Theory of reinforcement schedules

Model-based estimates for operant selection

We present a new methodology to partition different sources of behavior change within a selectionist framework based on the Price equation-the multilevel model of behavioral selection. The multilevel model of behavioral selection provides a theoretical background to describe behavior change in terms of operant selection. Operant selection is formally captured by the covariance-based law of effect and accounts for all changes in individual behavior that involve a covariance between behavior and predictors of evolutionary fitness (e.g., food). In this article, we show how the covariance-based law of effect may be applied to different components of operant behavior (e.g., allocation, speed, and accuracy of responding), thereby providing quantitative estimates for various selection effects affecting behavior change using data from a published learning experiment with pigeons.

Hyperbolae

Hyperbolic relations between independent and dependent variables are ubiquitous in the experimental analysis of behavior, mentioned in over 150 articles in the Journal of the Experimental Analysis of Behavior. There are two principal forms of hyperbolae: The first describes the relation between response rate and reinforcement rate on variable-interval schedules of reinforcement; it rises asymptotically toward a maximum. The second describes the relation between the current equivalent value of an incentive and its delay or (im)probability; it falls from a maximum toward an asymptote of 0. Where do these come from? What do their parameters mean? How are they related? This article answers the first two questions and addresses the last.