Jaśkiewicz, Anna and Matkowski, Janusz and Nowak, Andrzej S.
(2011):
*Persistently optimal policies in stochastic dynamic programming with generalized discounting.*

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## Abstract

In this paper we study a Markov decision process with a non-linear discount function. Our approach is in spirit of the von Neumann-Morgenstern concept and is based on the notion of expectation. First, we define a utility on the space of trajectories of the process in the finite and infinite time horizon and then take their expected values. It turns out that the associated optimization problem leads to a non-stationary dynamic programming and an infinite system of Bellman equations, which result in obtaining persistently optimal policies. Our theory is enriched by examples.

Item Type: | MPRA Paper |
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Original Title: | Persistently optimal policies in stochastic dynamic programming with generalized discounting |

English Title: | Persistently Optimal Policies in Stochastic Dynamic Programming with Generalized Discounting |

Language: | English |

Keywords: | Stochastic dynamic programming, Persistently optimal policies, Variable discounting, Bellman equation, Resource extraction, Growth theory |

Subjects: | D - Microeconomics > D9 - Intertemporal Choice > D90 - General C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis |

Item ID: | 31755 |

Depositing User: | Andrzej Nowak |

Date Deposited: | 21 Jun 2011 20:29 |

Last Modified: | 06 Oct 2019 21:56 |

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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/31755 |