Flexible Decisions and Chess Expertise

Adjusting our behavior to the changing demands of the environment requires flexible decision mechanisms. In an analysis of more than 91,000 chess games, an original research effort now suggests that performance is correlated with a player's ability to adjust its decision criteria to meet the varying degrees of complexity observed throughout a match (Sigman et al., 2010). Chess has always captivated not only to those who play it, but also mathematicians and computer scientists who are often drawn to the challenge of designing artificial intelligence algorithms capable of matching or even surpassing human cognition (Shannon, 1950; Turing, 1950). Traditionally, those trying to understand the cognitive processes related to chess have brought players within laboratory settings that allow studying such things as eye movements and pattern recognition abilities (Chase and Simon, 1973; Charness et al., 2001). A new approach, however, has taken the study of chess and decision making to new level by realizing that the enormous databases generated by storing the thousands of games played online every day can help uncover subtle but insightful statistical trends (Blasius and Tönjes, 2009). Sigman and colleagues analyzed how response time (RT) changed according to the number of moves played into the game. The resulting mean RT profile clearly showed that openings and endgames are played much faster than the middle game, a pattern that most chessists know from experience (see also Hyatt, 1984). This general trend was present among all contestants, but a revealing result emerged when the authors compared time usage of low (<1400) and high-rated (>1900) players: strong players spend even less time on the openings and endings, and invest significantly more time reflecting on middle game moves. The wider RT range of high-rated players suggested a more flexible policy of time management. Supporting this view, Sigman and collaborators found that, not only mean RT showed larger modulations throughout a match, but also the spread of the RT distributions for each move number was wider among strong players. But, what is the main factor shaping the general trend of slow moves at the middle, and fast ones at the opening and endgame? One possibility is that the time invested on a given move is determined by the complexity of the board position. Players intuitively know that position complexity grows as the match progresses from the opening into the middle game. To estimate how complexity changed as games unfolded, the authors came …