Response time distributions in rapid chess: a large-scale decision making experiment

Sigman, Mariano; Etchemendy, Pablo Esteban; Slezak, Diego Fernández; Cecchi, Guillermo A.

doi:10.3389/fnins.2010.00060

Cited by 27 publications

(36 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2a). As observed in our previous work [22], decision times are shorter during the first and last stages of the game, caused by the standardized openings or time constraints of the endgame (see Fig. 2a).…”

Section: Resultssupporting

confidence: 72%

“…Decision-time distributions of strong and weak players are comparable, although stronger players make slightly slower moves during middle-game and faster during the opening and the end-game [22]. We reasoned that this subtle differences in RT distributions between strong and weak players may rely on different decision processes.…”

Section: Specificitymentioning

confidence: 91%

“…The advent of big data, however, has turned this difficulty on its head [21]. To examine our hypothesis, therefore, we capitalized on a vast corpus of decision-making obtained from on-line chess servers [22]. This database has several virtues: (1) in any given move, players have to opt among a large number of options [23], (2) options grow exponentially (three steps down on decision tree typically results in more than a billion alternatives) and hence the search process becomes rapidly intractable without heuristics, (3) as in real-life, in chess choices have to be made with a finite time budget (4) the quality of the decision-maker is particularly easy to calibrate in chess (players have an ELO which indicates the quality of their decisions), and (5) it contains detailed information about more than 1 billion decisions, a volume that would be unthinkable to reproduce in a classical laboratory setting.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An entropic barriers diffusion theory of decision-making in multiple alternative tasks

Slezak

Sigman²,

Cecchi³

2018

Preprint

Self Cite

View full text Add to dashboard Cite

We present a theory of decision-making in the presence of multiple choices that departs from traditional approaches by explicitly incorporating entropic barriers in a stochastic search process. We analyze response time data from an on-line repository of 15 million blitz chess games, and show that our model fits not just the mean and variance, but the entire response time distribution (over several response-time orders of magnitude) at every stage of the game. We apply the model to show that (a) higher cognitive expertise corresponds to the exploration of more complex solution spaces, and (b) reaction times of users at an on-line buying website can be similarly explained. Our model can be seen as a synergy between diffusion models used to model simple two-choice decision-making and planning agents in complex problem solving.

show abstract

Section: Resultssupporting

confidence: 72%

Section: Specificitymentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An entropic barriers diffusion theory of decision-making in multiple alternative tasks

Slezak

Sigman²,

Cecchi³

2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…In recent years the scope of statistical physics has been extended to other fields to study, for instance, how humans behave individually or collectively [1][2][3]. In particular, the struggle of humans when playing games with a well defined set of rules provides a convenient experimental setup to understand human behavior and decision making processes [4][5][6][7][8][9][10][11][12][13][14][15][16]. This is particularly convenient from the physics' point of view because, under the rules of a game, the variables of the behavior under study are highly constrained.…”

Section: Introductionmentioning

confidence: 99%

A Study of Memory Effects in a Chess Database

2016

View full text Add to dashboard Cite

A series of recent works studying a database of chronologically sorted chess games–containing 1.4 million games played by humans between 1998 and 2007– have shown that the popularity distribution of chess game-lines follows a Zipf’s law, and that time series inferred from the sequences of those game-lines exhibit long-range memory effects. The presence of Zipf’s law together with long-range memory effects was observed in several systems, however, the simultaneous emergence of these two phenomena were always studied separately up to now. In this work, by making use of a variant of the Yule-Simon preferential growth model, introduced by Cattuto et al., we provide an explanation for the simultaneous emergence of Zipf’s law and long-range correlations memory effects in a chess database. We find that Cattuto’s Model (CM) is able to reproduce both, Zipf’s law and the long-range correlations, including size-dependent scaling of the Hurst exponent for the corresponding time series. CM allows an explanation for the simultaneous emergence of these two phenomena via a preferential growth dynamics, including a memory kernel, in the popularity distribution of chess game-lines. This mechanism results in an aging process in the chess game-line choice as the database grows. Moreover, we find burstiness in the activity of subsets of the most active players, although the aggregated activity of the pool of players displays inter-event times without burstiness. We show that CM is not able to produce time series with bursty behavior providing evidence that burstiness is not required for the explanation of the long-range correlation effects in the chess database. Our results provide further evidence favoring the hypothesis that long-range correlations effects are a consequence of the aging of game-lines and not burstiness, and shed light on the mechanism that operates in the simultaneous emergence of Zipf’s law and long-range correlations in a community of chess players.

show abstract

“…Some games are complex systems which provide information about social and biological processes [1,2,3,4,5,6,7,8,9,10,11,12]. They are currently being studied because of the existence of very well documented registers of games which are useful for statistical analysis.…”

Section: Introductionmentioning

confidence: 99%

Memory and long-range correlations in chess games

Schaigorodsky

Perotti

Billoni

2014

Physica A: Statistical Mechanics and its Applications

View full text Add to dashboard Cite

In this paper we report the existence of long-range memory in the opening moves of a chronologically ordered set of chess games using an extensive chess database. We used two mapping rules to build discrete time series and analyzed them using two methods for detecting long-range correlations; rescaled range analysis and detrented fluctuation analysis. We found that long-range memory is related to the level of the players. When the database is filtered according to player levels we found differences in the persistence of the different subsets. For high level players, correlations are stronger at long time scales; whereas in intermediate and low level players they reach the maximum value at shorter time scales. This can be interpreted as a signature of the different strategies used by players with different levels of expertise. These results are robust against the assignation rules and the method employed in the analysis of the time series.Comment: 12 pages, 5 figures. Published in Physica

show abstract

Response time distributions in rapid chess: a large-scale decision making experiment

Cited by 27 publications

References 31 publications

An entropic barriers diffusion theory of decision-making in multiple alternative tasks

An entropic barriers diffusion theory of decision-making in multiple alternative tasks

A Study of Memory Effects in a Chess Database

Memory and long-range correlations in chess games

Contact Info

Product

Resources

About