Reinforcement learning in professional basketball players

פרסום מחקרי: פרסום בכתב עתמאמרביקורת עמיתים

תקציר

Reinforcement learning in complex natural environments is a challenging task because the agent should generalize from the outcomes of actions taken in one state of the world to future actions in different states of the world. The extent to which human experts find the proper level of generalization is unclear. Here we show, using the sequences of field goal attempts made by professional basketball players, that the outcome of even a single field goal attempt has a considerable effect on the rate of subsequent 3 point shot attempts, in line with standard models of reinforcement learning. However, this change in behaviour is associated with negative correlations between the outcomes of successive field goal attempts. These results indicate that despite years of experience and high motivation, professional players overgeneralize from the outcomes of their most recent actions, which leads to decreased performance.

שפה מקוריתאנגלית אמריקאית
מספר המאמר569
כתב עתNature Communications
כרך2
מספר גיליון1
מזהי עצם דיגיטלי (DOIs)
סטטוס פרסוםפורסם - 2011

ASJC Scopus subject areas

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  • ???subjectarea.asjc.1300.1300???
  • ???subjectarea.asjc.3100.3100???

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