Results 31 to 40 of about 8,331,707 (294)
Deep Reinforcement Learning in Medicine [PDF]
Kidney Diseases, 2018 Reinforcement learning has achieved tremendous success in recent years, notably in complex games such as Atari, Go, and chess. In large part, this success has been made possible by powerful function approximation methods in the form of deep neural networks.
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Deep Reinforcement Learning with Interactive Feedback in a Human–Robot Environment
Applied Sciences, 2020 Robots are extending their presence in domestic environments every day, it being more common to see them carrying out tasks in home scenarios. In the future, robots are expected to increasingly perform more complex tasks and, therefore, be able to ...
Ithan Moreira +5 more
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A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation
Sensors, 2023 Robotic manipulation challenges, such as grasping and object manipulation, have been tackled successfully with the help of deep reinforcement learning systems.
Dong Han +3 more
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De novo drug design using reinforcement learning with graph-based deep generative models [PDF]
, 2021 Machine learning methods have proven to be effective tools for molecular design, allowing for efficient exploration of the vast chemical space via deep molecular generative models.
Sara, Romeo Atance +4 more
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Deep reinforcement learning of transition states [PDF]
Physical Chemistry Chemical Physics, 2021 RL ‡ can automatically locate the transition states of chemical reactions through deep reinforcement learning of feedback from molecular simulations.
Jun Zhang +7 more
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An Introduction to Deep Reinforcement Learning [PDF]
Foundations and Trends® in Machine Learning, 2018 Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has been able to solve a wide range of complex decision making tasks that were previously out of reach for a machine. Thus, deep RL opens up many new applications in domains such as healthcare, robotics, smart grids, finance, and many
Vincent François-Lavet +4 more
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Hyperbolic Deep Reinforcement Learning
CoRR, 2022 Preprint
Edoardo Cetin +3 more
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Real-time security margin control using deep reinforcement learning
Energy and AI, 2023 This paper develops a real-time control method based on deep reinforcement learning aimed to determine the optimal control actions to maintain a sufficient secure operating limit.
Hannes Hagmar +2 more
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Overview of Multi-agent Deep Reinforcement Learning Based on Value Factorization [PDF]
Jisuanji kexue, 2022 Multi-agent deep reinforcement learning based on value factorization is one of many multi-agent deep reinforcement learning algorithms,and it is also a research hotspot in the field of multi-agent deep reinforcement learning.Under some constraints,the ...
XIONG Li-qin, CAO Lei, LAI Jun, CHEN Xi-liang
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Abstraction for Deep Reinforcement Learning
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022 We characterise the problem of abstraction in the context of deep reinforcement learning. Various well established approaches to analogical reasoning and associative memory might be brought to bear on this issue, but they present difficulties because of the need for end-to-end differentiability.
Murray Shanahan, Melanie Mitchell
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