Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33451
Title: Dynamic Optimization of Large-Population Systems with Partial Information
Authors: Huang, J 
Wang, S
Keywords: Dynamic optimization
Forward–backward stochastic differential equation
Large-population system
Mean-field game
Partial information
Issue Date: 2015
Publisher: Springer New York LLC
Source: Journal of optimization theory and applications, 2015 How to cite?
Journal: Journal of Optimization Theory and Applications 
Abstract: We consider the dynamic optimization of large-population system with partial information. The associated mean-field game is formulated, and its consistency condition is equivalent to the wellposedness of some Riccati equation system. The limiting state-average is represented by a mean-field stochastic differential equation driven by the common Brownian motion. The decentralized strategies with partial information are obtained, and the approximate Nash equilibrium is verified.
URI: http://hdl.handle.net/10397/33451
ISSN: 0022-3239
DOI: 10.1007/s10957-015-0740-x
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