Habitual control of goal selection in humans

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 112; no. 45; pp. 13817 - 13822
• Main Authors: Cushman, Fiery, Morris, Adam
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 10.11.2015; National Acad Sciences
• Series: From the Cover
• Subjects: Algorithms; Choice Behavior - physiology; Decision making; Goals; Habits; Human subjects; Humans; Learning; Learning - physiology; Logistic Models; Models, Psychological; Objectives; Planning; Planning Techniques; Social Sciences; planning; goal selection; habit; hierarchical control; reinforcement learning
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.1506367112

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, yetmany 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.