Habitual control of goal selection in humans

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 contro...

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Veröffentlicht in:Proceedings of the National Academy of Sciences - PNAS Jg. 112; H. 45; S. 13817
Hauptverfasser: Cushman, Fiery, Morris, Adam
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 10.11.2015
Schlagworte:
Algorithms
Choice Behavior - physiology
Goals
Habits
Humans
Learning - physiology
Logistic Models
Models, Psychological
Planning Techniques
planning
goal selection
habit
hierarchical control
reinforcement learning
ISSN:1091-6490, 1091-6490
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Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1091-6490
1091-6490
DOI:10.1073/pnas.1506367112