We study some existing techniques for solving mean-payoff games (MPGs), improve them, and design a randomized algorithm for solving MPGs with currently the best expected complexity.
Abstract. We study existing parallel algorithms for the decomposition of a partitioned graph into its strongly connected components. In particular, we identify several individual procedures that the algorithms are assembled from and show how to assemble a new and more efficient algorithm, called Recursive OBF, to solve the decomposition problem. We also report on a thorough experimental study to evaluate the new algorithm. It shows that it is possile to perform SCC decomposition in parallel efficiently and that Recursive OBF, if properly implemented, is the best choice in most cases.
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