Abstract
Model-free learning enables an agent to make better decisions based on prior experience while representing only minimal knowledge about an environment’s structure. It is generally assumed that model-free state representations are based on outcome-relevant features of the environment. Here, we challenge this assumption by providing evidence that a putative model-free system assigns credit to task representations that are irrelevant to an outcome. We examined data from 769 individuals performing a well-described 2-step reward decision task where stimulus identity but not spatial-motor aspects of the task predicted reward. We show that participants assigned value to spatial-motor representations despite it being outcome irrelevant. Strikingly, spatial-motor value associations affected behavior across all outcome-relevant features and stages of the task, consistent with credit assignment to low-level state-independent task representations. Individual difference analyses suggested that the impact of spatial-motor value formation was attenuated for individuals who showed greater deployment of goal-directed (model-based) strategies. Our findings highlight a need for a reconsideration of how model-free representations are formed and regulated according to the structure of the environment.
Original language | English |
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Pages (from-to) | 15871-15876 |
Number of pages | 6 |
Journal | Proceedings of the National Academy of Sciences of the United States of America |
Volume | 116 |
Issue number | 32 |
DOIs | |
State | Published - 6 Aug 2019 |
Externally published | Yes |
Keywords
- Decision making
- Motor learning
- Reinforcement learning
ASJC Scopus subject areas
- General