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  • 标题:The Adversarial Stackelberg Value in Quantitative Games
  • 本地全文:下载
  • 作者:Emmanuel Filiot ; Raffaella Gentilini ; Jean-Fran{\c{c}}ois Raskin
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2020
  • 卷号:168
  • 页码:127:1-127:18
  • DOI:10.4230/LIPIcs.ICALP.2020.127
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:In this paper, we study the notion of adversarial Stackelberg value for two-player non-zero sum games played on bi-weighted graphs with the mean-payoff and the discounted sum functions. The adversarial Stackelberg value of Player 0 is the largest value that Player 0 can obtain when announcing her strategy to Player 1 which in turn responds with any of his best response. For the mean-payoff function, we show that the adversarial Stackelberg value is not always achievable but ε-optimal strategies exist. We show how to compute this value and prove that the associated threshold problem is in NP. For the discounted sum payoff function, we draw a link with the target discounted sum problem which explains why the problem is difficult to solve for this payoff function. We also provide solutions to related gap problems.
  • 关键词:Non-zero sum games; reactive synthesis; adversarial Stackelberg
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