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A Study of Multiagent Reinforcement Learning based on Quantum Theory

机译:基于量子理论的多主体强化学习研究

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In this paper, we present a novel Multiagent Reinforcement Learning Algorithm based on Q-Learning and Quantum Theory. As in reinforcement learning algorithm, when the number of agents or/and agent''s action is large enough, all of the action selection methods will be failed: the speed of learning is decreased sharply. we try to combine the quantum theory with Q-Learning, hoping that the problem will be resolved with our proposed.
机译:在本文中,我们提出了一种基于Q学习和量子理论的新颖的多主体强化学习算法。与强化学习算法一样,当主体或主体和/或主体的动作数量足够大时,所有动作选择方法都将失败:学习速度急剧下降。我们尝试将量子理论与Q-Learning相结合,希望我们提出的方案能够解决该问题。

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