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Atari Inc deep q-network (dqn) algorithm
Deep Q Network (Dqn) Algorithm, supplied by Atari Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/deep+q-network+(dqn)+algorithm/dqn/10__3390_slash_app10134529-22-5-22
Average 90 stars, based on 1 article reviews
deep q-network (dqn) algorithm - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Sample Efficient Reinforcement Learning Method via High Efficient Episodic Memory
Article Snippet: Taking deep reinforcement learning (DRL) for example, the algorithm named Deep Q-Network (DQN) got a superhuman level score in a range of Atari 2600 video games [6], [7].

Article Title: A Survey of Planning and Learning in Games
Article Snippet: More recent examples include the Deep Q-Network (DQN) [16] algorithm, which achieved human level gameplay and above on several games from the Atari 2600 gaming platform, using raw images as input; AlphaGo [17], the computer program that defeated the human European Go champion in 2015; OpenAI Five [18], the first AI to defeat the world champions at an e-sport game, Dota 2, in 2019; and AlphaStar [19], the first AI to defeat a top professional player in StarCraft II in 2018.



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