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High‐resolution surface velocities and strain for Anatolia from Sentinel‐1 InSAR and GNSS data 期刊论文
Geophysical Research Letters, 2020
作者:  Jonathan R. Weiss;  Richard J. Walters;  Yu Morishita;  Tim J. Wright;  Milan Lazecky;  Hua Wang;  Ekbal Hussain;  Andrew J. Hooper;  John R. Elliott;  Chris Rollins;  Chen Yu;  Pablo J. Gonzá;  lez;  Karsten Spaans;  Zhenhong Li;  Barry Parsons
收藏  |  浏览/下载:18/0  |  提交时间:2020/07/14
A distributional code for value in dopamine-based reinforcement learning 期刊论文
NATURE, 2020, 577 (7792) : 671-+
作者:  House, Robert A.;  Maitra, Urmimala;  Perez-Osorio, Miguel A.;  Lozano, Juan G.;  Jin, Liyu;  Somerville, James W.;  Duda, Laurent C.;  Nag, Abhishek;  Walters, Andrew;  Zhou, Ke-Jin;  Roberts, Matthew R.;  Bruce, Peter G.
收藏  |  浏览/下载:78/0  |  提交时间:2020/07/03

Since its introduction, the reward prediction error theory of dopamine has explained a wealth of empirical phenomena, providing a unifying framework for understanding the representation of reward and value in the brain(1-3). According to the now canonical theory, reward predictions are represented as a single scalar quantity, which supports learning about the expectation, or mean, of stochastic outcomes. Here we propose an account of dopamine-based reinforcement learning inspired by recent artificial intelligence research on distributional reinforcement learning(4-6). We hypothesized that the brain represents possible future rewards not as a single mean, but instead as a probability distribution, effectively representing multiple future outcomes simultaneously and in parallel. This idea implies a set of empirical predictions, which we tested using single-unit recordings from mouse ventral tegmental area. Our findings provide strong evidence for a neural realization of distributional reinforcement learning.


Analyses of single-cell recordings from mouse ventral tegmental area are consistent with a model of reinforcement learning in which the brain represents possible future rewards not as a single mean of stochastic outcomes, as in the canonical model, but instead as a probability distribution.


  
Mixed-quantum-dot solar cells 期刊论文
NATURE COMMUNICATIONS, 2017, 8
作者:  Yang, Zhenyu;  Fan, James Z.;  Proppe, Andrew H.;  de Arquer, F. Pelayo Garcia;  Rossouw, David;  Voznyy, Oleksandr;  Lan, Xinzheng;  Liu, Min;  Walters, Grant;  Quintero-Bermudez, Rafael;  Sun, Bin;  Hoogland, Sjoerd;  Botton, Gianluigi A.;  Kelley, Shana O.;  Sargent, Edward H.
收藏  |  浏览/下载:28/0  |  提交时间:2019/11/27