performance in synthetic environments are summarized, beginning with the potential uses and goals for behavioral models. The focus is on providing more complete performance, better integration of the models with synthetic environments and with each other (reusability), and improved usability of the models. Within this context, relevant, current work related to modeling is reviewed, such as cognitive modeling of emotion, advanced techniques for testing and building models of behavior, new cognitive architectures including hybrid architectures, and agent and Belief, Desires and Intentions (BDI) architectures. A list of projects with high payoff for modeling human performance in synthetic environments is provided as a conclusion.

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Jacques Pitrat

Papers

A chess combination program which uses plans