Task complexity interacts with state-space uncertainty in the arbitration between model-based and model-free learning

Abstract

The brain dynamically arbitrates between two model-based and model-free reinforcement learning (RL). Here, the authors show that participants tended to increase model-based control in response to increasing task complexity, but resorted to model-free when both uncertainty and task complexity were high.