A Test of Gibbon's Feedforward Model of Matching

Abstract Gibbon (1995) elaborated an ingenious model of matching, a feedforward model that is consistent with Heyman's (1982) suggestion that matching behavior does not depend on selection by consequences. Most models (for example, Herrnstein & Vaughan, 1980) have been feedback models, built on the law of effect. Measurements of how rapidly rats adjust to changes in the relative rates of brain stimulation reward on concurrent random interval schedules imply a feedforward process. The adjustments are, however, too fast to be consistent with Gibbon's model.

[1]  J. Stevens,et al.  Animal Intelligence , 1883, Nature.

[2]  P. L. Brown,et al.  Auto-shaping of the pigeon's key-peck. , 1968, Journal of the experimental analysis of behavior.

[3]  D. R. Williams,et al.  Auto-maintenance in the pigeon: sustained pecking despite contingent non-reinforcement. , 1969, Journal of the experimental analysis of behavior.

[4]  W M Baum,et al.  Choice as time allocation. , 1969, Journal of the experimental analysis of behavior.

[5]  S. Winokur,et al.  Controls for and constraints on auto-shaping. , 1973, Journal of the experimental analysis of behavior.

[6]  G. D. Steinhauer,et al.  A procedure for autoshaping the pigeon's key peck to an auditory stimulus. , 1977, Journal of the experimental analysis of behavior.

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

[8]  J. Staddon,et al.  Limits to action, the allocation of individual behavior , 1982 .

[9]  S. Lea,et al.  The Integration of Reinforcements over Time , 1984, Annals of the New York Academy of Sciences.

[10]  J. Gibbon,et al.  Timing and time perception. , 1984, Annals of the New York Academy of Sciences.

[11]  J. Gibbon,et al.  Cognition and behavior in studies of choice , 1986 .

[12]  R. Herrnstein,et al.  Melioration: A Theory of Distributed Choice , 1991 .

[13]  J. Gibbon Dynamics of time matching: Arousal makes better seem worse , 1995, Psychonomic bulletin & review.

[14]  P. Dayan,et al.  A framework for mesencephalic dopamine systems based on predictive Hebbian learning , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[15]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[16]  Andrew G. Barto,et al.  Reinforcement learning , 1998 .

[17]  I. P. L McLaren Animal Learning and Cognition: A neural network approach , 1998, Trends in Cognitive Sciences.

[18]  C. Gallistel,et al.  The rat approximates an ideal detector of changes in rates of reward: implications for the law of effect. , 2001, Journal of experimental psychology. Animal behavior processes.