AbstractThis paper studies the convergence of value-iteration functions and the existence of error bounds for rolling horizon procedures in discrete-time Markov control processes with Borel state and control spaces, and unbounded reward functions with a discount factor
AbstractWe consider an approximation scheme for solving Markov decision processes (MDPs) with counta...
summary:This work analyzes a discrete-time Markov Control Model (MCM) on Borel spaces when the perfo...
summary:The present paper studies the approximate value iteration (AVI) algorithm for the average co...
This paper is concerned with the links between the Value Iteration algorithm and the Rolling Horizon...
This paper shows the convergence of the value iteration (or successive approximations) algorithm for...
We study the behavior of the rolling horizon procedure for semi-Markov decision processes, with infi...
International audienceWe study the behaviour of the rolling horizon procedure for the case of two-pe...
Using the value iteration procedure for discrete-time Markov con-trol processes on general Borel spa...
This work considers denumerable state Markov Decision Chains endowed with a long-run expected averag...
We study the properties of the rolling horizon and the approximate rolling horizon procedures for th...
International audienceWe deal with the average criterion on Markov Decision Processes (MDP) to evalu...
International audienceWe consider a discrete-time Markov decision process with Borel state and actio...
AbstractConsiderable numerical experience indicates that the standard value iteration procedure for ...
We consider the problem of approximating the values and the optimal policies in risk-averse discount...
In this work, we deal with a discrete-time infinite horizon Markov decision process with locally com...
AbstractWe consider an approximation scheme for solving Markov decision processes (MDPs) with counta...
summary:This work analyzes a discrete-time Markov Control Model (MCM) on Borel spaces when the perfo...
summary:The present paper studies the approximate value iteration (AVI) algorithm for the average co...
This paper is concerned with the links between the Value Iteration algorithm and the Rolling Horizon...
This paper shows the convergence of the value iteration (or successive approximations) algorithm for...
We study the behavior of the rolling horizon procedure for semi-Markov decision processes, with infi...
International audienceWe study the behaviour of the rolling horizon procedure for the case of two-pe...
Using the value iteration procedure for discrete-time Markov con-trol processes on general Borel spa...
This work considers denumerable state Markov Decision Chains endowed with a long-run expected averag...
We study the properties of the rolling horizon and the approximate rolling horizon procedures for th...
International audienceWe deal with the average criterion on Markov Decision Processes (MDP) to evalu...
International audienceWe consider a discrete-time Markov decision process with Borel state and actio...
AbstractConsiderable numerical experience indicates that the standard value iteration procedure for ...
We consider the problem of approximating the values and the optimal policies in risk-averse discount...
In this work, we deal with a discrete-time infinite horizon Markov decision process with locally com...
AbstractWe consider an approximation scheme for solving Markov decision processes (MDPs) with counta...
summary:This work analyzes a discrete-time Markov Control Model (MCM) on Borel spaces when the perfo...
summary:The present paper studies the approximate value iteration (AVI) algorithm for the average co...
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