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This paper investigates an infinite-horizon linear quadratic stochastic (LQS) optimal control problem for a class of continuous-time stochastic systems. By employing the technique of adaptive dynamic programming (ADP), we propose a novel…

Optimization and Control · Mathematics 2022-10-11 Heng Zhang

This paper introduces a novel Differential Dynamic Programming (DDP) algorithm for solving discrete-time finite-horizon optimal control problems with inequality constraints. Two variants, namely Feasible- and Infeasible-IPDDP algorithms,…

Systems and Control · Electrical Eng. & Systems 2020-10-21 Andrei Pavlov , Iman Shames , Chris Manzie

This paper proposes a new gradient-based optimization approach for designing optimal feedback kernels for parabolic distributed parameter systems with boundary control. Unlike traditional kernel optimization methods for parabolic systems,…

Optimization and Control · Mathematics 2016-03-16 Zhigang Ren , Chao Xu , Qun Lin , Ryan Loxton

In spatial statistics and machine learning, the kernel matrix plays a pivotal role in prediction, classification, and maximum likelihood estimation. A thorough examination reveals that for large sample sizes, the kernel matrix becomes…

Machine Learning · Statistics 2023-11-07 Hao Zhang

All physical systems are affected by some noise that limits the resolution that can be attained in partitioning their state space. For chaotic, locally hyperbolic flows, this resolution depends on the interplay of the local…

Chaotic Dynamics · Physics 2015-12-15 Domenico Lippolis , Predrag Cvitanovic

We propose a variational framework in which the kernel function k : X x X -> R, interpreted as the foundational object encoding what distinctions an agent can represent, is treated as a dynamical variable subject to path entropy…

Machine Learning · Computer Science 2026-03-31 Jnaneshwar Das

It is well known that an Anosov diffeomorphism $T$ enjoys linear response of its SRB measure with respect to infinitesimal perturbations $\dot{T}$. For a fixed observation function $c$, we develop a theory to optimise the response of the…

Dynamical Systems · Mathematics 2026-05-12 Gary Froyland , Maxence Phalempin

As most natural resources, fisheries are affected by random disturbances. The evolution of such resources may be modelled by a succession of deterministic process and random perturbations on biomass and/or growth rate at random times. We…

Optimization and Control · Mathematics 2019-09-15 Patrice Loisel

Ordinary differential equation (ODE) is widely used in modeling biological and physical processes in science. In this article, we propose a new reproducing kernel-based approach for estimation and inference of ODE given noisy observations.…

Methodology · Statistics 2021-10-26 Xiaowu Dai , Lexin Li

We study methods based on reproducing kernel Hilbert spaces for estimating the value function of an infinite-horizon discounted Markov reward process (MRP). We study a regularized form of the kernel least-squares temporal difference (LSTD)…

Machine Learning · Statistics 2021-09-27 Yaqi Duan , Mengdi Wang , Martin J. Wainwright

In the third part of this series of papers, we address the same Cauchy problem that was considered in part 1, namely the nonlocal Fisher-KPP equation in one spatial dimension, $u_t = D u_{xx} + u(1-\phi_T*u)$, where $\phi_T*u$ is a spatial…

Analysis of PDEs · Mathematics 2024-11-25 David John Needham , John Billingham

We derive a closed-form geometric functional for kernel dynamics on finite graphs by applying the Maximum Caliber (MaxCal) variational principle to the spectral transfer function h(lambda) of the graph Laplacian eigenbasis. The main result…

Robotics · Computer Science 2026-04-14 Jnaneshwar Das

A class of Pyragas type nonlocal feedback controllers with time-delay is investigated for the Schl\"ogl model. The main goal is to find an optimal kernel in the controller such that the associated solution of the controlled equation is as…

Adaptation and Self-Organizing Systems · Physics 2015-05-11 Peter Nestler , Eckehard Schöll , Fredi Tröltzsch

We investigate an optimization problem that arises when working within the paradigm of Data-Driven Computational Mechanics. In the context of the diffusion-reaction problem, such an optimization problem seeks for the continuous primal…

Numerical Analysis · Mathematics 2025-06-13 Pedro B. Bazon , Cristian G. Gebhardt , Gustavo C. Buscaglia , Roberto F. Ausas

In this contribution, we generalize the concept of \textit{optimally accurate operators} proposed and used in a series of studies on the simulation of seismic wave propagation, particularly based on Geller \& Takeuchi (1995). Although these…

Geophysics · Physics 2025-05-06 Nobuaki Fuji , Thibault Duretz

We study pathwise approximation of scalar stochastic differential equations at a single point. We provide the exact rate of convergence of the minimal errors that can be achieved by arbitrary numerical methods that are based (in a…

Probability · Mathematics 2007-05-23 Thomas Muller-Gronbach

In this paper, we consider optimal control of stochastic differential equations subject to an expected path constraint. The stochastic maximum principle is given for a general optimal stochastic control in terms of constrained FBSDEs. In…

Optimization and Control · Mathematics 2022-08-16 Ying Hu , Shanjian Tang , Zuo Quan Xu

We adopt the integral definition of the fractional Laplace operator and analyze an optimal control problem for a fractional semilinear elliptic partial differential equation (PDE); control constraints are also considered. We establish the…

Numerical Analysis · Mathematics 2021-09-07 Enrique Otarola

In this work, we shall consider the existence and uniqueness of stationary solutions to stochastic partial functional differential equations with additive noise in which a neutral type of delay is explicitly presented. We are especially…

Probability · Mathematics 2017-07-26 Kai Liu

We address a general optimal switching problem over finite horizon for a stochastic system described by a differential equation driven by Brownian motion. The main novelty is the fact that we allow for infinitely many modes (or regimes,…

Optimization and Control · Mathematics 2019-08-07 Marco Fuhrman , Marie-Amélie Morlais