ArticleJournal of applied behavior analysis2020
Application of the generalized matching law to chess openings: A gambit analysis.
Article in Journal of applied behavior analysis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Within-Session Matching Analyses to Quantify the Effects of Individualized Preferred Interactions on Social Time Allocation.Behavioral sciences (Basel, Switzerland) · 2026Article
- Undermatching Is a Consequence of Policy Compression.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- ScalingPerspectives on behavior science · 2021Article
- Entropy-based metrics for predicting choice behavior based on local response to reward.Nature communications · 2021Article
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2 authors.
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Abstract
During the opening moves of a chess game, a player (typically White) may offer a number of gambits, which involve sacrificing a chess piece for an opponent for capture to achieve long-term positional advantages. One of the most popular gambits is called the Queen's Gambit and involves White offering a pawn to Black, which will open a lane for White's Queen if accepted by Black. In the present study, the generalized matching law (GML) was applied to chess openings involving the Queen's Gambit using over 71,000 archived chess games. Overall, chess players' opening moves involving the Queen's Gambit exhibited orderly matching as predicted by the GML, and the GML accounted for more variance in players' chess decision making as their relative playing experience increased. This study provides support for the generality of the GML and its application to complex operant behavior outside of laboratory contexts.
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