{"title":"ELM-Based Agents for Grid Resource Selection","authors":"Guopeng Zhao, Zhiqi Shen, Ailiya, C. Miao","doi":"10.1109/WIIAT.2008.355","DOIUrl":null,"url":null,"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.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIIAT.2008.355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
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.