{"title":"在线学习搜索Stackelberg游戏策略","authors":"J. Janáček, Marek Kvet","doi":"10.1109/CompEng.2018.8536234","DOIUrl":null,"url":null,"abstract":"This paper deals with the public service system design problem, in which we consider more service providers competing for the profit. We assume that the profit of a provider is proportional to transportation performance necessary to satisfy the demands of system users. The considered profit may be enlarged by system reengineering, which consists in changing current positions of some centers operated by the considered provider. Since each center relocation causes some reaction of other providers to maximize their profit, the providers' behavior can be modelled by Stackelberg's game. In this paper, we introduce an approximate solving technique for a special Stackelberg's game played by a leading service provider and other mutually cooperating providers represented by the follower. The strategy of the leading service provider may be sensitive to some parameters. To find their suitable settings, we suggest an online learning algorithm.","PeriodicalId":194279,"journal":{"name":"2018 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Online Learning Search for Stackelberg Game Strategy\",\"authors\":\"J. Janáček, Marek Kvet\",\"doi\":\"10.1109/CompEng.2018.8536234\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with the public service system design problem, in which we consider more service providers competing for the profit. We assume that the profit of a provider is proportional to transportation performance necessary to satisfy the demands of system users. The considered profit may be enlarged by system reengineering, which consists in changing current positions of some centers operated by the considered provider. Since each center relocation causes some reaction of other providers to maximize their profit, the providers' behavior can be modelled by Stackelberg's game. In this paper, we introduce an approximate solving technique for a special Stackelberg's game played by a leading service provider and other mutually cooperating providers represented by the follower. The strategy of the leading service provider may be sensitive to some parameters. To find their suitable settings, we suggest an online learning algorithm.\",\"PeriodicalId\":194279,\"journal\":{\"name\":\"2018 IEEE Workshop on Complexity in Engineering (COMPENG)\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Workshop on Complexity in Engineering (COMPENG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CompEng.2018.8536234\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Workshop on Complexity in Engineering (COMPENG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CompEng.2018.8536234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Online Learning Search for Stackelberg Game Strategy
This paper deals with the public service system design problem, in which we consider more service providers competing for the profit. We assume that the profit of a provider is proportional to transportation performance necessary to satisfy the demands of system users. The considered profit may be enlarged by system reengineering, which consists in changing current positions of some centers operated by the considered provider. Since each center relocation causes some reaction of other providers to maximize their profit, the providers' behavior can be modelled by Stackelberg's game. In this paper, we introduce an approximate solving technique for a special Stackelberg's game played by a leading service provider and other mutually cooperating providers represented by the follower. The strategy of the leading service provider may be sensitive to some parameters. To find their suitable settings, we suggest an online learning algorithm.