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We consider the control of a Markov decision process (MDP) that undergoes an abrupt change in its transition kernel (mode). We formulate the problem of minimizing regret under control-switching based on mode change detection, compared to a…

Systems and Control · Electrical Eng. & Systems 2022-10-11 Nathan Dahlin , Subhonmesh Bose , Venugopal V. Veeravalli

We consider a piecewise deterministic Markov decision process, where the expected exponential utility of total (nonnegative) cost is to be minimized. The cost rate, transition rate and post-jump distributions are under control. The state…

Optimization and Control · Mathematics 2017-11-22 Xin Guo , Yi Zhang

Many driven systems alternate between bursts of activity and quiescence and can become trapped in an absorbing state, such as complete inactivity in reaction-diffusion processes or extinction in predator-prey dynamics. It is generally…

Statistical Mechanics · Physics 2026-05-14 Kartik Chhajed , P. K. Mohanty

A short proof is given of a necessary and sufficient condition for the normalized occupation measure of a L\'evy process in a metrizable compact group to be asymptotically uniform with probability one.

Probability · Mathematics 2011-09-16 Arno Berger , Steven N. Evans

This paper discusses the functional stability of closed-loop Markov Chains under optimal policies resulting from a discounted optimality criterion, forming Markov Decision Processes (MDPs). We investigate the stability of MDPs in the sense…

Systems and Control · Electrical Eng. & Systems 2022-04-01 Arash Bahari Kordabad , Sebastien Gros

Many problems in sequential decision making and stochastic control often have natural multiscale structure: sub-tasks are assembled together to accomplish complex goals. Systematically inferring and leveraging hierarchical structure,…

Artificial Intelligence · Computer Science 2012-12-06 Jake Bouvrie , Mauro Maggioni

We consider Markov decision processes (MDPs) with unknown disturbance distribution and address this problem using the robust Markov decision process (RMDP) approach. We construct the empirical distribution of the unknown disturbance…

Optimization and Control · Mathematics 2026-03-11 Sivaramakrishnan Ramani

Analysis of Markov Decision Processes (MDP) is often hindered by state space explosion. Abstraction is a well-established technique in model checking to mitigate this issue. This paper presents a novel lazy abstraction method for MDP…

Logic in Computer Science · Computer Science 2024-06-04 Dániel Szekeres , Kristóf Marussy , István Majzik

In many practical settings control decisions must be made under partial/imperfect information about the evolution of a relevant state variable. Partially Observable Markov Decision Processes (POMDPs) is a relatively well-developed framework…

Machine Learning · Computer Science 2021-12-30 Yanling Chang , Alfredo Garcia , Zhide Wang , Lu Sun

This study focuses on solving the numerical challenges of imposing absorbing boundary conditions for dynamic simulations in the material point method (MPM). To attenuate elastic waves leaving the computational domain, the current work…

Geophysics · Physics 2025-01-24 Jun Kurima , Bodhinanda Chandra , Kenichi Soga

This article is concerned with moderate deviation principles of a general class of mean eld type interacting particle models. We discuss functional moderate deviations of the occupation measures for both the strong -topology on the space of…

Probability · Mathematics 2012-04-17 Pierre Del Moral , Shulan Hu , Liming Wu

In this paper, we propose a compositional approach for the construction of finite abstractions (a.k.a. finite Markov decision processes (MDPs)) for networks of discrete-time stochastic control subsystems that are not necessarily…

Systems and Control · Electrical Eng. & Systems 2020-02-12 Abolfazl Lavaei , Sadegh Soudjani , Majid Zamani

In Markov Decision Processes (MDPs) with intermittent state information, decision-making becomes challenging due to periods of missing observations. Linear programming (LP) methods can play a crucial role in solving MDPs, in particular,…

Optimization and Control · Mathematics 2025-09-09 Konstantin Avrachenkov , Madhu Dhiman , Veeraruna Kavitha

In this paper, we explore a topological system $f:M\rightarrow M$ with average shadowing property. We extend Sigmund's results and show that every non-empty, compact and connected subset $V\subseteq\mathcal {M}_{inv}(f)$ coincides with…

Dynamical Systems · Mathematics 2015-11-20 Yiwei Dong , Xueting Tian , Xiaoping Yuan

We study the quasi-stationary behavior of multidimensional processes absorbed when one of the coordinates vanishes. Our results cover competitive or weakly cooperative Lotka-Volterra birth and death processes and Feller diffusions with…

Probability · Mathematics 2019-10-10 Nicolas Champagnat , Denis Villemonais

Packing topological entropy is a dynamical analogy of the packing dimension, which can be viewed as a counterpart of Bowen topological entropy. In the present paper, we will give a systematically study to the packing topological entropy for…

Dynamical Systems · Mathematics 2021-09-29 Dou Dou , Dongmei Zheng , Xiaomin Zhou

We introduce the active exploration problem in Markov decision processes (MDPs). Each state of the MDP is characterized by a random value and the learner should gather samples to estimate the mean value of each state as accurately as…

Machine Learning · Statistics 2019-03-01 Jean Tarbouriech , Alessandro Lazaric

We consider a discrete time semi-Markov process where the characteristics defining the process depend on a small perturbation parameter. It is assumed that the state space consists of one finite communicating class of states and, in…

Probability · Mathematics 2016-03-21 Mikael Petersson

Markov decision processes (MDPs) are formal models commonly used in sequential decision-making. MDPs capture the stochasticity that may arise, for instance, from imprecise actuators via probabilities in the transition function. However, in…

Artificial Intelligence · Computer Science 2023-06-21 Marnix Suilen , Thiago D. Simão , David Parker , Nils Jansen

Our aim is to find sufficient conditions for weak convergence of stochastic integrals with respect to the state occupation measure of a Markov chain. First, we study properties of the state indicator function and the state occupation…

Probability · Mathematics 2017-12-12 H. M. Jansen