Solving games via three-valued abstraction refinement

AbstractGames that model realistic systems can have very large state-spaces, making their direct solution difficult. We present a symbolic abstraction-refinement approach to the solution of two-player games with reachability or safety goals. Given a reachability or safety property, an initial set of states, and a game representation, our approach starts by constructing a simple abstraction of the game, guided by the predicates present in the property and in the initial set. The abstraction is then refined, until it is possible to either prove, or disprove, the property over the initial states. Specifically, we evaluate the property on the abstract game in three-valued fashion, computing an over-approximation (the may states), and an under-approximation (the must states), of the states that satisfy the property. If this computation fails to yield a certain yes/no answer to the validity of the property on the initial states, our algorithm refines the abstraction by splitting uncertain abstract states (states that are may-states, but not must-states). The approach lends itself to an efficient symbolic implementation. We discuss the property required of the abstraction scheme in order to achieve convergence and termination of our technique