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 nonlinear discount function. Our approach is in spirit of the von NeumannMorgenstern 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 nonstationary 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 

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.unimuenchen.de/id/eprint/31755 