title: Habitual control of goal selection in humans.
abstract: Humans choose actions based on both habit and planning. Habitual control is computationally frugal but adapts slowly to novel circumstances, whereas planning is computationally expensive but can adapt swiftly. Current research emphasizes the competition between habits and plans for behavioral control, yet many complex tasks instead favor their integration. We consider a hierarchical architecture that exploits the computational efficiency of habitual control to select goals while preserving the flexibility of planning to achieve those goals. We formalize this mechanism in a reinforcement learning setting, illustrate its costs and benefits, and experimentally demonstrate its spontaneous application in a sequential decision-making task.
authors.affiliation: Department of Psychology, Harvard University, Cambridge, MA 02138 cushman@fas.harvard.edu.
authors.forename: Fiery
authors.identifier: http://orcid.org/0000-0002-6929-9982
authors.initials: F
authors.lastname: Cushman
authors.affiliation: Department of Psychology, Harvard University, Cambridge, MA 02138.
authors.forename: Adam
authors.initials: A
authors.lastname: Morris
mesh_terms: D000465:Algorithms; D002755:Choice Behavior / Q000502:physiology; D006040:Goals; D006184:Habits; D006801:Humans; D007858:Learning / Q000502:physiology; D016015:Logistic Models; D008960:Models, Psychological; D010934:Planning Techniques
keywords: goal selection; habit; hierarchical control; planning; reinforcement learning