Chess endgame tables should provide efficiently the value and depth of any required position during play. The indexing of an endgame's positions is crucial to meeting this objective. This paper updates Heinz' previous review of approaches to indexing and describes the latest approach by the first and third authors.Heinz' and Nalimov's endgame tables (EGTs) encompass the en passant rule and have the most compact index schemes to date. Nalimov's EGTs, to the Distance-to-Mate (DTM) metric, require only 30.6 × 10 9 elements in total for all the 3-to-5-man endgames and are individually more compact than previous tables. His new index scheme has proved itself while generating the tables and in the 1999 World Computer Chess Championship where many of the top programs used the new suite of EGTs. 1.Table 2, which includes the work of Wirth (1999), elicits these constraints and defines which of them have, in effect if not literally, been used by the EGT authors. The list below indicates that Edwards constrains the possible positions the least and Nalimov constrains them the most. For this reason, Edwards' index ranges are the largest and Nalimov's are the smallest. Heinz' EGTs made savings on the indexes of Thompson and Edwards which increase with the number of men, e.g., 3.13% for KxK, 7.67% for KxKy and 13.44% for KxyKz relative to Thompson's indexes.The next subsections explain the rationale for three of the constraints. 1

A reference model of fallible endgame play is defined in terms of a spectrum of endgame players whose play ranges in competence from the optimal to the anti-optimal choice of move. They may be used as suitably skilled practice partners, to assess a player, to differentiate between otherwise equi-optimal moves, to promote or expedite a game result, to run Monte-Carlo simulations, and to identify the difficulty of a position or a whole endgame.

Abstract-Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess. Bayesian methods are used to infer the distribution of players' skill levels from the moves they play rather than from their competitive results. The approach is used on large sets of games by players across a broad FIDE Elo range, and is in principle applicable to any scenario where high-value decisions are being made under pressure.

Abstract. This paper studies the population of chess players and the distribution of their performances measured by Elo ratings and by computer analysis of moves. Evidence that ratings have remained stable since the inception of the Elo system in the 1970's is given in several forms: by showing that the population of strong players fits a simple logistic-curve model without inflation, by plotting players' average error against the FIDE category of tournaments over time, and by skill parameters from a model that employs computer analysis keeping a nearly constant relation to Elo rating across that time. The distribution of the model's Intrinsic Performance Ratings can hence be used to compare populations that have limited interaction, such as between players in a national chess federation and FIDE, and ascertain relative drift in their respective rating systems.Note.

Abstract. Evaluating agents in decision-making applications requires assessing their skill and predicting their behaviour. Both are well developed in Poker-like situations, but less so in more complex game and model domains. This paper addresses both tasks by using Bayesian inference in a benchmark space of reference agents. The concepts are explained and demonstrated using the game of chess but the model applies generically to any domain with quantifiable options and fallible choice. Demonstration applications address questions frequently asked by the chess community regarding the stability of the rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The last include alleged under-performance, fabrication of tournament results, and clandestine use of computer advice during competition. Beyond the model world of games, the aim is to improve fallible human performance in complex, high-value tasks.