Presentation | 2005/6/17 Distributed-representation-based reasoning by the trajectory attractor model Ken YAMANE, Atsuo SUEMITSU, Masahiko MORITA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The trajectory attractor model is a recurrent neural network that can make continuous state transitions along learned trajectories, and is capable of simulating any large-scale finite automaton without using local representations or symbols. In the present paper, we show a system using this model that reasons based on distributed representation. This model not only has strong generalization ability but also can deal with exceptional data in a simple and natural manner, and thus can make common-sense inferences from a limited amount of given rules. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | nonmonotone neural network / selective desensitization / nonmonotonic reasoning / artificial intelligence |
Paper # | NC2005-24 |
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Committee | NC |
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Conference Date | 2005/6/17(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Distributed-representation-based reasoning by the trajectory attractor model |
Sub Title (in English) | |
Keyword(1) | nonmonotone neural network |
Keyword(2) | selective desensitization |
Keyword(3) | nonmonotonic reasoning |
Keyword(4) | artificial intelligence |
1st Author's Name | Ken YAMANE |
1st Author's Affiliation | Graduate School of Systems and Information Engineering, University of Tsukuba() |
2nd Author's Name | Atsuo SUEMITSU |
2nd Author's Affiliation | Graduate School of Systems and Information Engineering, University of Tsukuba |
3rd Author's Name | Masahiko MORITA |
3rd Author's Affiliation | Graduate School of Systems and Information Engineering, University of Tsukuba |
Date | 2005/6/17 |
Paper # | NC2005-24 |
Volume (vol) | vol.105 |
Number (no) | 131 |
Page | pp.pp.- |
#Pages | 6 |
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