Add to ORKGIn this note, we consider discrete-time Markov decision processes with finite state space. Recalling explicit formulas for the growth rate of expected value and variance of the cumulative (random) reward, algorithmic procedures for finding optimal policies with respect to various mean variance optimality criteria are discussed. Computational experience with large scale numerical examples is reported
We consider Markov reward processes with finite state space both in discrete- and continuous-time se...
We develop the asymptotic variance for Markov decision processes. Results are provided to express th...
This paper is concerned with the averagevariance of Markov decision processes with countable states ...
We consider finite horizon Markov decision processes under performance measures that involve both th...
summary:This paper deals with a first passage mean-variance problem for semi-Markov decision process...
In this note, we compare two aproaches for handling risk-variability features arising in discrete-ti...
summary:The article is devoted to Markov reward chains in discrete-time setting with finite state sp...
We consider a discrete time Markov reward process with finite state and action spaces and random ret...
AbstractWe consider the optimization of the variance of the sum of costs as well as that of an avera...
In this note we consider continuous-time Markov decision processes with finite state and actions spa...
Semi-Markov decision processes can be considered as an extension of discrete- and continuous-time M...
summary:In this note we focus attention on identifying optimal policies and on elimination suboptima...
Time-average Markov decision problems are considered for the finite state and action spaces. Several...
We consider finite horizon Markov decision processes under performance measures that involve both th...
We study the complexity of central controller synthesis problems for finite-state Markov decision pr...
We consider Markov reward processes with finite state space both in discrete- and continuous-time se...
We develop the asymptotic variance for Markov decision processes. Results are provided to express th...
This paper is concerned with the averagevariance of Markov decision processes with countable states ...
We consider finite horizon Markov decision processes under performance measures that involve both th...
summary:This paper deals with a first passage mean-variance problem for semi-Markov decision process...
In this note, we compare two aproaches for handling risk-variability features arising in discrete-ti...
summary:The article is devoted to Markov reward chains in discrete-time setting with finite state sp...
We consider a discrete time Markov reward process with finite state and action spaces and random ret...
AbstractWe consider the optimization of the variance of the sum of costs as well as that of an avera...
In this note we consider continuous-time Markov decision processes with finite state and actions spa...
Semi-Markov decision processes can be considered as an extension of discrete- and continuous-time M...
summary:In this note we focus attention on identifying optimal policies and on elimination suboptima...
Time-average Markov decision problems are considered for the finite state and action spaces. Several...
We consider finite horizon Markov decision processes under performance measures that involve both th...
We study the complexity of central controller synthesis problems for finite-state Markov decision pr...
We consider Markov reward processes with finite state space both in discrete- and continuous-time se...
We develop the asymptotic variance for Markov decision processes. Results are provided to express th...
This paper is concerned with the averagevariance of Markov decision processes with countable states ...