We study the asymptotic optimal control of multi-class restless bandits. A restless bandit is a controllable stochastic process whose state evolution depends on whether or not the bandit …
A Piunovskiy, Y Zhang - Probability Theory and Stochastic Modelling, 2020 - Springer
The study of continuous-time Markov decision processes dates back at least to the 1950s, shortly after that of its discrete-time analogue. Since then, the theory has rapidly developed …
In this paper, we discuss the dynamic server control in a two-class service system with abandonments. Two models are considered. In the first case, rewards are received upon …
MK Ghosh, S Saha - … An International Journal of Probability and …, 2014 - Taylor & Francis
We study risk-sensitive control of continuous time Markov chains taking values in discrete state space. We study both finite and infinite horizon problems. In the finite horizon problem …
The intent of this book is to present recent results in the control theory for the longrun average continuous control problem of Piecewise Deterministic Markov Processes (PDMPs) …
X Guo, A Piunovskiy - Mathematics of Operations Research, 2011 - pubsonline.informs.org
This paper deals with denumerable continuous-time Markov decision processes (MDP) with constraints. The optimality criterion to be minimized is expected discounted loss, while …
Uniformization, also referred to as randomization, is a well-known performance evaluation technique to model and analyse continuous-time Markov chains via an easier to …
A Piunovskiy, Y Zhang - SIAM journal on control and optimization, 2011 - SIAM
This paper deals with constrained discounted continuous-time Markov decision processes, also known as controlled jump Markov processes, with Borel state and action spaces. Under …
This book concerns continuous-time controlled Markov chains, also known as continuous- time Markov decision processes. They form a class of stochastic control problems in which a …