TWO LOCAL STRATEGY ITERATION SCHEMES FOR PARITY GAME SOLVING

Abstract

The problem of solving a parity game is at the core of many problems in model checking, satisfiability checking and program synthesis. Some of the best algorithms for solving parity game are strategy iteration algorithms. These are global in nature since they require the entire parity game to be present at the beginning. This is a distinct disadvantage because in many applications one only needs to know which winning region a particular node belongs to, and a witnessing winning strategy may cover only a fractional part of the entire game graph. We present two local strategy iteration algorithms which explore the game graph on-the-fly whilst performing the improvement steps. We also compare them empirically with existing global strategy iteration algorithms and the currently only other local algorithm for solving parity games. It turns out that local strategy iteration can outperform these others significantly.