2026-08-07T05:10:00Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:12534 2024-03-06T10:50:23Z ddc:004 open_access

The Adversarial Stackelberg Value in Quantitative Games Filiot, Emmanuel Gentilini, Raffaella Raskin, Jean-François Non-zero sum games reactive synthesis adversarial Stackelberg 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Emmanuel Filiot and Raffaella Gentilini and Jean-François Raskin 2020 Is Part Of LIPIcs, Volume 168, 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.ICALP.2020.127 urn:nbn:de:0030-drops-125348 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2020.127 eng https://creativecommons.org/licenses/by/3.0/legalcode