{"paper":{"title":"A Potential Reduction Algorithm for Two-person Zero-sum Mean Payoff Stochastic Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Endre Boros, Kazuhisa Makino, Khaled Elbassioni, Vladimir Gurvich","submitted_at":"2015-08-14T10:04:00Z","abstract_excerpt":"We suggest a new algorithm for two-person zero-sum undiscounted stochastic games focusing on stationary strategies. Given a positive real $\\epsilon$, let us call a stochastic game $\\epsilon$-ergodic, if its values from any two initial positions differ by at most $\\epsilon$. The proposed new algorithm outputs for every $\\epsilon>0$ in finite time either a pair of stationary strategies for the two players guaranteeing that the values from any initial positions are within an $\\epsilon$-range, or identifies two initial positions $u$ and $v$ and corresponding stationary strategies for the players p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1508.03455","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}