Résumé | A simple stochastic game, SSG for short, is a two-player zero-sum game, a turn-based version of stochastic games. SSGs were introduced by Condon and provide a general framework that allows to study algorithmic complexity issues underlying reachability objectives. The best algorithm so far for solving SSGs is Ludwig’s randomized algorithm which works in expected 2^O(sqrt(n)) time. We first give a simpler iterative variant of this algorithm, using Bland’s rule from the simplex algorithm, which uses exponentially less random bits than Ludwig’s version. Then, we show how to adapt this method to the algorithm of Gimbert and Horn whose worst case complexity is O(k!), where k is the number of random nodes. Our algorithm has an expected running time of 2^O(k) , and works for general random nodes with arbitrary outdegree and probability distribution on outgoing arcs. |