Risk-Sensitive Mean-Field Type Control Under Partial Observation

DOI10.1007/978-3-319-23425-0_9zbMath1334.93180arXiv1411.7231OpenAlexW2963293760WikidataQ69037720 ScholiaQ69037720MaRDI QIDQ2801796

Hamidou Tembine, Boualem Djehiche

Publication date: 22 April 2016

Published in: Stochastics of Environmental and Financial Economics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1411.7231

zbMATH Keywords

maximum principlerisk-sensitive controlpartial observationmean-field SDEtime inconsistent control

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Optimal stochastic control (93E20) Applications of stochastic analysis (to PDEs, etc.) (60H30) Financial applications of other theories (91G80) Optimality conditions for problems involving randomness (49K45)

Related Items (14)

Necessary conditions for partially observed optimal control of general McKean–Vlasov stochastic differential equations with jumps ⋮ Linear-quadratic mean-field-type games: a direct method ⋮ A stochastic maximum principle for partially observed optimal control problem of McKean-Vlasov FBSDEs with random jumps ⋮ Partially observed discrete-time risk-sensitive mean field games ⋮ Risk-sensitive mean-field-type games with \(L^p\)-norm drifts ⋮ On partially observed optimal singular control of McKean–Vlasov stochastic systems: Maximum principle approach ⋮ Berge equilibrium in linear-quadratic mean-field-type games ⋮ Linear‐Quadratic Optimal Control Problems for Mean‐Field Stochastic Differential Equations with Jumps ⋮ Stochastic maximum principle for partially observed optimal control problems of general McKean-Vlasov differential equations ⋮ Approximate Markov-Nash Equilibria for Discrete-Time Risk-Sensitive Mean-Field Games ⋮ A maximum principle for mean-field stochastic control system with noisy observation ⋮ Mean Field Control and Mean Field Game Models with Several Populations ⋮ Mean-field-type games ⋮ Mean-Field Controls with Q-Learning for Cooperative MARL: Convergence and Complexity Analysis

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