Self-organization Based Manufacturing System Configuration Using Multi-agent Learning
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- Fujii Nobutada
- The University of Tokyo
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- Yokoi Shintaro
- The University of Tokyo
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- Ueda Kanji
- The University of Tokyo
Bibliographic Information
- Other Title
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- マルチエージェント学習による生産システムの自己組織的構成法
Description
This paper presents a self-organization approach to manufacturing system configuration using multi-agent learning to cope with today's complexity in manufacturing systems. In this proposed approach, the roles of machines emerge, using EANNs, to achieve the objective of the whole system through interaction of the machines on the production floor. It can be expected that each machine can change its role to adapt to the new situation through re-organization processes that occur when the manufacturing environment changes. The feasibility of the proposal is discussed using computer simulation results.
Journal
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- Proceedings of JSPE Semestrial Meeting
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Proceedings of JSPE Semestrial Meeting 2007A (0), 377-378, 2007
The Japan Society for Precision Engineering
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Details 詳細情報について
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- CRID
- 1390282680627703424
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- NII Article ID
- 130005027886
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed