In this work we present a Reinforcement Learning approach for the Flexible Job Shop Scheduling problem. The proposed approach follows the ideas of the hierarchical approaches and combines learning and optimization in order to achieve better results. Several problem in-stances were used to test the algorithm and to compare the results with those reported by previous approaches.
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