A New Method to Quantify the Causal Effects of Reinforcement in Terms of Behavioral 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 (MLBS). The MLBS 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 (CLOE) 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 CLOE 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 in pigeons.