Threshold Constraints with Guarantees for Parity Objectives in Markov Decision Processes
Rapha\"el Berthon, Mickael Randour, Jean-Fran\c{c}ois Raskin

TL;DR
This paper extends beyond worst-case synthesis to parity objectives in Markov decision processes, enabling strategies that guarantee functional properties while optimizing probabilistic performance, with complexity comparable to classical parity games.
Contribution
It introduces a framework for strategies satisfying parity objectives with probabilistic guarantees, maintaining the same complexity class as classical parity games.
Findings
Deciding strategy existence is in NP ∩ coNP.
Framework supports functional and probabilistic guarantees simultaneously.
Complexity matches that of classical parity games.
Abstract
The beyond worst-case synthesis problem was introduced recently by Bruy\`ere et al. [BFRR14]: it aims at building system controllers that provide strict worst-case performance guarantees against an antagonistic environment while ensuring higher expected performance against a stochastic model of the environment. Our work extends the framework of [BFRR14] and follow-up papers, which focused on quantitative objectives, by addressing the case of -regular conditions encoded as parity objectives, a natural way to represent functional requirements of systems. We build strategies that satisfy a main parity objective on all plays, while ensuring a secondary one with sufficient probability. This setting raises new challenges in comparison to quantitative objectives, as one cannot easily mix different strategies without endangering the functional properties of the system. We establish…
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
