When artificial intelligence evaluates chess champions

The ELO system, which most chess federations use today, ranks players by the results of their games. Although simple and efficient, it overlooks relevant criteria such as the quality of the moves players actually make. To overcome these limitations, Jean-Marc Alliot of the Institut de recherche en informatique de Toulouse (IRIT - CNRS/INP Toulouse/Université Toulouse Paul Sabatier/Université Toulouse Jean Jaurès/Université Toulouse Capitole) demonstrates a new system, published on 24 april 2017 in the International Computer Games Association Journal. Since the 1970s, the system designed by the Hungarian, Arpad Elo, has been ranking chess players according to the result of their games. The best players have the highest ranking, and the difference in ELO points between two players predicts the probability of either player winning a given game. If players perform better or worse than predicted, they either gain or lose points accordingly. This method does not take into account the quality of the moves played during a game and is therefore unable to reliably rank players who have played at different periods.