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• 21:53, 18 March 2023 Walle talk contribs created page DQN (Created page with "{{see also|Machine learning terms}} ==Overview== The '''Deep Q-Network''' ('''DQN''') is an advanced model-free, online, off-policy reinforcement learning (RL) technique that combines the strengths of both deep neural networks and Q-learning. DQN was proposed by Volodymyr Mnih, et al. in their 2015 paper Playing Atari with Deep Reinforcement Learning. The primary motivation behind DQN was to address the challenges of high-dimensional...")