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The Multi-Agent RLRM (Reinforcement Learning with Reward Machines) Framework is a library designed to facilitate the formulation of multi-agent problems and solve them through reinforcement learning. The framework supports the integration of Reward Machines (RMs), providing a modular and flexible structure for defining complex tasks.