Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences

Abstract

Humans often make sub-optimal decisions, choosing options that are less advantageous than available alternatives. Using computational modeling of behavior, the authors demonstrate that such irrational choices can arise from context dependence in reinforcement learning.