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Real time strategy games are complex scenarios where multiple agents must be coordinated in a dynamic, partially observable environment. In this work, we model coordination as a task allocation problem, in which specific tasks must be properly assigned to agents. We employ a task allocation algorithm based on swarm intelligence and adjust its parameters using a genetic algorithm. A fitness estimation method is employed to accelerate execution of the genetic algorithm. To evaluate this approach,doi:10.1109/sbgames.2014.17 dblp:conf/sbgames/TavaresAC14 fatcat:v6rvufcqzrbnjcitx3sp7bbgqe