Compositional Controller Synthesis for Stochastic Games

Design of autonomous systems is facilitated by automatic synthesis of correct-by-construction controllers from formal models and speci cations. We focus on stochastic games, which can model the interaction with an adverse environment, as well as probabilistic behaviour arising from uncertainties. We propose a synchronising parallel composition for stochastic games that enables a compositional approach to controller synthesis. We leverage rules for compositional assume-guarantee veri cation of probabilistic automata to synthesise controllers for games with multi-objective quantitative winning conditions. By composing winning strategies synthesised for the individual components, we can thus obtain a winning strategy for the composed game, achieving better scalability and eciency at a cost of restricting the class of controllers

Compositional Controller Synthesis for Stochastic Games

Abstract. Design of autonomous systems is facilitated by automatic synthesis of correct-by-construction controllers from formal models and specifications. We focus on stochastic games, which can model the inter-action with an adverse environment, as well as probabilistic behaviour arising from uncertainties. We propose a synchronising parallel composi-tion for stochastic games that enables a compositional approach to con-troller synthesis. We leverage rules for compositional assume-guarantee verification of probabilistic automata to synthesise controllers for games with multi-objective quantitative winning conditions. By composing win-ning strategies synthesised for the individual components, we can thus obtain a winning strategy for the composed game, achieving better scal-ability and efficiency at a cost of restricting the class of controllers.

Compositional Controller Synthesis for Stochastic Games

Design of autonomous systems is facilitated by automatic synthesis of correct-by-construction controllers from formal models and speci cations. We focus on stochastic games, which can model the interaction with an adverse environment, as well as probabilistic behaviour arising from uncertainties. We propose a synchronising parallel composition for stochastic games that enables a compositional approach to controller synthesis. We leverage rules for compositional assume-guarantee veri cation of probabilistic automata to synthesise controllers for games with multi-objective quantitative winning conditions. By composing winning strategies synthesised for the individual components, we can thus obtain a winning strategy for the composed game, achieving better scalability and eciency at a cost of restricting the class of controllers