Nonlinear influence of reward volatility on arbitration between multiple learning strategies reflects cost-benefit optimization
Taiji Yamada, Kazuyuki Samejima
This study shows that reward volatility nonlinearly affects the balance between model-free and model-based learning strategies, with model-based learning being most effective at intermediate volatility levels.
bioRxiv · Jun 19, 2026 · PreprintAnimal Behavior & Cognition