Modeling sensory-motor decisions in natural behavior.
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ABSTRACT:
SUBMITTER: Zhang R
PROVIDER: S-EPMC6219815 | biostudies-literature | 2018 Oct
REPOSITORIES: biostudies-literature
Publications
Modeling sensory-motor decisions in natural behavior.
Zhang Ruohan R Zhang Shun S Tong Matthew H MH Cui Yuchen Y Rothkopf Constantin A CA Ballard Dana H DH Hayhoe Mary M MM
PLoS computational biology 20181025 10
Although a standard reinforcement learning model can capture many aspects of reward-seeking behaviors, it may not be practical for modeling human natural behaviors because of the richness of dynamic environments and limitations in cognitive resources. We propose a modular reinforcement learning model that addresses these factors. Based on this model, a modular inverse reinforcement learning algorithm is developed to estimate both the rewards and discount factors from human behavioral data, which ...[more]
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