Presentation 2010-03-11
Construction of a Brain-like Decision Making System Focusing on Sequential Analysis : A Gomoku System with Reinforcement, SOM Learnillg System, and Sequential Analysis
Satoshi KUROKI, Keiichi MURAMATSU, Kazuaki KOJIMA, Tatsunori MATSUI,
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Abstract(in English) We propose a brain-like decision making model consisting of SA(Sequential Analysis), RL(Reinforcement Learning) and SOM(Self Organizing Map), to provide a basis for building a new system by modeling human brains as high quality information processing systems. Through comparison of our model with previous studies in neuroscience and economics, and through an experiment by computer simulations of our model, we discussed to what extent our model reproduces behaviors of human decision making. The results indicated that our model can mimic some functions of human brains in decision making of human validly, especially ones functioning in neocortex.
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Keyword(in English) Decision Making / Gomoku / Sequential Analysis / Reinforcement Learning / Self Organizing Map
Paper # NC2009-165
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Committee NC
Conference Date 2010/3/2(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) Construction of a Brain-like Decision Making System Focusing on Sequential Analysis : A Gomoku System with Reinforcement, SOM Learnillg System, and Sequential Analysis
Sub Title (in English)
Keyword(1) Decision Making
Keyword(2) Gomoku
Keyword(3) Sequential Analysis
Keyword(4) Reinforcement Learning
Keyword(5) Self Organizing Map
1st Author's Name Satoshi KUROKI
1st Author's Affiliation School of Human Sciences, Waseda University()
2nd Author's Name Keiichi MURAMATSU
2nd Author's Affiliation Graduate School of Human Sciences, Waseda University
3rd Author's Name Kazuaki KOJIMA
3rd Author's Affiliation Faculty of Human Sciences, Waseda University
4th Author's Name Tatsunori MATSUI
4th Author's Affiliation Faculty of Human Sciences, Waseda University
Date 2010-03-11
Paper # NC2009-165
Volume (vol) vol.109
Number (no) 461
Page pp.pp.-
#Pages 6
Date of Issue