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.
| Original language | English |
|---|---|
| Pages (from-to) | 231-245 |
| Number of pages | 15 |
| Journal | Journal of Optimization Theory and Applications |
| Volume | 168 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jan 2016 |
Keywords
- Dynamic optimization
- Forward–backward stochastic differential equation
- Large-population system
- Mean-field game
- Partial information
ASJC Scopus subject areas
- Control and Optimization
- Management Science and Operations Research
- Applied Mathematics