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• W2022074309 abstract "Resource selection in Grid involves great dynamics and uncertainties inherited from tasks and resources. The optimal selection of a resource against a task requires fast and intelligent services. Intelligent agent with fast learning capability is promising to resource selection problem in Grid. This paper proposes an Extreme Learning Machine (ELM)-based agent, in which an ELM connectionist module is embedded in an extended Belief-Desire-Intention (BDI) architecture. ELM empowers the agent with fast training and learning speed in the Grid environment. To improve generalization performance a cooperative learning among a group of ELM-based agents is proposed, for which the group decision is summarized upon individual decisions. The experiment results show that ELM-based agents are able to provide intelligent resource selection services, and the proposed cooperative learning outperforms the individual one." @default.
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• W2022074309 date "2008-12-01" @default.
• W2022074309 modified "2023-09-28" @default.
• W2022074309 title "ELM-Based Agents for Grid Resource Selection" @default.
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• W2022074309 doi "https://doi.org/10.1109/wiiat.2008.355" @default.
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