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Paper Abstract and Keywords
Presentation 2014-03-18 16:00
Causality Trace -- Effective Retrospective Learning by Introducing Parallel and Subjective Time Scales --
Katsunari Shibata (Oita Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) As a general method for effective retrospective learning in uninterrupted time based on the concept of ``subjective time'', ``causality trace'' is introduced. A trace, which is assigned at each connection in each neuron, takes in the corresponding input signal according to the temporal change in the neuron's output. This enables to memorize only past important events, to hold them in its local memory, and to learn the past processes effectively. Through learning, the criteria of what is important is acqquired, and the division of roles in the time axis among neurons is promoted. From the viewpoint of time, there are parallel, non-uniform and subjective time scales in the neural network. The causality traces can be applied to value learning with a neural network, and also to the learning of recurrent neural networks though the way of application is a bit different. A new simulation result in a value-learning task shows its effectiveness and the division of roles in the time axis among neurons through learning.
Keyword (in Japanese) (See Japanese page) 
(in English) Causality Trace / Neural Network / Reinforcement Learning / Eligibility Trace / Subjective Time / Retrospective Learning / Recurrent Neural Network / Supervised Learning  
Reference Info. IEICE Tech. Rep., vol. 113, no. 500, NC2013-115, pp. 157-162, March 2014.
Paper # NC2013-115 
Date of Issue 2014-03-10 (NC) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380

Conference Information
Committee NC MBE  
Conference Date 2014-03-17 - 2014-03-18 
Place (in Japanese) (See Japanese page) 
Place (in English) Tamagawa University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2014-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Causality Trace 
Sub Title (in English) Effective Retrospective Learning by Introducing Parallel and Subjective Time Scales 
Keyword(1) Causality Trace  
Keyword(2) Neural Network  
Keyword(3) Reinforcement Learning  
Keyword(4) Eligibility Trace  
Keyword(5) Subjective Time  
Keyword(6) Retrospective Learning  
Keyword(7) Recurrent Neural Network  
Keyword(8) Supervised Learning  
1st Author's Name Katsunari Shibata  
1st Author's Affiliation Oita University (Oita Univ.)
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Date Time 2014-03-18 16:00:00 
Presentation Time 20 
Registration for NC 
Paper # IEICE-NC2013-115 
Volume (vol) IEICE-113 
Number (no) no.500 
Page pp.157-162 
#Pages IEICE-6 
Date of Issue IEICE-NC-2014-03-10 

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