McKean–Vlasov optimal control: The dynamic programming principle
Author:
Affiliation:
1. École Polytechnique
2. Department of Mathematics, ETH Zürich
3. Department of Mathematics, The Chinese University of Hong Kong
Publisher
Institute of Mathematical Statistics
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Reference51 articles.
1. Carmona, R., Delarue, F. and Lachapelle, A. (2013). Control of McKean–Vlasov dynamics versus mean field games. Math. Financ. Econ. 7 131–166.
2. ALIPRANTIS, C. D. and BORDER, K. C. (2006). Infinite Dimensional Analysis: A Hitchhiker’s Guide, 3rd ed. Springer, Berlin.
3. BAYRAKTAR, E., COSSO, A., PHAM, H. and PHAM, H. (2018). Randomized dynamic programming principle and Feynman–Kac representation for optimal control of McKean–Vlasov dynamics. Trans. Amer. Math. Soc. 370 2115–2160.
4. BENSOUSSAN, A., FREHSE, J. and YAM, P. (2013). Mean Field Games and Mean Field Type Control Theory. SpringerBriefs in Mathematics. Springer, New York.
5. BENSOUSSAN, A., FREHSE, J. and YAM, S. C. P. (2015). The master equation in mean field theory. J. Math. Pures Appl. (9) 103 1441–1474.
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