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FEEDBACK FUNCTIONS, OPTIMIZATION, AND THE RELATION OF RESPONSE RATE TO REINFORCER RATE
Author(s) -
Soto Paul L.,
McDowell Jack J.,
Dallery Jesse
Publication year - 2006
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.2006.13-05
Subject(s) - reinforcement , lever , schedule , operant conditioning , matching law , quadratic function , function (biology) , control theory (sociology) , statistics , quadratic equation , psychology , mathematics , social psychology , computer science , control (management) , artificial intelligence , physics , geometry , quantum mechanics , evolutionary biology , biology , operating system
The present experiment arranged a series of inverted U‐shaped feedback functions relating reinforcer rate to response rate to test whether responding was consistent with an optimization account or with a one‐to‐one relation of response rate to reinforcer rate such as linear system theory's rate equation or Herrnstein's hyperbola. Reinforcer rate was arranged according to a quadratic equation with a maximum at a unique response rate. The experiment consisted of two phases, during which 6 Long Evans rats lever pressed for food. In the first phase of the experiment, the rats responded on six fixed‐interval‐plus‐quadratic‐feedback schedules, and in the second phase the rats responded on three variable‐interval‐plus‐quadratic‐feedback schedules. Responding in both phases was inconsistent with a one‐to‐one relation of response rate to reinforcer rate. Instead, different response rates were obtained at equivalent reinforcer rates. Responding did vary directly with the vertex of the feedback function in both phases, a finding consistent with optimization of reinforcer rate. The present results suggest that the feedback function relating reinforcer rate to response rate imposed by a reinforcement schedule can be an important determinant of behavior. Furthermore, the present experiment illustrates the benefit of arranging feedback functions to investigate assumptions about the variables that control schedule performance.