Distributional Reinforcement Learning in the Brain.
Distributional Reinforcement Learning in the Brain.
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DOI：
10.1016/j.tins.2020.09.004
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发表时间：
2020-12
影响因子：
15.9
通讯作者：
Uchida N
中科院分区：
文献类型：
--
作者：
Lowet AS;Zheng Q;Matias S;Drugowitsch J;Uchida N
Learning about rewards and punishments is critical for survival. Classical studies have demonstrated an impressive correspondence between the firing of dopamine neurons in the mammalian midbrain and the reward prediction errors of reinforcement learning algorithms, which express the difference between actual reward and predicted mean reward. However, it may be advantageous to learn not only the mean but also the complete distribution of potential rewards. Recent advances in machine learning have revealed a biologically plausible set of algorithms for reconstructing this reward distribution from experience. Here, we review the mathematical foundations of these algorithms as well as initial evidence for their neurobiological implementation. We conclude by highlighting outstanding questions regarding the circuit computation and behavioral readout of these distributional codes.
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DOI：
10.1523/jneurosci.3886-12.2013
发表时间：
2013-03-13
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Fiorillo CD;Yun SR;Song MR
通讯作者：
Song MR
影响因子：
9.2
作者：
Constantinople, Christine M.;Piet, Alex T.;Brody, Carlos D.
通讯作者：
Brody, Carlos D.
影响因子：
56.9
作者：
Bashivan, Pouya;Kar, Kohitij;DiCarlo, James J.
通讯作者：
DiCarlo, James J.
影响因子：
56.9
作者：
Fiorillo, CD;Tobler, PN;Schultz, W
通讯作者：
Schultz, W
影响因子：
11
作者：
Castrioto, Anna;Funkiewiez, Aurelie;Krack, Paul
通讯作者：
Krack, Paul