Paper Info
Title
Backward Mean-Field Linear-Quadratic-Gaussian (LQG) Games: Full and Partial Information.
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, $\epsilon$- Nash equilibrium) of decentralized strategies are verified. To this end, some estimates to BSDE, are presented in the large-population setting.
Year
DOI
Venue
2016
10.1109/TAC.2016.2519501
IEEE Trans. Automat. Contr.
Keywords
Field
DocType
Sociology,Statistics,Games,Couplings,Optimal control,Differential equations,Optimization
Information structure,Differential equation,Mathematical optimization,Optimal control,Decentralised system,Linear-quadratic-Gaussian control,Control theory,Stochastic differential equation,Initial value problem,Nash equilibrium,Mathematics
Journal
Volume
Issue
ISSN
61
12
0018-9286
Citations 
PageRank 
References 
3
0.38
8
Authors
3
Name
Order
Citations
PageRank
Jianhui Huang18114.20
Shujun Wang2143.36
Zhen Wu3237.12