{"title":"猜测随机函数和连续时间中的重复博弈","authors":"Catherine Rainer , Eilon Solan","doi":"10.1016/j.orl.2024.107120","DOIUrl":null,"url":null,"abstract":"<div><p>We study a game where one player selects a random function and the other guesses that function, and show that with high probability the second player can correctly guess most of the random function. We apply this analysis to continuous-time repeated games played with mixed strategies with delay, identify good responses of a player to any strategy profile of her opponents, and show that each player's minmax value coincides with her minmax value in pure strategies of the one-shot game.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"54 ","pages":"Article 107120"},"PeriodicalIF":0.8000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Guessing a random function and repeated games in continuous time\",\"authors\":\"Catherine Rainer , Eilon Solan\",\"doi\":\"10.1016/j.orl.2024.107120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We study a game where one player selects a random function and the other guesses that function, and show that with high probability the second player can correctly guess most of the random function. We apply this analysis to continuous-time repeated games played with mixed strategies with delay, identify good responses of a player to any strategy profile of her opponents, and show that each player's minmax value coincides with her minmax value in pure strategies of the one-shot game.</p></div>\",\"PeriodicalId\":54682,\"journal\":{\"name\":\"Operations Research Letters\",\"volume\":\"54 \",\"pages\":\"Article 107120\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Research Letters\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167637724000567\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research Letters","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167637724000567","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
Guessing a random function and repeated games in continuous time
We study a game where one player selects a random function and the other guesses that function, and show that with high probability the second player can correctly guess most of the random function. We apply this analysis to continuous-time repeated games played with mixed strategies with delay, identify good responses of a player to any strategy profile of her opponents, and show that each player's minmax value coincides with her minmax value in pure strategies of the one-shot game.
期刊介绍:
Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.