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- W2407094413 abstract "The dislribut.ed agcnl system finds the solulJon of the problem gJven through the recIprocal cooperalion between agents, but Its concept and thell mutual operation are complicated Tins paper suggesls a neural schedulmG method for an effjcienl job link between the aGents as a solution ror these problems First, a tala! of 8750 case pallems are cOlTIposed on the base of s)'Stem operation scenano for drawlOG up of a neural schedubng, Among these cases, we learned In neural nelwork by usmg 2,000 and 6750 cases for learOlUg data and UlC lcsl paUem respeclively. The resull of the learnmg showed mor~ than 90% of convergence rates about learnmg a.TJd test patterns in 200 leamll1G times, The agent creation. Its Job performance, 8nd the dlvlSlon and mutua! cooperattan between lhem were abo made well by usmg the reslllt for a neural scheduling cl8ta," @default.
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- W2407094413 date "2000-10-01" @default.
- W2407094413 modified "2023-09-24" @default.
- W2407094413 title "A Neural Scheduling Method for Efficient Use of Distributed Multi-Agent System" @default.
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