In search of the feedback function for variable-interval schedules.

Finding a theoretically sound feedback function for variable-interval schedules remains an important unsolved problem. It is important because interval schedules model a significant feature of the world: the dependence of reinforcement on factors beyond the organism's control. The problem remains unsolved because no feedback function yet proposed satisfies all the theoretical and empirical requirements. Previous suggestions that succeed in fitting data fail theoretically because they violate a newly recognized theoretical requirement: The slope of the function must approach or equal 1.0 at the origin. A function is presented that satisfies all requirements but lacks any theoretical justification. This function and two suggested by Prelec and Herrnstein (1978) and Nevin and Baum (1980) are evaluated against several sets of data. All three fitted the data well. The success of the two theoretically incorrect functions raises an empirical puzzle: Low rates of reinforcement are coupled with response rates that seem anomalously high. It remains to be discovered what this reflects about the temporal patterning of operant behavior at low reinforcement rates. A theoretically and empirically correct function derived from basic assumptions about operant behavior also remains to be discovered.

[1]  J. Staddon CHAPTER 4 – Optimality Analyses of Operant Behavior and Their Relation to Optimal Foraging1 , 1980 .

[2]  W M Baum,et al.  Feedback functions for variable-interval reinforcement. , 1980, Journal of the experimental analysis of behavior.

[3]  J Myerson,et al.  Choice in transition: A comparison of melioration and the kinetic model. , 1988, Journal of the experimental analysis of behavior.

[4]  Drazen Prelec,et al.  Feedback functions for reinforcement: A paradigmatic experiment , 1978 .

[5]  J J McDowell,et al.  A multivariate rate equation for variable-interval performance. , 1979, Journal of the experimental analysis of behavior.

[6]  B A Schneider,et al.  A two-state analysis of fixed-interval responding in the pigeon. , 1969, Journal of the experimental analysis of behavior.

[7]  J. J. McDowell,et al.  The linear system theory's account of behavior maintained by variable-ratio schedules. , 1988, Journal of the experimental analysis of behavior.

[8]  W M Baum,et al.  Optimization and the matching law as accounts of instrumental behavior. , 1981, Journal of the experimental analysis of behavior.

[9]  W M Baum,et al.  The correlation-based law of effect. , 1973, Journal of the experimental analysis of behavior.

[10]  D S Blough,et al.  Interresponse time as a function of continuous variables: a new method and some data. , 1963, Journal of the experimental analysis of behavior.

[11]  W. Baum,et al.  Time-based and count-based measurement of preference. , 1976, Journal of the experimental analysis of behavior.

[12]  J E Staddon,et al.  Quasi-dynamic choice models: Melioration and ratio invariance. , 1988, Journal of the experimental analysis of behavior.

[13]  J. Kagel,et al.  Maximization theory in behavioral psychology , 1981, Behavioral and Brain Sciences.

[14]  W. Palya Dynamics in the fine structure of schedule-controlled behavior. , 1992, Journal of the experimental analysis of behavior.

[15]  F. Mcsweeney Concurrent schedule responding as a function of body weight , 1975 .

[16]  H. Rachlin,et al.  Effects of alternative reinforcement: does the source matter? , 1972, Journal of the experimental analysis of behavior.

[17]  Ronald E. Schaub Analyses of Interresponse Times with Small Class Intervals , 1967 .

[18]  H. Rachlin A molar theory of reinforcement schedules. , 1978, Journal of the experimental analysis of behavior.

[19]  W M Baum,et al.  Quantitative Prediction and Molar Description of the Environment , 1989, The Behavior analyst.

[20]  R. Herrnstein,et al.  CHAPTER 5 – Melioration and Behavioral Allocation1 , 1980 .