Multiagent Reinforcement Learning for Integrated Network: Applying to a Part of the Road Network of Krasnoyarsk City-Reference-Cited by-同舟云学术

Multiagent Reinforcement Learning for Integrated Network: Applying to a Part of the Road Network of Krasnoyarsk City

Published:2022-10-12 Issue: Volume: Page:
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Container-title:2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT)
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Author:

Tislenko Timofei I.¹,Semenova Daria V.¹,Sergeeva Nataly A.²,Goldenok Elena E.³,Kononova Nadezhda V.⁴

Affiliation:

1. Siberian Federal University,School of Mathematics and Computer Science,Krasnoyarsk,Russian Federation

2. LLC «R.D.Science»,Analytics Groups,Krasnoyarsk,Russian Federation

3. Krasnoyarsk State Medical University Named After Professor V.F. Voyno- Yasenetsky Name of Organization,Department of Medical Cybernetics and Informatics,Krasnoyarsk,Russian Federation

4. Siberian Federal University,School of Space and Information Technology,Krasnoyarsk,Russian Federation

Funder

Ministry of Science and Higher Education of the Russian Federation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10013483/10013493/10013610.pdf?arnumber=10013610

Reference21 articles.

1. Multi-agent reinforcement learning: Amodular approach;ono;Proc 2nd Int Conf Multi-Agent Syst,1996

2. Multi-Agent Q-Learning with Joint State Value Approximation;chen;Proceedings of the 30th Chinese Control Conference,2011

3. Reinforcement Learning: An Introduction;sutton;Massachusetts London,2015

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