title: Evolutionary game dynamics of controlled and automatic decision-making.
abstract: We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions in which having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and human cognition and suggest necessary conditions for the rise and fall of rationality.
authors.affiliation: Center for Applied Mathematics, Cornell University, Ithaca, New York 14853, USA.
authors.forename: Danielle F P
authors.initials: DF
authors.lastname: Toupo
authors.affiliation: Center for Applied Mathematics, Cornell University, Ithaca, New York 14853, USA.
authors.forename: Steven H
authors.initials: SH
authors.lastname: Strogatz
authors.affiliation: Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, New Jersey 08540, USA.
authors.forename: Jonathan D
authors.initials: JD
authors.lastname: Cohen
authors.affiliation: Department of Psychology and Department of Economics, Yale University, New Haven, Connecticut 06511, USA.
authors.forename: David G
authors.initials: DG
authors.lastname: Rand
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D032701:Biomimetics / Q000379:methods*; D003071:Cognition; D003657:Decision Making; D003661:Decision Support Techniques; D005716:Game Theory; D006801:Humans; D000069550:Machine Learning; D017711:Nonlinear Dynamics