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We study the ergodic property of a continuous-state branching process with immigration and competition. The exponential ergodicity in a weighted total variation distance is proved under natural assumptions. The main theorem applies to…

Probability · Mathematics 2023-09-06 Pei-Sen Li , Zenghu Li , Jian Wang , Xiaowen Zhou

This paper studies constrained optimal impulse control problems of a deterministic system described by a (semi)flow, where the performance measures are the discounted total costs including both the costs incurred with applying impulses as…

Optimization and Control · Mathematics 2025-04-28 Alexey Piunovskiy , Yi Zhang

Autonomous systems often have logical constraints arising, for example, from safety, operational, or regulatory requirements. Such constraints can be expressed using temporal logic specifications. The system state is often partially…

Artificial Intelligence · Computer Science 2024-06-21 Krishna C. Kalagarla , Dhruva Kartik , Dongming Shen , Rahul Jain , Ashutosh Nayyar , Pierluigi Nuzzo

The purpose of this paper is to study the time average behavior of Markov chains with transition probabilities being kernels of completely continuous operators, and therefore to provide a sufficient condition for a class of Markov chains…

Probability · Mathematics 2018-11-16 Shizhou Xu

In this work, we study an optimal control problem for a multi-agent system modeled by an undirected formation graph with nodes describing the kinematics of each agent, given by a left-invariant control system on a Lie group. The agents…

Optimization and Control · Mathematics 2020-11-26 Leonardo Colombo , Dimos Dimarogonas

This paper deals with control of partially observable discrete-time stochastic systems. It introduces and studies Markov Decision Processes with Incomplete Information and with semi-uniform Feller transition probabilities. The important…

Optimization and Control · Mathematics 2022-08-30 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

We consider a simple control problem in which the underlying dynamics depend on a parameter that is unknown and must be learned. We exhibit a control strategy which is optimal to within a multiplicative constant. While most authors find…

Optimization and Control · Mathematics 2021-09-15 Jacob Carruth , Maximilian F. Eggl , Charles Fefferman , Clarence W. Rowley , Melanie Weber

Risk-sensitive control balances performance with resilience to unlikely events in uncertain systems. This paper introduces ergodic-risk criteria, which capture long-term cumulative risks through probabilistic limit theorems. By ensuring the…

Optimization and Control · Mathematics 2025-03-11 Shahriar Talebi , Na Li

We continue our study of the dynamics of mappings with small topological degree on (projective) complex surfaces. Previously, under mild hypotheses, we have constructed an ergodic ``equilibrium'' measure for each such mapping. Here we study…

Dynamical Systems · Mathematics 2009-09-10 Jeffrey Diller , Romain Dujardin , Vincent Guedj

In the paper average reward per unit time and average risk sensitive reward functionals are considered for controlled nonhomogeneous Markov processes. Existence of solutions to suitable Bellman equations is shown. Continuity of the value…

Optimization and Control · Mathematics 2025-06-19 Łukasz Stettner

We study the ergodic control problem for a class of controlled jump diffusions driven by a compound Poisson process. This extends the results of [SIAM J. Control Optim. 57 (2019), no. 2, 1516-1540] to running costs that are not…

Optimization and Control · Mathematics 2021-01-01 Ari Arapostathis , Guodong Pang , Yi Zheng

In this paper, we describe a constrained Lagrangian and Hamiltonian formalism for the optimal control of nonholonomic mechanical systems. In particular, we aim to minimize a cost functional, given initial and final conditions where the…

Optimization and Control · Mathematics 2014-12-24 Anthony Bloch , Leonardo Colombo , Rohit Gupta , David Martin de Diego

In this work, we address the challenge of approximating unknown system dynamics and costs by representing them as a bilinear system using Koopman-based Inverse Optimal Control (IOC). Using optimal trajectories, we construct a bilinear…

Systems and Control · Electrical Eng. & Systems 2025-01-31 Victor Nan Fernandez-Ayala , Shankar A. Deka , Dimos V. Dimarogonas

We introduce a notion of bounded variation solution for a new class of nonlinear control systems with ordinary and impulsive controls, in which the drift function depends not only on the state, but also on its past history, through a finite…

Optimization and Control · Mathematics 2023-07-25 Giovanni Fusco , Monica Motta

Among various rare events, the effective computation of transition paths connecting metastable states in a stochastic model is an important problem. This paper proposes a stochastic optimal control formulation for transition path problems…

Optimization and Control · Mathematics 2023-11-15 Yuan Gao , Jian-Guo Liu , Oliver Tse

The aim of this paper is to show how extracting dynamical behavior and ergodic properties from deterministic chaos with the assistance of exact invariant measures. On the one hand, we provide an approach to deal with the inverse problem of…

Chaotic Dynamics · Physics 2015-06-24 Roberto Venegeroles

We establish existence, approximate controllability and optimal control of a class of impulsive non-local non-linear fractional dynamical systems in Banach spaces. We use fractional calculus, sectorial operators and Krasnoselskii fixed…

Optimization and Control · Mathematics 2018-07-10 Sarra Guechi , Amar Debbouche , Delfim F. M. Torres

This article treats long term average impulse control problems with running costs in the case that the underlying process is a L\'evy process. Under quite general conditions we characterize the value of the control problem as the value of a…

Probability · Mathematics 2020-05-15 Sören Christensen , Tobias Sohr

Euclidean Markov decision processes are a powerful tool for modeling control problems under uncertainty over continuous domains. Finite state imprecise, Markov decision processes can be used to approximate the behavior of these infinite…

Artificial Intelligence · Computer Science 2020-06-29 Manfred Jaeger , Giorgio Bacci , Giovanni Bacci , Kim Guldstrand Larsen , Peter Gjøl Jensen

We consider a risk-sensitive optimization of consumption-utility on infinite time horizon where the one-period investment gain depends on an underlying economic state whose evolution over time is assumed to be described by a discrete-time,…

Optimization and Control · Mathematics 2021-11-19 Anindya Goswami , Nimit Rana , Tak Kuen Siu