Free Access
Issue
ESAIM: COCV
Volume 27, 2021
Article Number 5
Number of page(s) 18
DOI https://doi.org/10.1051/cocv/2021003
Published online 03 March 2021
  1. T. Björk, M. Khapko and A. Murgoci, On time-inconsistent stochastic control in continuous time. Finance Stoch. 21 (2017) 331–360. [Google Scholar]
  2. F. Cherbonnier, Optimal insurance for time-inconsistent agents. Preprint (2016). [Google Scholar]
  3. M. Dodd, Obesity and time-inconsistent preferences. Obes. Res. Clin. Practice 2 (2008) 83–89. [Google Scholar]
  4. I. Ekeland and T.A. Pirvu, Investment and consumption without commitment. Math. Finan. Econ. 2 (2008) 57–86. [Google Scholar]
  5. I. Ekeland and A. Lazrak, The golden rule when preferences are time inconsistent. Math. Finan. Econ. 4 (2010) 29–55. [Google Scholar]
  6. I. Ekeland, O. Mbodji and T.A. Pirvu, Time-consistent portfolio management. SIAM J. Financ. Math. 3 (2012) 1–32. [Google Scholar]
  7. T.S. Findley and F.N. Caliendo, Short horizons, time inconsistency and optimal social security. Int. Tax & Public Finance 16 (2009) 487–513. [Google Scholar]
  8. T.S. Findley and J.A. Feigenbaum, Quasi-hyperbolic discounting and the existence of time-inconsistent retirement. Theor. Econ. Lett. 3 (2013) 119–123. [Google Scholar]
  9. S.L. Green, Time inconsistency, self-control, and remembrance. Faith Econ. 42 (2003) 51–60. [Google Scholar]
  10. S.R. Grenadier and N. Wang, Investment under uncertainty and time-inconsistent preferences. J. Financ. Econ. 84 (2007) 2–39. [Google Scholar]
  11. Y. Hu, H. Jin and X.Y. Zhou, Time-inconsistent stochastic linear–quadratic control. SIAM J. Control Optim. 50 (2012) 1548–1572. [Google Scholar]
  12. Y. Hu, H. Jin and X.Y. Zhou, Time-inconsistent stochastic linear–quadratic control: characterization and uniqueness of equilibrium. SIAM J. Control Optim. 55 (2017) 1261–1279. [Google Scholar]
  13. M. Huang, R.P. Malhamé and P.E. Caines, Large population stochastic dynamic games: closed-loop McKean-Vlasov systems and the Nash certainty equivalence principle. Commun. Inf. Syst. 6 (2006) 221–252. [Google Scholar]
  14. M. Huang, P.E. Caines and R.P. Malhamé, Large-population cost-coupled LQG problems with nonuniform agents: individual-mass behavior and decentralized-nash equilibria. IEEE Trans. Autom. Control 52 (2007) 1560–1571. [Google Scholar]
  15. M. Huang, P.E. Caines and R.P. Malhamé, The Nash Certainty Equivalence Principle and McKean-Vlasov Systems: an Invariance Principle and Entry Adaptation. 46th IEEE Conference on Decision and Control (2007) 121–123. [Google Scholar]
  16. M. Huang, P.E. Caines and R.P. Malhamé, An invariance principle in large population stochastic dynamic games. J. Syst. Sci. Complex. 20 (2007) 162–172. [Google Scholar]
  17. J.-M. Lasry and P.-L. Lions, Jeux champ moyen. I. Le cas stationnaire. C.R. Math. Acad. Sci. Paris 343 (2006) 619–625. [Google Scholar]
  18. J.-M. Lasry and P.-L. Lions, Jeux champ moyen. II. Horizon fini et contrle optimal. C.R. Math. Acad. Sci. Paris 343 (2006) 679–684. [Google Scholar]
  19. J.-M. Lasry and P.-L. Lions, Large investor trading impacts on volatility. Ann. Inst. Henri Poincaré Anal. Non Linaire 24 (2007) 311–323. [Google Scholar]
  20. J.-M. Lasry and P.-L. Lions, Mean field games. Jpn. J. Math. 2 (2007) 229–260. [Google Scholar]
  21. H. Mei and J. Yong, Equilibrium strategies for time-inconsistent stochastic switching systems. ESAIM: COCV 25 (2019) 64. [EDP Sciences] [Google Scholar]
  22. Y. Ni, J.Zhang and M. Krstic, Time-inconsistent mean-field stochastic LQ problem: open-loop time-consistent control. IEEE Trans. Autom. Control 63 (2018) 2771–2786. [Google Scholar]
  23. S.L. Nguyen, D.T. Nguyen and G. Yin, A stochastic maximum principle for switching diffusions using conditional mean-fields with applications to control problems. ESAIM: COCV 26 (2020) 69. [EDP Sciences] [Google Scholar]
  24. S. Nguyen, G. Yin and T. Hoang, On laws of large numbers for systems with mean-field interactions and Markovian switching. Stochastic Process. Appl. 130 (2020) 262–296. [Google Scholar]
  25. H. Pham and X. Wei, Bellman equation and viscosity solutions for mean-field stochastic control problem. ESAIM: COCV 24 (2018) 437–461. [CrossRef] [EDP Sciences] [Google Scholar]
  26. H. Pham and X. Wei, Dynamic programming for optimal control of Stochastic McKean–Vlasov dynamics. SIAM J. Control Optim. 55 (2017) 1069–1101. [Google Scholar]
  27. R.A. Pollak, Consistent planning. Rev. Econ. Stud. 35 (1968) 185–199. [Google Scholar]
  28. H. Wang, J. Sun and J. Yong, Recursive Utility Processes, Dynamic Risk Measures and Quadratic Backward Stochastic VolterraIntegral Equations. Appl. Math. Optim. (2019) 1–46. [Google Scholar]
  29. H. Wang and J. Yong, Time-inconsistent stochastic optimal control problems and back-ward stochastic volterra integral equations. Preprint arXiv:1911.04995 (2019). [Google Scholar]
  30. T. Wang, Characterizations of equilibrium controls in time inconsistent mean-field stochastic linear quadratic problems. I. Preprint arXiv:1802.01080 (2018). [Google Scholar]
  31. J. Wei, Time-inconsistent optimal control problems with regime switching. Math. Control Rel. Fields 7 (2017) 585–622. [Google Scholar]
  32. Q. Wei, J. Yong and Z. Yu, Time-inconsistent recrusive stochastic optimal control problems. SIAM J. Control Optim. 55 (2017) 4156–4201. [Google Scholar]
  33. W. Yan and J. Yong, Time-inconsistent optimal control problems and related issues. Modeling, Stochastic Control, Optimization, and Applications, edited by G. Yin., Q. Zhang. In Vol. 164 of The IMA Volumes in Mathematics and its Applications. Springer (2019) 533–569. [Google Scholar]
  34. G. Yin and Q. Zhang, Continuous-time Markov chains and applications: a singular perturbation approach. Vol. 37. Springer (2012). [Google Scholar]
  35. J. Yong, Time-inconsistent optimal control problems and the equilibrium HJB equation. Math. Control Relat. Fields 2 (2012) 271–329. [Google Scholar]
  36. J. Yong, Linear-quadratic optimal control problems for mean-field stochastic differential equations – time-consistent solutions. Trans. AMS 369 (2017) 5467–5523. [Google Scholar]

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