Article

Hierarchical Bayesian Models of Reinforcement Learning: Introduction and comparison to alternative methods

2020-10-20

Abstract excerpt

Reinforcement learning models have been used extensively to capture learning and decision-making processes in humans and other organisms. One essential goal of these computational models is the generalization to new sets of observations. Extracting parameters that can reliably predict out-of-sample data can be difficult, however. The use of prior distributions to regularize parameter estimates has been shown to he...

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Literature Corpus work: 4a7c64ed-2957-551c-b379-132d4e82cd78
DOI: 10.1101/2020.10.19.345512

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