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In this paper, we investigate the concentration properties of cumulative reward in Markov Decision Processes (MDPs), focusing on both asymptotic and non-asymptotic settings. We introduce a unified approach to characterize reward…

Machine Learning · Computer Science 2025-12-04 Borna Sayedana , Peter E. Caines , Aditya Mahajan

In this article, we consider a continuous review (s, S) inventory system with failures of demand fulfillment (service) modeled as a Markov-modulated retrial queueing system. The inventory system features a single product that experiences…

Probability · Mathematics 2023-07-18 James Cordeiro , Ying-Ju Chen , Andres Larrain-Hubach , Mark Abramson

This paper studies the effect of an overdispersed arrival process on the performance of an infinite-server system. In our setup, a random environment is modeled by drawing an arrival rate $\Lambda$ from a given distribution every $\Delta$…

Probability · Mathematics 2016-02-02 Mariska Heemskerk , Johan van Leeuwaarden , Michel Mandjes

We introduce the Markov Distributional Conformal Prediction (MDCP) method that extends the distributional conformal prediction (previously developed for regression) to the setting of a strictly stationary Markov process. Instead of relying…

Methodology · Statistics 2026-05-26 Dehao Dai , Kejin Wu , Dimitris N. Politis

The polling system with switch-over durations is a useful model with several practical applications. It is classified as a Discrete Event Dynamic System (DEDS) for which no one agreed upon modelling approach exists. Furthermore, DEDS are…

Optimization and Control · Mathematics 2021-12-14 Dylan Solms

To perform a queuing analysis or design in a communications context, we need to estimate the values of the input parameters, specifically the mean of the arrival rate and service time. In this paper, we propose an approach for estimating…

Applications · Statistics 2008-02-26 Xinjia Chen

We study a system, where a random flow of customers is served by servers (called agents) invited on-demand. Each invited agent arrives into the system after a random time; after each service completion, an agent returns to the system or…

Probability · Mathematics 2017-11-28 Lam M. Nguyen , Alexander Stolyar

We investigate the parameter recovery of Markov-switching ordinary differential processes from discrete observations, where the differential equations are nonlinear additive models. This framework has been widely applied in biological…

Methodology · Statistics 2025-01-03 Katherine Tsai , Mladen Kolar , Sanmi Koyejo

We study the synthesis of mode switching protocols for a class of discrete-time switched linear systems in which the mode jumps are governed by Markov decision processes (MDPs). We call such systems MDP-JLS for brevity. Each state of the…

Systems and Control · Electrical Eng. & Systems 2020-01-06 Bo Wu , Murat Cubuktepe , Franck Djeumou , Zhe Xu , Ufuk Topcu

In this paper, we consider a queue-aware distributive resource control algorithm for two-hop MIMO cooperative systems. We shall illustrate that relay buffering is an effective way to reduce the intrinsic half-duplex penalty in cooperative…

Machine Learning · Computer Science 2015-05-20 Rui Wang , Vincent K. N. Lau , Ying Cui

We prove two Large deviations principles (LDP) in the zone of moderate deviation probabilities. First we establish LDP for the conditional distributions of moderate deviations of empirical bootstrap measures given empirical probability…

Statistics Theory · Mathematics 2014-05-22 Mikhail Ermakov

Consider a queueing system fed by traffic from $N$ independent and identically distributed marked point processes. We establish several novel sample path large deviations results in the scaled uniform topology for such a system with a small…

Probability · Mathematics 2019-12-11 James R. Cruise , Fraser Daly , Bemsibom Toh

Markov decision processes (MDPs) are a standard model for sequential decision-making problems and are widely used across many scientific areas, including formal methods and artificial intelligence (AI). MDPs do, however, come with the…

Artificial Intelligence · Computer Science 2024-12-11 Marnix Suilen , Thom Badings , Eline M. Bovy , David Parker , Nils Jansen

The paper studies a multiserver retrial queueing system with $m$ servers. Arrival process is a point process with strictly stationary and ergodic increments. A customer arriving to the system occupies one of the free servers. If upon…

Probability · Mathematics 2021-07-01 Vyacheslav M. Abramov

We consider a load balancing model where a Poisson stream of jobs arrive at a system of many servers whose service time distribution possesses a finite second moment. A small fraction of arrivals pass through the so called power-of-choice…

Probability · Mathematics 2024-04-16 Rami Atar , Gershon Wolansky

Robust Markov Decision Processes (MDPs) are receiving much attention in learning a robust policy which is less sensitive to environment changes. There are an increasing number of works analyzing sample-efficiency of robust MDPs. However,…

Machine Learning · Statistics 2023-09-13 Wenhao Yang , Han Wang , Tadashi Kozuno , Scott M. Jordan , Zhihua Zhang

The purpose of this paper is to investigate the deviation inequalities and the moderate deviation principle of the least squares estimators of the unknown parameters of general $p$th-order bifurcating autoregressive processes, under…

Probability · Mathematics 2012-04-12 Hacène Djellout , Valère Bitseki Penda

We consider a fading point-to-point link with packets arriving randomly at rate $\lambda$ per slot to the transmitter queue. We assume that the transmitter can control the number of packets served in a slot by varying the transmit power for…

Networking and Internet Architecture · Computer Science 2013-09-24 Vineeth B. S. , Utpal Mukherji

We study a queueing network with a single shared server that serves the queues in a cyclic order. External customers arrive at the queues according to independent Poisson processes. After completing service, a customer either leaves the…

Probability · Mathematics 2014-08-04 Marko Boon , Rob van der Mei , Erik Winands

Interval Markov Decision Processes (IMDPs) are finite-state uncertain Markov models, where the transition probabilities belong to intervals. Recently, there has been a surge of research on employing IMDPs as abstractions of stochastic…

Systems and Control · Electrical Eng. & Systems 2026-02-18 Giannis Delimpaltadakis , Morteza Lahijanian , Manuel Mazo , Luca Laurenti
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