Solving Qualitative Multi-Objective Stochastic Games

TL;DR

This paper analyzes the complexity and memory requirements of two-player multi-objective stochastic games with qualitative reachability and safety objectives, revealing new complexity classifications and determinacy results.

Contribution

It characterizes the complexity and determinacy of multi-objective stochastic games with Boolean combinations of qualitative objectives, extending the understanding of their computational landscape.

Findings

Games with conjunctions of AS and NZ objectives are determined and PSPACE-complete.

Full Boolean combinations of qualitative objectives are not determined and are NEXPTIME-hard.

Results connect stochastic game complexity with logics involving partially-ordered quantification.

Abstract

Many problems in compositional synthesis and verification of multi-agent systems -- such as rational verification and assume-guarantee verification in probabilistic systems -- reduce to reasoning about two-player multi-objective stochastic games. This motivates us to study the problem of characterizing the complexity and memory requirements for two-player stochastic games with Boolean combinations of qualitative reachability and safety objectives. Reachability objectives require that a given set of states is reached; safety requires that a given set is invariant. A qualitative winning condition asks that an objective is satisfied almost surely (AS) or (in negated form) with non-zero (NZ) probability. We study the determinacy and complexity landscape of the problem. We show that games with conjunctions of AS and NZ reachability and safety objectives are determined, and determining the winner is PSPACE-complete. The same holds for positive boolean combinations of AS reachability and safety, as well as for negations thereof. On the other hand, games with full Boolean combinations of qualitative objectives are not determined, and are NEXPTIME-hard. Our hardness results show a connection between stochastic games and logics with partially-ordered quantification. Our results shed light on the relationship between determinacy and complexity, and extend the complexity landscape for stochastic games in the multi-objective setting.