Adaptive integration of model-based and model-free strategies in human reinforcement learning of reachable space
Tianyao Zhu, Rohaan Syan, Shrika Vejandla, Jason P. Gallivan, Daniel M. Wolpert, John Randall Flanagan
This study shows humans adaptively use model-based and model-free strategies in learning to reach around obstacles in reachable space, with increased model-free reliance as learning progresses.
bioRxiv · Mar 4, 2026 · PreprintNeuroscience