목록논문 리뷰/Reinforcement Learning (3)

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[논문 리뷰] Dueling DQN: Dueling Network Architectures for Deep Reinforcement Learning (2016)

이번에 리뷰할 논문은 Dueling Network Architectures for Deep Reinforcement Learning 입니다. https://arxiv.org/abs/1511.06581 Dueling Network Architectures for Deep Reinforcement LearningIn recent years there have been many successes of using deep representations in reinforcement learning. Still, many of these applications use conventional architectures, such as convolutional networks, LSTMs, or auto-encoders..
논문 리뷰/Reinforcement Learning 2025. 4. 22. 04:11
[논문 리뷰] DDQN: Deep Reinforcement Learning with Double Q-learning (2016)

이번에 리뷰할 논문은 Deep Reinforcement Learning with Double Q-learning 입니다.https://arxiv.org/abs/1509.06461 Deep Reinforcement Learning with Double Q-learningThe popular Q-learning algorithm is known to overestimate action values under certain conditions. It was not previously known whether, in practice, such overestimations are common, whether they harm performance, and whether they can generally be pr..
논문 리뷰/Reinforcement Learning 2025. 4. 22. 01:44
[논문 리뷰] DQN: Playing Atari with Deep Reinforcement Learning (2013, 2015)

이번에 리뷰할 논문은 Playing Atari with Deep Reinforcement Learning 입니다.https://arxiv.org/abs/1312.5602 Playing Atari with Deep Reinforcement LearningWe present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. The model is a convolutional neural network, trained with a variant of Q-learning, whose input is rawa..
논문 리뷰/Reinforcement Learning 2025. 4. 20. 02:56
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