Discrete-time mean field partially observable controlled systems subject to common noise
DOI10.1007/s00245-017-9437-xzbMath1378.49013OpenAlexW2733047115MaRDI QIDQ1678478
Publication date: 17 November 2017
Published in: Applied Mathematics and Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00245-017-9437-x
discrete-time systemscommon noisepartial observationmean field gamemean field type stochastic control
Gaussian processes (60G15) Filtering in stochastic control theory (93E11) Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10) Optimal stochastic control (93E20) Discrete approximations in optimal control (49M25) Existence of optimal solutions to problems involving randomness (49J55) Stochastic difference equations (39A50)
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Cites Work
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- Linear-quadratic mean field games
- Mean field games with a dominating player
- Mean field games with common noise
- A maximum principle for SDEs of mean-field type
- A general stochastic maximum principle for SDEs of mean-field type
- Mean-field backward stochastic differential equations: A limit approach
- Mean field games. I: The stationary case
- Mean field games. II: Finite horizon and optimal control
- Mean field games
- Explicit solutions of some linear-quadratic mean field games
- Mean field games and systemic risk
- Large population stochastic dynamic games: closed-loop McKean-Vlasov systems and the Nash certainty equivalence principle
- On the rate of convergence for the mean-field approximation of controlled diffusions with large number of players
- Probabilistic Analysis of Mean-Field Games
- $\epsilon$-Nash Mean Field Game Theory for Nonlinear Stochastic Dynamical Systems with Major and Minor Agents
- Large Deviations for a Mean Field Model of Systemic Risk
- Mean Field Games and Applications
- A mean-field stochastic maximum principle via Malliavin calculus
- Large-Population LQG Games Involving a Major Player: The Nash Certainty Equivalence Principle
- Mean Field Games and Mean Field Type Control Theory
- Mean Field Stackelberg Games: Aggregation of Delayed Instructions
