{"title":"An Ontology for Observation of Multiagent Based Simulation","authors":"Tiana Ralambondrainy, R. Courdier, D. Payet","doi":"10.1109/WI-IATW.2006.43","DOIUrl":null,"url":null,"abstract":"In multiagent based simulation (MABS), the observation of simulation results is a complex task: interactions between simulation agents produce a large mass of simulation results, which is particularly complex to analyze. We are assured that the use of another second multiagent system is a suitable approach to achieve this task. This second system then introduces a new category of agents called observation agents. The first step to build this multiagent system for observation is to define a specification of concepts used between its observation agents. Our contribution is an ontology for observation of MABS. This ontology is composed of a set of concepts and relations usable to acquire and process simulation results, and to produce their presentation form. This ontology has three main root classes: observation elements, processing, and presentation","PeriodicalId":358971,"journal":{"name":"2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI-IATW.2006.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In multiagent based simulation (MABS), the observation of simulation results is a complex task: interactions between simulation agents produce a large mass of simulation results, which is particularly complex to analyze. We are assured that the use of another second multiagent system is a suitable approach to achieve this task. This second system then introduces a new category of agents called observation agents. The first step to build this multiagent system for observation is to define a specification of concepts used between its observation agents. Our contribution is an ontology for observation of MABS. This ontology is composed of a set of concepts and relations usable to acquire and process simulation results, and to produce their presentation form. This ontology has three main root classes: observation elements, processing, and presentation