Looking at Mean-Payoff through Foggy Windows
Paul Hunter, Guillermo A. P\'erez, Jean-Fran\c{c}ois Raskin

TL;DR
This paper explores window mean-payoff objectives in partial-observation games, demonstrating that some are decidable, unlike classical mean-payoff objectives which are undecidable in this setting.
Contribution
It introduces the decidability of certain window mean-payoff objectives in partial-observation games, contrasting with the undecidability of classical mean-payoff objectives.
Findings
Some window mean-payoff objectives are decidable under partial observation.
Classical mean-payoff objectives remain undecidable with partial observation.
The study provides new insights into quantitative game objectives under limited information.
Abstract
Mean-payoff games (MPGs) are infinite duration two-player zero-sum games played on weighted graphs. Under the hypothesis of perfect information, they admit memoryless optimal strategies for both players and can be solved in NP-intersect-coNP. MPGs are suitable quantitative models for open reactive systems. However, in this context the assumption of perfect information is not always realistic. For the partial-observation case, the problem that asks if the first player has an observation-based winning strategy that enforces a given threshold on the mean-payoff, is undecidable. In this paper, we study the window mean-payoff objectives that were introduced recently as an alternative to the classical mean-payoff objectives. We show that, in sharp contrast to the classical mean-payoff objectives, some of the window mean-payoff objectives are decidable in games with partial-observation.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFormal Methods in Verification · Computability, Logic, AI Algorithms · Distributed systems and fault tolerance
