{"title":"Determining successful negotiation strategies: an evolutionary approach","authors":"Noyda Matos, C. Sierra, N. Jennings","doi":"10.1109/ICMAS.1998.699048","DOIUrl":null,"url":null,"abstract":"To be successful in open, multi-agent environments, autonomous agents must be capable of adapting their negotiation strategies and tactics to their prevailing circumstances. To this end, we present an empirical study showing the relative success of different strategies against different types of opponent in different environments. In particular we adopt an evolutionary approach in which strategies and tactics correspond to the genetic material in a genetic algorithm. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve depending on the context and negotiation stance of the agent's opponent.","PeriodicalId":244857,"journal":{"name":"Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"214","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMAS.1998.699048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 214
Abstract
To be successful in open, multi-agent environments, autonomous agents must be capable of adapting their negotiation strategies and tactics to their prevailing circumstances. To this end, we present an empirical study showing the relative success of different strategies against different types of opponent in different environments. In particular we adopt an evolutionary approach in which strategies and tactics correspond to the genetic material in a genetic algorithm. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve depending on the context and negotiation stance of the agent's opponent.