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Monte Carlo Planning in RTS Games

Monte Carlo simulations have been successfully used in classic turn–based games such as backgammon, bridge, poker, and Scrabble. In this paper, we apply the ideas to the problem of planning in games with imperfect information, stochasticity, and simultaneous moves. The domain we consider is real–time strategy games. We present a framework — MCPlan — for Monte Carlo planning, identify its performance parameters, and analyze the results of an implementation in a capture– the–flag game.