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Dynamical Systems Approach: An Elementary Introduction and Application to Research on Dopamine and Reinforcement Learning Ayaka Kato 1,2,3 , Kenji Morita 4,5 1Graduate School of Arts and Sciences, The University of Tokyo 2RIKEN Center for Brain Science 3JSPS 4Graduate School of Education, The University of Tokyo 5International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Keyword: 力学系 , アトラクター , 分岐 , ドーパミン , 強化学習 , dynamical system , attractor , bifurcation , dopamine , reinforcement learning pp.1275-1282
Published Date 2020/11/1
DOI https://doi.org/10.11477/mf.1416201679
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Abstract

In order to analyze the dynamic behavior of neural systems such as oscillations or rhythms, an approach based on the dynamical systems theory may be useful. In the first part of this article, we present an elementary introduction to that approach based on the materials for an author's lecture. In the second part, we introduce our own study related to dopamine and reinforcement learning using that approach, in which we assumed the decay of learned values and propose a possible mechanism of the effects of dopamine depletion on motivation.


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電子版ISSN 1344-8129 印刷版ISSN 1881-6096 医学書院

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