An opponent striatal circuit for distributional reinforcement learning
Adam S. Lowet,
Qiao Zheng,
Melissa Meng
et al.
Abstract:Machine learning research has achieved large performance gains on a wide range of tasks by expanding the learning target from mean rewards to entire probability distributions of rewards — an approach known as distributional reinforcement learning (RL)1. The mesolimbic dopamine system is thought to underlie RL in the mammalian brain by updating a representation of mean value in the striatum2,3, but little is known about whether, where, and how neurons in this circuit encode information about higher-order moment… Show more
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