James Berneburg, Xuan Wang, Xuesu Xiao, Daigo Shishika
{"title":"通过对抗性图遍历博弈诱导危险环境中的多机器人协调","authors":"James Berneburg, Xuan Wang, Xuesu Xiao, Daigo Shishika","doi":"arxiv-2409.08222","DOIUrl":null,"url":null,"abstract":"This paper presents a game theoretic formulation of a graph traversal\nproblem, with applications to robots moving through hazardous environments in\nthe presence of an adversary, as in military and security applications. The\nblue team of robots moves in an environment modeled by a time-varying graph,\nattempting to reach some goal with minimum cost, while the red team controls\nhow the graph changes to maximize the cost. The problem is formulated as a\nstochastic game, so that Nash equilibrium strategies can be computed\nnumerically. Bounds are provided for the game value, with a guarantee that it\nsolves the original problem. Numerical simulations demonstrate the results and\nthe effectiveness of this method, particularly showing the benefit of mixing\nactions for both players, as well as beneficial coordinated behavior, where\nblue robots split up and/or synchronize to traverse risky edges.","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Robot Coordination Induced in Hazardous Environments through an Adversarial Graph-Traversal Game\",\"authors\":\"James Berneburg, Xuan Wang, Xuesu Xiao, Daigo Shishika\",\"doi\":\"arxiv-2409.08222\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a game theoretic formulation of a graph traversal\\nproblem, with applications to robots moving through hazardous environments in\\nthe presence of an adversary, as in military and security applications. The\\nblue team of robots moves in an environment modeled by a time-varying graph,\\nattempting to reach some goal with minimum cost, while the red team controls\\nhow the graph changes to maximize the cost. The problem is formulated as a\\nstochastic game, so that Nash equilibrium strategies can be computed\\nnumerically. Bounds are provided for the game value, with a guarantee that it\\nsolves the original problem. Numerical simulations demonstrate the results and\\nthe effectiveness of this method, particularly showing the benefit of mixing\\nactions for both players, as well as beneficial coordinated behavior, where\\nblue robots split up and/or synchronize to traverse risky edges.\",\"PeriodicalId\":501031,\"journal\":{\"name\":\"arXiv - CS - Robotics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.08222\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08222","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-Robot Coordination Induced in Hazardous Environments through an Adversarial Graph-Traversal Game
This paper presents a game theoretic formulation of a graph traversal
problem, with applications to robots moving through hazardous environments in
the presence of an adversary, as in military and security applications. The
blue team of robots moves in an environment modeled by a time-varying graph,
attempting to reach some goal with minimum cost, while the red team controls
how the graph changes to maximize the cost. The problem is formulated as a
stochastic game, so that Nash equilibrium strategies can be computed
numerically. Bounds are provided for the game value, with a guarantee that it
solves the original problem. Numerical simulations demonstrate the results and
the effectiveness of this method, particularly showing the benefit of mixing
actions for both players, as well as beneficial coordinated behavior, where
blue robots split up and/or synchronize to traverse risky edges.