Michael Davison

Demarcated response sequences and generalised matching

The generalised matching law was applied for the first time to sequences of responses. Pigeons responded on dependently arranged two-operandum concurrent schedules in which all four possible two-response sequences on these operanda were demarcated and reinforced. Reinforcer rates for the sequences were varied over a wide range, including extinction. Sequences of responses, rather than individual responses, followed the generalised matching law. We compared single-sensitivity and multiple-sensitivity versions of the generalised matching law. The multiple sensitivities were not significantly different from each other, so the single-sensitivity model provided the more efficient fit. As in previous research, responding was biased against the emission of sequences that required changeovers.

Four-alternative choice violates the constant-ratio rule

Six pigeons responded on a four-key concurrent variable-interval schedule in which a 27:9:3:1 distribution of reinforcers between the keys changed every 10 reinforcers. Their behaviour quickly came under the control of this changing four-way reinforcer ratio. However, preference between a pair of keys depended not only on the relative reinforcer rates on those keys, but also on the absolute levels of those rates. This contradicts the constant-ratio rule that underpins the matching approach to choice, but is predicted by a contingency-discriminability model that assumes that organisms may occasionally misattribute reinforcers to a response that did not produce them. Reinforcers produced strong preference pulses, or transient increases in responding on the just-reinforced key. Despite accurate tracking of the reinforcer ratio, reinforcers obtained late in components and from leaner keys still produced strong pulses, suggesting both extended and local control of behaviour. Patterns of switching between keys were graded and similarly controlled by the reinforcer rates on each key. Whether considered in terms of switching, local preference pulses, or extended preference, behaviour was controlled by a rapidly changing four-way reinforcer ratio in a graduated, continuous manner that is unlikely to be explained by a simple heuristic such as fix-and-sample.

THE DYNAMICS OF THE LAW OF EFFECT: A COMPARISON OF MODELS

Dynamical models based on three steady-state equations for the law of effect were constructed under the assumption that behavior changes in proportion to the difference between current behavior and the equilibrium implied by current reinforcer rates. A comparison of dynamical models showed that a model based on Navakatikyans (2007) two-component functions law-of-effect equations performed better than models based on Herrnsteins (1970) and Davison and Hunters (1976) equations. Navakatikyans model successfully described the behavioral dynamics in schedules with negative-slope feedback functions, concurrent variable-ratio schedules, Vaughans (1981) melioration experiment, and experiments that arranged equal, and constant-ratio unequal, local reinforcer rates.