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Dynamic dispatching aims to smartly allocate the right resources to the rightplace at the right time. Dynamic dispatching is one of the core problems foroperations optimization in the mining industry. Theoretically, deepreinforcement learning (RL) should be a natural fit to solve this problem.However, the industry relies on heuristics or even human intuitions, which areoften short-sighted and sub-optimal solutions. In this paper, we review themain challenges in using deep RL to address the dynamic dispatching problem inthe mining industry.

Challenges of Applying Deep Reinforcement Learning in Dynamic Dispatching