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  • Deep Q-Network (DQN) Applied to Gymnasium Mountain Car | Python+Pytorch Deep Reinforcement Learning · Comments2.

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    1日前 -This study introduces a decontamination technique involving a supervised rewarding strategy to drive a deep Q-network-based agent (supDQN). ... The deep Q-network ...

    2024/4/20 -In this paper, the state matrix corresponding to the preprocessed raster map is used as the input of the deep neural network. The deep Q network (DQN) is used ...

    2024/4/21 -To improve energy efficiency and reduce power consumption, this paper proposes a Deep Q-Network policy with a novel power allocation method for NOMA-enabled ...

    2024/4/24 -This is a pytorch implementation where we will solve this environmnet using two model, DeepQNetwork and Q learning. Deep Q-Network (DQN). Hyperaparameters ...

    2024/4/24 -This study aims to explore the potential of using reinforcement learning, specifically through the double deep Q-network (DDQN) [11], to predict stock market ...

    3日前 -Artificial intelligence could be one of humanity's most useful inventions. We research and build safe artificial intelligence systems.

    3日前 -Abbreviation for Deep Q-Network. E. environment. #rl. In reinforcement learning, the ...

    2024/4/23 -Deep Q Network (DQN), Double DQN, and Dueling DQN: A step towards general artificial intelligence [M]//Deep reinforcement learning: Frontiers of artificial ...

    2024/4/15 -... DQN is trained by sampling batches of experiences from the replay buffer, calculating the loss, and updating the eval net's weights θ using back-propagation ...