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STOCHASTIC MATCHING AND THE VOLUNTARY NATURE OF CHOICE
Author(s) -
Neuringer Allen,
Jensen Greg,
Piff Paul
Publication year - 2007
Publication title -
journal of the experimental analysis of behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.75
H-Index - 61
eISSN - 1938-3711
pISSN - 0022-5002
DOI - 10.1901/jeab.2007.65-06
Subject(s) - volition (linguistics) , matching law , matching (statistics) , voluntary action , psychology , turnover , reinforcement , social psychology , task (project management) , cognitive psychology , probabilistic logic , relation (database) , function (biology) , computer science , artificial intelligence , statistics , mathematics , perception , philosophy , linguistics , management , database , neuroscience , evolutionary biology , economics , biology
Attempts to characterize voluntary behavior have been ongoing for thousands of years. We provide experimental evidence that judgments of volition are based upon distributions of responses in relation to obtained rewards. Participants watched as responses, said to be made by “actors,” appeared on a computer screen. The participant's task was to estimate how well each actor represented the voluntary choices emitted by a real person. In actuality, all actors' responses were generated by algorithms based on Baum's (1979) generalized matching function. We systematically varied the exponent values (sensitivity parameter) of these algorithms: some actors matched response proportions to received reinforcer proportions, others overmatched (predominantly chose the highest‐valued alternative), and yet others undermatched (chose relatively equally among the alternatives). In each of five experiments, we found that the matching actor's responses were judged most closely to approximate voluntary choice. We found also that judgments of high volition depended upon stochastic (or probabilistic) generation. Thus, stochastic responses that match reinforcer proportions best represent voluntary human choice.