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This paper employs a policy iteration reinforcement learning (RL) method to study continuous-time linear-quadratic mean-field control problems in infinite horizon.
M. L. Minsky, “Theory of neural-analog reinforcement systems and its application to the brain model problem,” Ph.D. dissertation, Princeton University, 1954
1954
Earlier work this paper cites.
J. M. Bismut, “Linear quadratic optimal control with random coefficients,”
1976
Earlier work this paper cites.
S. Bittanti, A. J. Laub, and J. C. Willems,
1991
Earlier work this paper cites.
S. J. Bradtke, B. E. Ydestie and A. G. Barto, “Adaptive linear quadratic control using policy iteration,” in Proc. Amer. Control Conf., pp. 3475-3476, 1994
1994
Earlier work this paper cites.
1999
Earlier work this paper cites.
M. Ait Rami and X. Y. Zhou, “Linear matrix inequalities, Riccati equations, and indefinite stochastic linear quadratic controls”,
2000
Earlier work this paper cites.
J. J. Murray, C. J. Cox, G. G. Lendaris and R. Saeks, “Adaptive dynamic programming”,
2002
Earlier work this paper cites.
M. Huang, P. E. Caines and Malhamé, R. P., “Large-population cost-coupled LQG problems with nonuniform agents: Individual-mass behavior and decentralized
2007
Earlier work this paper cites.
J. M. Lasry and P. L. Lions, “Mean field games”,
2007
Earlier work this paper cites.
F. L. Lewis, D. Vrabie and K. G. Vamvoudakis, “Reinforcement learning and Feedback Control”,
2012
Cited alongside, same era.
A. Bensoussan, J. Frehse and P. Yam,
2013
Cited alongside, same era.
J. Yong, “Linear-quadratic optimal control problems for mean-field stochastic differential equations”,
2013
Cited alongside, same era.
J. Huang, X. Li and J, Yong, “A Linear-quadratic optimal control problem for mean-field stochastic differential equations in infinite horizon”,
2015
Cited alongside, same era.
T. Bian, Y. Jiang and Z. P. Jiang, “Adaptive dynamic programming for stochastic systems with state and control dependent noise”,
2016
Cited alongside, same era.
J. Yong, “Linear-quadratic optimal control problems for mean-field stochastic differential equations-time-consistent solutions”,
H. Wang and X. Y. Zhou, “Continuous-time mean–variance portfolio selection: A reinforcement learning framework”,
2020
Later among the works it cites.
X. Li, J. Shi and J. Yong, “Mean-field linear-quadratic stochastic differential games in an infinite horizon”,
2021
Later among the works it cites.
S. Perrin, M. Laurière, J. Pérolat, M. Geist, R. Élie, O. Pietquin. “Mean Field Games Flock! The Reinforcement Learning Way”,
2021
Later among the works it cites.
X. Chen, G. Qu, Y. Tang, S. Low and N. Li, “Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges”,
2022
Later among the works it cites.
K. Du, Q. Meng and F. Zhang, “A Q-learning algorithm for discrete-time linear-quadratic control with random parameters of unknown distribution: Convergence and stabilization”, vol. 60, pp.1991-2015, 2022
2022
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2017
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2018
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R. Élie, J. Pérolat, M. Laurière, M. Geist, and O. Pietquin, “On the Convergence of Model Free Learning in Mean Field Games”,
2020
Cited alongside, same era.
H. Wang, T. Zariphopoulou and X. Y. Zhou, “Reinforcement learning in continuous time and space: A stochastic control approach”,
2020
Cited alongside, same era.
Later among the works it cites.
X. Gao, Z. Q. Xu and X. Y. Zhou, “State-dependent temperature control for Langevin diffusions”,
2022
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M. Laurière, S. Perrin, S. Girgin, P. Muller, A. Jain, T. Cabannes, G. Piliouras, J. Pérolat, R. Élie, O. Pietquin, and M. Geist, “Scalable Deep Reinforcement Learning Algorithms for Mean Field Games”,
2022
Later among the works it cites.
N. Li, X. Li, J. Peng and Z. Q. Xu, “Stochastic linear quadratic optimal control problem: A reinforcement learning method”,
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Later among the works it cites.
Z. Xu, T. Shen, and M. Huang. “Model-free policy iteration approach to NCE-based strategy design for linear quadratic Gaussian games”,
2023
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