{"title":"On fuzzy decision processes with discounted fuzzy rewards","authors":"Y. Yoshida","doi":"10.1109/ISUMA.1995.527705","DOIUrl":null,"url":null,"abstract":"Deals with a multi-stage decision process with fuzzy transitions, which is termed a 'fuzzy decision process'. We consider the fuzzy decision process, where both states and actions are assumed to be fuzzy, from the point of view of a dynamic fuzzy system which has been developed by the authors. The discounted total reward is described by a fuzzy number on a closed bounded interval. A partial order of convex fuzzy numbers, which is called a 'fuzzy max order', is used to discuss the optimization problem. We characterize the discounted total reward associated with an admissible stationary policy by a unique fixed point of the contractive mapping. Further, we estimate the fuzzy rewards by introducing a fuzzy expectation generated by a fuzzy goal.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISUMA.1995.527705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Deals with a multi-stage decision process with fuzzy transitions, which is termed a 'fuzzy decision process'. We consider the fuzzy decision process, where both states and actions are assumed to be fuzzy, from the point of view of a dynamic fuzzy system which has been developed by the authors. The discounted total reward is described by a fuzzy number on a closed bounded interval. A partial order of convex fuzzy numbers, which is called a 'fuzzy max order', is used to discuss the optimization problem. We characterize the discounted total reward associated with an admissible stationary policy by a unique fixed point of the contractive mapping. Further, we estimate the fuzzy rewards by introducing a fuzzy expectation generated by a fuzzy goal.