Habitual control of goal selection in humans
Abstract
Human cognition makes widespread use of goal-directed planning. However, exhaustive forward planning for tasks of real-world complexity is prohibitively computationally demanding. Much research aims to find efficient mechanisms for approximate planning. We describe an approach to this problem that exploits the computational efficiency of habit learning to select goal states that are subsequently used in planning. We also provide experimental evidence that humans implement this approach. Our findings illuminate the basis of learning and choice in humans, demonstrate an integration between mechanisms of habitual and planned control, and contribute to the development of computationally tractable planning algorithms.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 12, 2015
- Source ID
- 10.1073/pnas.1506367112
Entities
People
- Adam Morris
- Fiery Cushman
Organizations
- Harvard University
- Office of Naval Research