Results 11 to 20 of about 198,528 (317)
The Journal of Neuroscience, 2021 Humans routinely learn the value of actions by updating their expectations based on past outcomes – a process driven by reward prediction errors (RPEs). Importantly, however, implementing a course of action also requires the investment of effort. Recent work has revealed a close link between the neural signals involved in effort exertion and those ...
Huw Jarvis +5 more
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Reinforcement Learning and Physics
Applied Sciences, 2021 Machine learning techniques provide a remarkable tool for advancing scientific research, and this area has significantly grown in the past few years. In particular, reinforcement learning, an approach that maximizes a (long-term) reward by means of the ...
José D. Martín-Guerrero, Lucas Lamata
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Relational reinforcement learning [PDF]
Machine Learning, 1998 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Saso Dzeroski +2 more
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Sensors, 2023 Reinforcement learning agents that have not been seen during training must be robust in test environments. However, the generalization problem is challenging to solve in reinforcement learning using high-dimensional images as the input. The addition of a
Sanghoon Park +4 more
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Learning to reinforcement learn
CoRR, 2016 17 pages, 7 figures, 1 ...
Wang, Jane +8 more
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Algorithms, 2020 Reinforcement learning, as a branch of machine learning, has been gradually applied in the control field. However, in the practical application of the algorithm, the hyperparametric approach to network settings for deep reinforcement learning still ...
Menglin Li +3 more
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A Survey on Reinforcement Learning Methods in Bionic Underwater Robots
Biomimetics, 2023 Bionic robots possess inherent advantages for underwater operations, and research on motion control and intelligent decision making has expanded their application scope.
Ru Tong +5 more
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Review of Model-Based Reinforcement Learning
Jisuanji kexue yu tansuo, 2020 Deep reinforcement learning (DRL) as an important learning paradigm in the field of machine learning, has received increasing attentions after AlphaGo defeats the human.
ZHAO Tingting, KONG Le, HAN Yajie, REN Dehua, CHEN Yarui
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, 2020 Chapter in "A Guided Tour of Artificial Intelligence Research ...
Buffet, Olivier +2 more
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Reinforcement Learning for Bioretrosynthesis [PDF]
ACS Synthetic Biology, 2019 Abstract Metabolic engineering aims to produce chemicals of interest from living organisms, to advance towards greener chemistry. Despite efforts, the research and development process is still long and costly and efficient computational design tools are required to explore the chemical biosynthetic space. Here, we propose to explore the
Koch, Mathilde +2 more
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