We design and implement an efficient model checking algorithm for alternating-time temporal logic (ATL) on turn-based multi-player stochastic games with weighted transitions. This logic allows us to query about the existence of multiplayer strategies that aim to maximize the probability of game runs satisfying resource-bounded next and until logical operators, while requiring that the accumulated weight along the successful runs does not exceed a given upper bound. Our method relies on a recently introduced formalism of abstract dependency graphs (ADG) and we provide an efficient reduction of our model checking problem to finding the minimum fixed-point assignment on an ADG over the domain of unit intervals extended with certain-zero optimization. As the fixed-point computation on ADGs is performed in an on-the-fly manner without the need of a priori generating the whole graph, we achieve a performance that is comparable with state-of-the-art model checker PRISM-games for finding the exact solutions and sometimes an order of magnitude faster for queries that ask about approximate probability bounds. We document this on a series of scalable experiments from the PRISM-games benchmark that we annotate with weight information.
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