2026-08-25T22:09:02Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:27345 2026-08-24T14:08:30Z ddc:004 open_access

Asymmetrically Discounted Stochastic Games Bahmani, Sarvin Paul, Soumyajit Schewe, Sven Kalat, Shadi Tasdighi Trivedi, Ashutosh Stochastic Games Asymmetric Discounting Stackelberg Equilibrium We study asymmetrically discounted stochastic games, in which players use distinct and reasonably apart discount factors. We show that optimal strategies in these games may require both memory and randomisation, in contrast to the classical symmetrically discounted setting. Our main technical contribution establishes that computing incentive Stackelberg equilibria - a variant of Stackelberg equilibria in which one player, called Player Max, can offer payments to the other player, called Player Min - is no harder than solving classical discounted games. We further show that optimal strategies in this setting can be realised by finite counting strategies, whereas restricting players to stationary strategies makes the problem computationally intractable. Finally, we establish that computing classical Stackelberg equilibria in these games under the constraint of memoryless strategies is NP-complete and remains NP-hard even when general or counting strategies are allowed. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Sarvin Bahmani and Soumyajit Paul and Sven Schewe and Shadi Tasdighi Kalat and Ashutosh Trivedi 2026 Is Part Of LIPIcs, Volume 391, 37th International Conference on Concurrency Theory (CONCUR 2026) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.CONCUR.2026.14 urn:nbn:de:0030-drops-273453 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2026.14 eng https://creativecommons.org/licenses/by/4.0/legalcode