Add to ORKGWe consider Markov reward processes with finite state space both in discrete- and continuous-time setting. Explicit formulas for the second moment and variance of the cumulative (random) reward up to a given time point are obtained
summary:The article is devoted to Markov reward chains in discrete-time setting with finite state sp...
In this thesis, the problem of computing the cumulative distribution function (cdf) of the random ti...
We discuss using the semi-regenerative method, importance sampling, and stratification to estimate t...
In this note, we consider discrete-time Markov decision processes with finite state space. Recalling...
We analyze the moments of the accumulated reward over the interval (0, t) in a continuous-time Marko...
We consider the variance of the reward until absorption in a Markov chain. This variance is usually ...
We consider a discrete time Markov reward process with finite state and action spaces and random ret...
International audienceWe analyze the moments of the accumulated reward over the interval (0,t) in a ...
AbstractTime Markov decision processes with countable states and actions continuous are discussed wi...
Semi-Markov decision processes can be considered as an extension of discrete- and continuous-time M...
This thesis attempts to bring together two different approaches to the modeling of event driven syst...
Power moments for accumulated rewards defined on Markov and semi-Markov chains are studied. A model ...
In this paper we consider the Markov decision process with finite state and action spaces at the cri...
In this paper, a full treatment of homogeneous discrete time Markov reward processes is presented. T...
In this paper we consider discounted Markov decision processes with finite state space and compact a...
summary:The article is devoted to Markov reward chains in discrete-time setting with finite state sp...
In this thesis, the problem of computing the cumulative distribution function (cdf) of the random ti...
We discuss using the semi-regenerative method, importance sampling, and stratification to estimate t...
In this note, we consider discrete-time Markov decision processes with finite state space. Recalling...
We analyze the moments of the accumulated reward over the interval (0, t) in a continuous-time Marko...
We consider the variance of the reward until absorption in a Markov chain. This variance is usually ...
We consider a discrete time Markov reward process with finite state and action spaces and random ret...
International audienceWe analyze the moments of the accumulated reward over the interval (0,t) in a ...
AbstractTime Markov decision processes with countable states and actions continuous are discussed wi...
Semi-Markov decision processes can be considered as an extension of discrete- and continuous-time M...
This thesis attempts to bring together two different approaches to the modeling of event driven syst...
Power moments for accumulated rewards defined on Markov and semi-Markov chains are studied. A model ...
In this paper we consider the Markov decision process with finite state and action spaces at the cri...
In this paper, a full treatment of homogeneous discrete time Markov reward processes is presented. T...
In this paper we consider discounted Markov decision processes with finite state space and compact a...
summary:The article is devoted to Markov reward chains in discrete-time setting with finite state sp...
In this thesis, the problem of computing the cumulative distribution function (cdf) of the random ti...
We discuss using the semi-regenerative method, importance sampling, and stratification to estimate t...