Towards the Usage of Window Counting Constraints in the Synthesis of Reactive Systems to Reduce State Space Explosion

TL;DR

This paper introduces window counting constraints to mitigate state space explosion in reactive system synthesis by enabling step-wise specification refinement, demonstrated through an implementation in a zero-sum game setting.

Contribution

It presents a novel approach using window counting constraints to reduce automaton size during synthesis by exploiting specification monotony properties.

Findings

Significant reduction in automaton size achieved.

Effective iterative synthesis procedure demonstrated.

Implementation results validate the approach's potential.

Abstract

The synthesis of reactive systems aims for the automated construction of strategies for systems that interact with their environment. Whereas the synthesis approach has the potential to change the development of reactive systems significantly due to the avoidance of manual implementation, it still suffers from a lack of efficient synthesis algorithms for many application scenarios. The translation of the system specification into an automaton that allows for strategy construction is nonelementary in the length of the specification in S1S and double exponential for LTL, raising the need of highly specialized algorithms. In this paper, we present an approach on how to reduce this state space explosion in the construction of this automaton by exploiting a monotony property of specifications. For this, we introduce window counting constraints that allow for step-wise refinement or abstraction of specifications. In an iterating synthesis procedure, those window counting constraints are used to construct automata representing over- or under-approximations (depending on the counting constraint) of constraint-compliant behavior. Analysis results on winning regions of previous iterations are used to reduce the size of the next automaton, leading to an overall reduction of the state space explosion extend. We present the implementation results of the iterated synthesis for a zero-sum game setting as proof of concept. Furthermore, we discuss the current limitations of the approach in a zero-sum setting and sketch future work in non-zero-sum settings.