Shaping Large Population Agent Behaviors Through Entropy-Regularized Mean-Field Games-Reference-Cited by-同舟云学术

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Shaping Large Population Agent Behaviors Through Entropy-Regularized Mean-Field Games

Published:2022-06-08 Issue: Volume: Page:
ISSN:
Container-title:2022 American Control Conference (ACC)
language:
Short-container-title:

Author:

Guan Yue¹,Zhou Mi²,Pakniyat Ali³,Tsiotras Panagiotis⁴

Affiliation:

1. Georgia Institute of Technology,School of Aerospace Enginnering,Atlanta,GA,USA

2. Georgia Institute of Technology,School of Electrical and Computer Engineering,Atlanta,GA,USA

3. University of Alabama,Department of Mechanical Engineering,Tuscaloosa,AL,USA

4. Georgia Institute of Technology,David & Andrew Lewis Chair Professor With the School of Aerospace Engineering,Atlanta,GA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9866948/9867142/09867358.pdf?arnumber=9867358

Reference21 articles.

1. Mean Field Games: Numerical Methods

2. Learning mean-field games;guo;NeurIPS,2019

3. Approximately solving mean field games via entropy-regularized deep reinforcement learning;cui;International Conference on Artificial Intelligence and Statistics,2021

4. Mean field multi-agent reinforcement learning;yang;International Conference on Machine Learning,2018

5. Q-learning in regularized mean-field games;anahtarci,2020

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