Muqsit Azeem, Alexandros Evangelidis, Jan Křetínský, Alexander Slivinskiy, Maximilian Weininger
{"title":"简单随机对策的乐观和拓扑值迭代","authors":"Muqsit Azeem, Alexandros Evangelidis, Jan Křetínský, Alexander Slivinskiy, Maximilian Weininger","doi":"10.48550/arXiv.2207.14417","DOIUrl":null,"url":null,"abstract":". While value iteration (VI) is a standard solution approach to simple stochastic games (SSGs), it suffered from the lack of a stopping criterion. Recently, several solutions have appeared, among them also “optimistic” VI (OVI). However, OVI is applicable only to one-player SSGs with no end components. We lift these two assumptions, making it available to general SSGs . Further, we utilize the idea in the context of topological VI, where we provide an efficient precise solution. In order to compare the new algorithms with the state of the art, we use not only the standard benchmarks, but we also design a random generator of SSGs, which can be biased towards various types of models, aiding in understanding the advantages of different algorithms on SSGs.","PeriodicalId":335085,"journal":{"name":"Automated Technology for Verification and Analysis","volume":"281 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Optimistic and Topological Value Iteration for Simple Stochastic Games\",\"authors\":\"Muqsit Azeem, Alexandros Evangelidis, Jan Křetínský, Alexander Slivinskiy, Maximilian Weininger\",\"doi\":\"10.48550/arXiv.2207.14417\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". While value iteration (VI) is a standard solution approach to simple stochastic games (SSGs), it suffered from the lack of a stopping criterion. Recently, several solutions have appeared, among them also “optimistic” VI (OVI). However, OVI is applicable only to one-player SSGs with no end components. We lift these two assumptions, making it available to general SSGs . Further, we utilize the idea in the context of topological VI, where we provide an efficient precise solution. In order to compare the new algorithms with the state of the art, we use not only the standard benchmarks, but we also design a random generator of SSGs, which can be biased towards various types of models, aiding in understanding the advantages of different algorithms on SSGs.\",\"PeriodicalId\":335085,\"journal\":{\"name\":\"Automated Technology for Verification and Analysis\",\"volume\":\"281 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Automated Technology for Verification and Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.48550/arXiv.2207.14417\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automated Technology for Verification and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48550/arXiv.2207.14417","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimistic and Topological Value Iteration for Simple Stochastic Games
. While value iteration (VI) is a standard solution approach to simple stochastic games (SSGs), it suffered from the lack of a stopping criterion. Recently, several solutions have appeared, among them also “optimistic” VI (OVI). However, OVI is applicable only to one-player SSGs with no end components. We lift these two assumptions, making it available to general SSGs . Further, we utilize the idea in the context of topological VI, where we provide an efficient precise solution. In order to compare the new algorithms with the state of the art, we use not only the standard benchmarks, but we also design a random generator of SSGs, which can be biased towards various types of models, aiding in understanding the advantages of different algorithms on SSGs.