Dynamic Programming Deconstructed: Transformations of the Bellman Equation and Computational Efficiency

Published Online:https://doi.org/10.1287/opre.2020.2006

References

  • Bagger J , Fontaine F , Postel-Vinay F , Robin JM (2014) Tenure, experience, human capital, and wages: A tractable equilibrium search model of wage dynamics. Amer. Econom. Rev. 104(6):1551–1596.CrossrefGoogle Scholar
  • Bäuerle N , Jaśkiewicz A (2018) Stochastic optimal growth model with risk sensitive preferences. J. Econom. Theory 173:181–200.CrossrefGoogle Scholar
  • Bellman R (1957) Dynamic Programming (Princeton University Press, New York).Google Scholar
  • Bertsekas DP (2012) Dynamic Programming and Optimal Control , vol. 2, 4th ed. (Athena Scientific, Massachusetts).Google Scholar
  • Bertsekas DP (2013) Abstract Dynamic Programming (Athena Scientific, Belmont, MA).Google Scholar
  • Bertsekas DP , Yu H (2012) Q-learning and enhanced policy iteration in discounted dynamic programming. Math. Oper. Res. 37(1):66–94.LinkGoogle Scholar
  • Bidder RM , Smith ME (2012) Robust animal spirits. J. Monetary Econom. 59(8):738–750.CrossrefGoogle Scholar
  • Bloise G , Vailakis Y (2018) Convex dynamic programming with (bounded) recursive utility. J. Econom. Theory 173:118–141.CrossrefGoogle Scholar
  • Dixit AK , Pindyck RS (1994) Investment Under Uncertainty (Princeton University Press, Princeton, NJ).CrossrefGoogle Scholar
  • Hansen LP , Sargent TJ (2008) Robustness (Princeton University Press, Princeton, NJ).CrossrefGoogle Scholar
  • Iyengar GN (2005) Robust dynamic programming. Math. Oper. Res. 30(2):257–280.LinkGoogle Scholar
  • Kellogg R (2014) The effect of uncertainty on investment: Evidence from Texas oil drilling. Amer. Econom. Rev. 104(6):1698–1734.CrossrefGoogle Scholar
  • Kochenderfer MJ (2015) Decision Making Under Uncertainty: Theory and Application (MIT Press, Cambridge, MA).CrossrefGoogle Scholar
  • Kristensen D , Mogensen P , Moon JM , Schjerning B (2018) Solving dynamic discrete choice models using smoothing and sieve methods. Technical report, University of Copenhagen, Copenhagen.Google Scholar
  • Livshits I , MacGee J , Tertilt M (2007) Consumer bankruptcy: A fresh start. Amer. Econom. Rev. 97(1):402–418.CrossrefGoogle Scholar
  • Low H , Meghir C , Pistaferri L (2010) Wage risk and employment risk over the life cycle. Amer. Econom. Rev. 100(4):1432–1467.CrossrefGoogle Scholar
  • Marinacci M , Montrucchio L (2010) Unique solutions for stochastic recursive utilities. J. Econom. Theory 145(5):1776–1804.CrossrefGoogle Scholar
  • McCall JJ (1970) Economics of information and job search. Quart. J. Econom. 84(1):113–126.CrossrefGoogle Scholar
  • Monahan GE (1980) Optimal stopping in a partially observable Markov process with costly information. Oper. Res. 28(6):1319–1334.LinkGoogle Scholar
  • Munos R , Szepesvári C (2008) Finite-time bounds for fitted value iteration. J. Machine Learn. Res. 9(May):815–857.Google Scholar
  • Peskir G , Shiryaev A (2006) Optimal Stopping and Free-Boundary Problems (Springer, Berlin).Google Scholar
  • Powell WB (2007) Approximate Dynamic Programming: Solving the Curses of Dimensionality (John Wiley & Sons, Hoboken, NJ).CrossrefGoogle Scholar
  • Puterman ML , Shin MC (1982) Action elimination procedures for modified policy iteration algorithms. Oper. Res. 30(2):301–318.LinkGoogle Scholar
  • Rust J (1987) Optimal replacement of GMC bus engines: An empirical model of Harold Zurcher. Econometrica 55(5):999–1033.CrossrefGoogle Scholar
  • Rust J (1994) Structural estimation of Markov decision processes. Engle RF, McFadden DL, eds. Handbook of Econometrics, vol. 4 (Elsevier, Amsterdam), 3081–3143.Google Scholar
  • Rust J (1996) Numerical dynamic programming in economics. Amman H, Kendrick D, Rust J. Handbook of Computational Economics, vol. 1 (Elsevier, North-Holland, Amsterdam), 619–729.Google Scholar
  • Ruszczyński A (2010) Risk-averse dynamic programming for Markov decision processes. Math. Programming 125(2):235–261.CrossrefGoogle Scholar
  • Skiena SS (2008) The Algorithm Design Manual (Springer, London).CrossrefGoogle Scholar
  • Tauchen G (1986) Finite state Markov-chain approximations to univariate and vector autoregressions. Econom. Lett. 20(2):177–181.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.