Results 41 to 50 of about 1,052,376 (334)
Deep Reinforcement Learning methods for StarCraft II Learning Environment [PDF]
, 2022 Reinforcement Learning (RL) is a Machine Learning framework in which an agent learns to solve a task by trial-and-error interaction with the surrounding environment.
Dainese, Nicola
core
Hyperbolic Deep Reinforcement Learning
CoRR, 2022 Preprint
Edoardo Cetin +3 more
openaire +3 more sources
Magnetic control of tokamak plasmas through deep reinforcement learning
Nature, 2022 Nuclear fusion using magnetic confinement, in particular in the tokamak configuration, is a promising path towards sustainable energy. A core challenge is to shape and maintain a high-temperature plasma within the tokamak vessel.
Jonas Degrave +30 more
semanticscholar +1 more source
Crowd-Robot Interaction: Crowd-Aware Robot Navigation With Attention-Based Deep Reinforcement Learning [PDF]
IEEE International Conference on Robotics and Automation, 2018 Mobility in an effective and socially-compliant manner is an essential yet challenging task for robots operating in crowded spaces. Recent works have shown the power of deep reinforcement learning techniques to learn socially cooperative policies ...
Changan Chen +3 more
semanticscholar +1 more source
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
openaire +2 more sources
The neurobiology of deep reinforcement learning [PDF]
Current Biology, 2020 In this primer, Ölveczky and Gershman review concepts and advances in deep reinforcement learning and discuss how these can inform the implementation of learning processes in biological neural networks.
Samuel J, Gershman, Bence P, Ölveczky
openaire +2 more sources
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
doaj +1 more source
Deep Reinforcement and InfoMax Learning
CoRR, 2020 NeurIPS ...
Bogdan Mazoure +4 more
openaire +3 more sources
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
openaire +3 more sources
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
doaj +1 more source