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Interval Markov decision processes (IMDPs) generalise classical MDPs by having interval-valued transition probabilities. They provide a powerful modelling tool for probabilistic systems with an additional variation or uncertainty that…

Systems and Control · Computer Science 2017-07-07 Ernst Moritz Hahn , Vahid Hashemi , Holger Hermanns , Morteza Lahijanian , Andrea Turrini

Given a possibly discontinuous, bounded function $f:\mathbb{R}\mapsto\mathbb{R}$, we consider the set of generalized flows, obtained by assigning a probability measure on the set of Carath\'eodory solutions to the ODE ~$\dot x = f(x)$. The…

Classical Analysis and ODEs · Mathematics 2020-09-15 Alberto Bressan , Marco Mazzola , Khai T. Nguyen

A Markovian bridge is a probability measure taken from a disintegration of the law of an initial part of the path of a Markov process given its terminal value. As such, Markovian bridges admit a natural parameterization in terms of the…

Probability · Mathematics 2011-03-15 Loïc Chaumont , Gerónimo Uribe Bravo

Consider the Leibenson equation \begin{equation*} \partial_t u = \Delta_p u^q, \end{equation*} where $\Delta_p f = div(|\nabla f|^{p-2}\nabla f)$ for $p>1$ and $q>0$, which is a simultaneous generalization of the porous media and the…

Probability · Mathematics 2025-08-19 Viorel Barbu , Sebastian Grube , Marco Rehmeier , Michael Röckner

Semi-Markov processes are a generalization of Markov processes since the exponential distribution of time intervals is replaced with an arbitrary distribution. This paper provides an integro-differential form of the Kolmogorov's backward…

Probability · Mathematics 2017-09-20 Enzo Orsingher , Costantino Ricciuti , Bruno Toaldo

An infinite system of point particles placed in $\mathds{R}^d$ is studied. Its constituents perform random jumps with mutual repulsion described by a translation-invariant jump kernel and interaction potential, respectively. The pure states…

Probability · Mathematics 2021-03-18 Yuri Kozitsky , Michael Röckner

We study and compare two concepts for weak solutions to semilinear parabolic path-dependent partial differential equations (PPDEs). The first is that of mild solutions as it appears, e.g., in the log-Laplace functionals of historical…

Probability · Mathematics 2018-11-16 Alexander Kalinin , Alexander Schied

We analyze the well-posedness of a so called McKean Feynman-Kac Equation (MFKE), which is a McKean type equation with a Feynman-Kac perturbation. We provide in particular weak and strong existence conditions as well as pathwise uniqueness…

Probability · Mathematics 2024-03-08 Jonas Lieber , Nadia Oudjane , Francesco Russo

We study existence and uniqueness of invariant probability measures for continuous-time Markov processes on general state spaces. Existence is obtained from tightness of time averages under a weak regularity assumption inspired by…

Probability · Mathematics 2026-01-21 Jean-Gabriel Attali

We extend the notion of viscosity solutions for path-dependent PDEs introduced by Ekren et al. [Ann. Probab. 42 (2014), no. 1, 204-236] to path-dependent integro-differential equations and establish well-posedness, i.e., existence,…

Analysis of PDEs · Mathematics 2014-12-31 Christian Keller

This paper investigates natural conditions for the existence of optimal policies for a Markov decision process with incomplete information (MDPII) and with expected total costs. The MDPII is the classic model of a controlled stochastic…

Optimization and Control · Mathematics 2021-09-30 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

The computation of the probability of the first-passage time through a given threshold of a stochastic process is a classic problem that appears in many branches of physics. When the stochastic dynamics is markovian, the probability admits…

Statistical Mechanics · Physics 2009-05-05 Michele Maggiore , Antonio Riotto

The paper concerns classical solution of path-dependent partial differential equations (PPDEs) with coefficients depending on both variables of path and path-valued measure, which are crucial to understanding large-scale mean-field…

Probability · Mathematics 2024-07-26 Shanjian Tang , Huilin Zhang

We propose to solve polynomial hyperbolic partial differential equations (PDEs) with convex optimization. This approach is based on a very weak notion of solution of the nonlinear equation, namely the measure-valued (mv) solution,…

Analysis of PDEs · Mathematics 2018-07-09 Swann Marx , Tillmann Weisser , Didier Henrion , Jean Lasserre

This paper is devoted to the study of some nonlinear parabolic equations with discontinuous diffusion intensities. Such problems appear naturally in physical and biological models. Our analysis is based on variational techniques and in…

Analysis of PDEs · Mathematics 2021-02-09 Dohyun Kwon , Alpár Richárd Mészáros

The notion of a successful coupling of Markov processes, based on the idea that both components of the coupled system ``intersect'' in finite time with probability one, is extended to cover situations when the coupling is unnecessarily…

Probability · Mathematics 2007-05-23 Michael Blank , Sergey Pirogov

The study of multidimensional stochastic processes involves complex computations in intricate functional spaces. In particular, the diffusion processes, which include the practically important Gauss-Markov processes, are ordinarily defined…

Probability · Mathematics 2010-09-06 Thibaud Taillefumier , Jonathan Touboul

In this paper, we study the existence and uniqueness of solutions for general fractional-time parabolic equations of mixture type, and their probabilistic representations in terms of the corresponding inverse subordinators with or without…

Probability · Mathematics 2019-11-04 Zhen-Qing Chen

For a wide class of continuous-time Markov processes, including all irreducible hypoelliptic diffusions evolving on an open, connected subset of $\RL^d$, the following are shown to be equivalent: (i) The process satisfies (a slightly weaker…

Probability · Mathematics 2016-04-27 Ioannis Kontoyiannis , Sean P. Meyn

We formulate Bayesian updates in Markov processes by means of path integral techniques and derive the imaginary-time Schr\"{o}dinger equation with likelihood to direct the inference incorporated as a potential for the posterior probability…

Statistics Theory · Mathematics 2017-10-24 Toshiyuki Fujii , Noriyuki Hatakenaka