Reinforcement learning: The Good, The Bad and The Ugly

Peter Dayan; Yael Niv

doi:10.1016/j.conb.2008.08.003

Reinforcement learning: The Good, The Bad and The Ugly

Peter Dayan, Yael Niv

Research output: Contribution to journal › Review article › peer-review

488 Scopus citations

Abstract

Reinforcement learning provides both qualitative and quantitative frameworks for understanding and modeling adaptive decision-making in the face of rewards and punishments. Here we review the latest dispatches from the forefront of this field, and map out some of the territories where lie monsters.

Original language	English (US)
Pages (from-to)	185-196
Number of pages	12
Journal	Current Opinion in Neurobiology
Volume	18
Issue number	2
DOIs	https://doi.org/10.1016/j.conb.2008.08.003
State	Published - Apr 2008

All Science Journal Classification (ASJC) codes

General Neuroscience

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10.1016/j.conb.2008.08.003

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abstract = "Reinforcement learning provides both qualitative and quantitative frameworks for understanding and modeling adaptive decision-making in the face of rewards and punishments. Here we review the latest dispatches from the forefront of this field, and map out some of the territories where lie monsters.",

author = "Peter Dayan and Yael Niv",

note = "Funding Information: We are very grateful to Peter Bossaerts, Nathaniel Daw, Michael Frank, Russell Poldrack, Daniel Salzman, Ben Seymour and Wako Yoshida for their helpful comments on a previous version of this manuscript. PD is funded by the Gatsby Charitable Foundation; YN is funded by the Human Frontiers Science Program.",

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Reinforcement learning: The Good, The Bad and The Ugly

Abstract

All Science Journal Classification (ASJC) codes

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