Abstract
Rapid reacquisition refers to the recurrence of a previously eliminated behavior following the response-dependent reintroduction of the reinforcer that originally maintained it. Woods and Bouton (2007) demonstrated that rapid reacquisition was attenuated when behavior was decelerated using intermittent reinforcement rather than extinction-a finding attributed to the reduced discriminability of reinforcer reintroduction under intermittent schedules. The present study used artificial organisms (AOs) animated by the Evolutionary Theory of Behavior Dynamics (ETBD) to evaluate the extent to which rapid reacquisition and its mitigation can be captured within a computational framework. AOs with phenotypes characterized by a high sensitivity to environmental contingencies exhibited reduced reacquisition of the target response following intermittent reinforcement compared to extinction, replicating prior findings. In contrast, AOs with diminished sensitivity to environmental changes showed little difference in reacquisition across response elimination conditions; instead, their relapse was primarily driven by the density of reinforcement in the reacquisition challenge condition. These findings revealed that susceptibility to disruption varied systematically with mutation rate, offering a computational perspective on how reinforcement sensitivity modulates behavioral persistence. These findings suggest that the impact of reinforcement history on relapse is phenotype-dependent and potentially shaped by operant variability. This study is the first to demonstrate rapid reacquisition using the ETBD and provides a foundation for future theoretical and translational investigations of relapse and resistance to change.