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deep q network dqn  (Deepmind Technologies Ltd)

 
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    Deepmind Technologies Ltd deep q network dqn
    Deep Q Network Dqn, supplied by Deepmind Technologies Ltd, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/deep+q-network+(dqn)/deep+network+q/10__1002_slash_rob__70199-630-6-12
    Average 86 stars, based on 1 article reviews
    deep q network dqn - by Bioz Stars, 2026-09
    86/100 stars

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    Article Title: Path planning of mobile robot based on improved double deep Q-network algorithm
    Article Snippet: The DRL algorithm most widely used in path planning is the Deep Q Network (DQN) algorithm proposed by the DeepMind team ( ).

    Article Title: Optimal Load Distribution Control for Airport Terminal Chiller Units Based on Deep Reinforcement Learning
    Article Snippet: The building sector consumes substantial energy, with HVAC systems accounting for nearly half of the total energy use.. Optimizing chiller unit operations is crucial for reducing energy consumption.. This research introduces a novel model-free control method for optimizing central chiller load distribution using deep reinforcement learning (DRL).

    Article Title: Control System for the Navigation of the Agricultural Robots: A Review
    Article Snippet: A widely used method is the Deep Q‐Network (DQN), initially introduced by DeepMind in 2015, which combines Q‐learning with function approximation through convolutional or fully connected neural networks and experience replay mechanisms (Vasconez et al. 2019).

    Article Title: When large language model meets optimization
    Article Snippet: In 2013, Mnih et al. from DeepMind combined DL with Q-learning, proposing the groundbreaking Deep Q-network (DQN) [42].

    Article Title: Sim-to-Real Learning-based Nonlinear MPC for UAV Navigation and Collision Avoidance in Unknown Cluttered Environments
    Article Snippet: Notable examples include pioneering algorithms from DeepMind, such as the deep-Q-network (DQN) [6], along with variations like double DQN and dueling DQN [7].

    Control:

    Article Title: Control System for the Navigation of the Agricultural Robots: A Review
    Article Snippet: .. Likewise, controllers based on deep reinforcement learning, such as the Deep Q Network (DQN) developed by DeepMind in 2015, combine reinforcement learning (Q‐learning) with deep neural networks, allowing the development of adaptive control strategies, as implemented by Zhang et al. (2019) in a commercial robot. ..



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