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A RUNS‐TEST ALGORITHM: CONTINGENT REINFORCEMENT AND RESPONSE RUN STRUCTURES
Author(s) -
Hachiga Yosuke,
Sakagami Takayuki
Publication year - 2010
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.2010.93-61
Subject(s) - reinforcement , blackout , cued speech , contingency , contingency table , stimulus (psychology) , computer science , test (biology) , statistics , artificial intelligence , psychology , mathematics , cognitive psychology , machine learning , social psychology , paleontology , biology , power (physics) , linguistics , physics , philosophy , electric power system , quantum mechanics
Four rats' choices between two levers were differentially reinforced using a runs‐test algorithm. On each trial, a runs‐test score was calculated based on the last 20 choices. In Experiment 1, the onset of stimulus lights cued when the runs score was smaller than criterion. Following cuing, the correct choice was occasionally reinforced with food, and the incorrect choice resulted in a blackout. Results indicated that this contingency reduced sequential dependencies among successive choice responses. With one exception, subjects' choice rule was well described as biased coin flipping. In Experiment 2, cuing was removed and the reinforcement criterion was changed to a percentile score based on the last 20 reinforced responses. The results replicated those of Experiment 1 in successfully eliminating first‐order dependencies in all subjects. For 2 subjects, choice allocation was approximately consistent with nonbiased coin flipping. These results suggest that sequential dependencies may be a function of reinforcement contingency.