Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/65659
Title: Backward mean-field Linear-Quadratic-Gaussian (LQG) games : full and partial information
Authors: Huang, J 
Wang, S
Wu, Z
Keywords: BSDE
decentralized control
Full information
Large-population system
Mean-field LQG games
Partial information
ϵ-Nash equilibrium
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on automatic control, 2016, v. 61, no. 12, 7386584, p. 3784-3796 How to cite?
Journal: IEEE transactions on automatic control 
Abstract: This paper introduces the backward mean-field (MF) linear-quadratic-Gaussian (LQG) games (for short, BMFLQG) of weakly coupled stochastic large-population system. In contrast to the well-studied forward mean-field LQG games, the individual state in our large-population system follows the backward stochastic differential equation (BSDE) whose terminal instead initial condition should be prescribed. Two classes of BMFLQG games are discussed here and their decentralized strategies are derived through the consistency condition. In the first class, the individual agents of large-population system are weakly coupled in their state dynamics and the full information can be accessible to all agents. In the second class, the coupling structure lies in the cost functional with only partial information structure. In both classes, the asymptotic near-optimality property (namely, ?-Nash equilibrium) of decentralized strategies are verified. To this end, some estimates to BSDE, are presented in the large-population setting.
URI: http://hdl.handle.net/10397/65659
ISSN: 0018-9286
EISSN: 1558-2523
DOI: 10.1109/TAC.2016.2519501
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