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G.McC.: Intrinsic chess ratings (2011)
| Content Provider | CiteSeerX |
|---|---|
| Author | Regan, Kenneth W. Haworth, Guy Mcc |
| Description | This paper develops and tests formulas for representing play-ing strength at chess by the quality of moves played, rather than by the results of games. Intrinsic quality is estimated via evaluations given by computer chess programs run to high depth, ideally so that their playing strength is sufficiently far ahead of the best human players as to be a ‘relatively om-niscient ’ guide. Several formulas, each having intrinsic skill parameters s for sensitivity and c for consistency, are argued theoretically and tested by regression on large sets of tourna-ment games played by humans of varying strength as mea-sured by the internationally standard Elo rating system. This establishes a correspondence between Elo rating and the pa-rameters. A smooth correspondence is shown between statis-tical results and the century points on the Elo scale, and rat-ings are shown to have stayed quite constant over time. That is, there has been little or no ‘rating inflation’. The theory and empirical results are transferable to other rational-choice settings in which the alternatives have well-defined utilities, but in which complexity and bounded information constrain the perception of the utility values. |
| File Format | |
| Language | English |
| Publisher Date | 2011-01-01 |
| Publisher Institution | AAAI-11, the 25th AAAI Conference on Artificial Intelligence |
| Access Restriction | Open |
| Subject Keyword | Smooth Correspondence Well-defined Utility Computer Chess Program Play-ing Strength Statis-tical Result Utility Value Intrinsic Quality Century Point Playing Strength Elo Scale Intrinsic Chess Rating Om-niscient Guide Elo Rating Rating Inflation Several Formula High Depth Tourna-ment Game Rational-choice Setting Human Player Intrinsic Skill Parameter Large Set Information Constrain G.m Cc Standard Elo Rating System Empirical Result |
| Content Type | Text |
| Resource Type | Article |
