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The main problem of reinforcement learning is that the learning converges slowly. As one of the solutions, McGovern (1997) proposed the "macro-action". However, a human expert needs to design macro-actions which adapt to an environment. In this paper, we propose a new method that enables one to generate the macro-actions which adapt to the environment automatically using the genetic algorithm.