Rapid chess: A massive-scale experiment

Abstract

The proliferation of chess servers on the Internet has turned active chess, blitz and lightning, into a vast cognitive phenomenon involving engaged participants. Here we use this large database of human decision making (rapid chess) as a privileged window to understand human cognition. FICS (Free Internet Chess Server), http://www.freechess.org/ is a free ICS-compatible server for playing chess games through Internet, with more than 300.000 registered users. Using this available chess server in the Internet, we constructed a massive decision-making database. This data includes thousands of million moves of chess games, with the estimated time of each one of them. In order to evaluate the goodness of moves, we used Crafty (an open-source chess engine) to analyse the score of the move. This process is compute expensive, so we parallelized the analysis on a Beowulf cluster. We studied the structure of the time players take to make a move during a game, and using parallelization we were able to analyse a huge amount of moves obtaining a quantification of the quality of the decision made in millions of instances. This approach allowed us to identify a number of statistical fingerprints that uniquely characterize the emergent structure of the game.