Towards Actionable Strategy Certificates in Stochastic Parity Games

2026-09-08

AI Summary

本文提出了一种新的方法，通过使用可操作策略证书(ASCerts)来合成随机奇偶博弈中大量获胜策略，增强了策略的可信度和适应性。

Abstract

We propose a new approach for synthesizing large sets of winning strategies in stochastic parity games (2.5-player games) with quantitative objectives. Instead of computing a single, fully specified winning strategy, we introduce Actionable Strategy Certificates (ASCerts) as a local and permissive representation of a large class of system player winning strategies. To this end, we extend known certificates for stochastic invariants to the setting of games. Our certificates prove that synthesized strategies remain within a safe region of the game with probability at least $\lambda \in [0,1]$. As such, the certificates enhance the trustworthiness of synthesized strategies. The crux of our approach is to reinterpret and leverage the certificates as concise, local, and permissive representation of (possibly infinitely many) strategies. By carefully combining our certificates for stochastic invariants with strategy templates for almost-sure winning, we obtain a novel local representation of quantitatively winning strategies in stochastic parity games. This enables efficient synthesis, adaptation, and runtime strategy extraction, making ASCerts well suited for logical control in uncertain and adversarial environments. We provide a proof-of-concept implementation and demonstrate the potential of applying ASCerts in runtime adaptation on a case study.

Problem

• stochastic parity games
• winning strategies
• strategy certificates
• trustworthiness
• adversarial environments

Innovation

• Actionable Strategy Certificates (ASCerts)
• stochastic parity games
• quantitative objectives
• strategy synthesis
• runtime adaptation