Presentation 2012-06-28
A Computational Model for State Value Estimation in the Brain Using Two Kinds of Temporal Differences
Masanari SHINOTSUKA, Masahiko MORITA,
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Abstract(in English) The basal ganglia has been considered to be deeply involved in reinforcement learning since Schultz et al. reported that the midbrain dopamine neurons show activities in accordance with temporal differences (TD). However, existing TD-learning models of the basal ganglia seem to assume some implausible neural mechanisms. We constructed a more plausible model for state value computation by introducing two kinds of TD signals: prospective and actual. Computer simulations on a simple reward prediction task showed that the prospective TD signal varies frequently depending on the short-term history of actions and rewards, and that longer-term state values can be acquired based on the actual TD signal which follows the prospective one with a smaller variation. This model leads to the hypothesis that these two TD signals may be encoded by different dopamine systems in the midbrain.
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Keyword(in English) reinforcement learning / temporal difference / state value function / basal ganglia / dopamine neurons
Paper # NC2012-5
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Committee NC
Conference Date 2012/6/21(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Computational Model for State Value Estimation in the Brain Using Two Kinds of Temporal Differences
Sub Title (in English)
Keyword(1) reinforcement learning
Keyword(2) temporal difference
Keyword(3) state value function
Keyword(4) basal ganglia
Keyword(5) dopamine neurons
1st Author's Name Masanari SHINOTSUKA
1st Author's Affiliation Graduate School of Systems and Information Engineering, University of Tsukuba()
2nd Author's Name Masahiko MORITA
2nd Author's Affiliation Graduate School of Systems and Information Engineering, University of Tsukuba
Date 2012-06-28
Paper # NC2012-5
Volume (vol) vol.112
Number (no) 108
Page pp.pp.-
#Pages 6
Date of Issue