From this he derived a probabilistic model for each player, and used it to compute the win/draw/lose probability for any given match between any two players. The assumption is that the engine is executing almost perfect moves.Īlliot has evaluated 26,000 games played by World Champions since Steinitz, estimating the probability of their making a mistake – and the magnitude of the mistake – for each position in their games. He does this by comparing the moves of World Champions with those of a strong chess engine – the program Stockfish running on a supercomputer. Now computer scientist and AI researcher Jean-Marc Alliot of the Institut de Recherche en Informatique de Toulouse has come up with a new system (and reported on it in the journal of the International Computer Games Association) that does exactly that: rank players by evaluating the quality of their actual moves. However, the Elo system does not take into account the the quality of the moves played during a game and is therefore unable to reliably rank players who have played at different periods in history. If a player performs better or worse than predicted then rating points are added to or deducted from his rating. Designed by the Hungarian physics professor and chess master Árpád Imre Élo in 1970 the system is used to predict the probability of rated players winning or losing their games against another rated players. ![]() The Elo rating system in chess, well known to all of us, is based on the results of players against each other.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |