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This paper presents a Bayesian model to predict the opening (first strategy) of opponents in real-time strategy (RTS) games. Our model is general enough to be applied to any RTS game with the canonical gameplay of gathering resources to extend a technology tree and produce military units and we applied it to StarCraft 1 . This model can also predict the possible technology trees of the opponent, but we will focus on openings here. The parameters of this model are learned from replays (gamedoi:10.1109/cig.2011.6032018 dblp:conf/cig/SynnaeveB11a fatcat:ca6qp3aryfbmhiddo4jr7gmhmu