Modeling and quantifying resurgence in the Evolutionary Theory of Behavior Dynamics

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McDowell's Evolutionary Theory of Behavior Dynamics (ETBD) has been shown to model a wide range of live organism behavior with excellent descriptive accuracy. Recently, artificial organisms (AOs) animated by the ETBD were shown to replicate the resurgence of a target response following downshifts in the density of reinforcement for an alternative response and across repeated iterations of the traditional three-phase resurgence paradigm in a manner commensurate with nonhuman subjects. In the current investigation, we successfully replicated an additional study that used this traditional three-phase resurgence paradigm with human participants. We fitted two models based on the Resurgence as Choice (RaC) theory to the data generated by the AOs. Because the models had varying numbers of free parameters, we used an information-theoretic approach to compare the models against one another. We found that a version of the Resurgence as Choice in Context model that incorporates aspects of Davison and colleague's Contingency Discriminability Model provided the best description of the resurgence data emitted by the AOs when accounting for the models’ complexity. Last, we discuss considerations when developing and testing new quantitative models of resurgence that account for the ever-growing literature of resurgence.

Original languageEnglish (US)
Article number104860
JournalBehavioural Processes
StatePublished - May 2023


  • Evolutionary Theory of Behavior Dynamics
  • Information theory
  • Model fitting
  • Resurgence

ASJC Scopus subject areas

  • Animal Science and Zoology
  • Behavioral Neuroscience


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