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Navigating a collision-free and optimal trajectory for a robot is a challenging task, particularly in environments with moving obstacles such as humans. We formulate this problem as a stochastic optimal control problem. Since solving the…

Systems and Control · Electrical Eng. & Systems 2026-03-17 Seyyed Reza Jafari , Anders Hansson , Bo Wahlberg

In this paper, we introduce a model-based deep-learning approach to solve finite-horizon continuous-time stochastic control problems with jumps. We iteratively train two neural networks: one to represent the optimal policy and the other to…

Machine Learning · Computer Science 2026-01-16 Patrick Cheridito , Jean-Loup Dupret , Donatien Hainaut

We address the problem of computing a control for a time-dependent nonlinear system to reach a target set in a minimal time. To solve this minimal time control problem, we introduce a hierarchy of linear semi-infinite programs, the values…

Optimization and Control · Mathematics 2023-07-04 Antoine Oustry , Matteo Tacchi

In this article, a class of optimal control problems of differential equations with delays are investigated for which the associated Hamilton-Jacobi-Bellman (HJB) equations are nonlinear partial differential equations with delays. This type…

Optimization and Control · Mathematics 2015-07-16 Jianjun Zhou

We show that necessary and sufficient conditions of optimality in periodic optimization problems can be stated in terms of a solution of the corresponding HJB inequality, the latter being equivalent to a max-min type variational problem…

Optimization and Control · Mathematics 2013-09-10 Vladimir Gaitsgory , Ludmila Manic

This paper presents an inverse optimality method to solve the Hamilton-Jacobi-Bellman equation for a class of nonlinear problems for which the cost is quadratic and the dynamics are affine in the input. The method is inverse optimal because…

Optimization and Control · Mathematics 2011-10-11 Luis Rodrigues , Didier Henrion , Mehdi Abedinpour Fallah

In this paper we present a new algorithm for the solution of Hamilton-Jacobi-Bellman equations related to optimal control problems. The key idea is to divide the domain of computation into subdomains which are shaped by the optimal dynamics…

Numerical Analysis · Mathematics 2014-08-04 Simone Cacace , Emiliano Cristiani , Maurizio Falcone , Athena Picarelli

This paper introduces a novel methodology that leverages the Hamilton-Jacobi solution to enhance non-linear model predictive control (MPC) in scenarios affected by navigational uncertainty. Using Hamilton-Jacobi-Theoretic approach, a…

Optimization and Control · Mathematics 2025-04-01 Amit Jain , Roshan T. Eapen , Puneet Singla

In this paper we investigate a kind of optimal control problem of coupled forward-backward stochastic system with jumps whose cost functional is defined through a coupled forward-backward stochastic differential equation with Brownian…

Probability · Mathematics 2020-09-15 Qian Lin

This paper is concerned with stochastic impulse control problems in which the running cost changes depending on the impulse control. Because of such a dependence, it brings several difficulties when the usual dynamic programming principle…

Optimization and Control · Mathematics 2025-11-11 Yuchen Cao , Jiongmin Yong

We consider optimal transport problems where the cost is optimized over controlled dynamics and the end time is free. Unlike the classical setting, the search for optimal transport plans also requires the identification of optimal "stopping…

Optimization and Control · Mathematics 2018-07-09 Nassif Ghoussoub , Young-Heon Kim , Aaron Zeff Palmer

We study a family of optimal control problems under a set of controlled-loss constraints holding at different deterministic dates. The characterization of the associated value function by a Hamilton-Jacobi-Bellman equation usually calls for…

Optimization and Control · Mathematics 2020-07-27 Geraldine Bouveret , Athena Picarelli

In this paper, we study one kind of stochastic recursive optimal control problem with the obstacle constraints for the cost function where the cost function is described by the solution of one reflected backward stochastic differential…

Optimization and Control · Mathematics 2007-05-23 Zhen Wu , Zhiyong Yu

We present a method for collisionless multi-agent path planning using the Hamilton-Jacobi-Bellman equation. Because the method is rooted in optimal control theory and partial differential equations, it avoids the need for hierarchical…

Optimization and Control · Mathematics 2026-04-01 Christian Parkinson , Adan Baca , Huy Nguyen

We introduce a new and efficient numerical method for multicriterion optimal control and single criterion optimal control under integral constraints. The approach is based on extending the state space to include information on a "budget"…

Optimization and Control · Mathematics 2016-01-06 Ajeet Kumar , Alexander Vladimirsky

Feedback controllers for port-Hamiltonian systems reveal an intrinsic inverse optimality property since each passivating state feedback controller is optimal with respect to some specific performance index. Due to the nonlinear…

Optimization and Control · Mathematics 2020-07-20 Lukas Kölsch , Pol Jané Soneira , Felix Strehle , Sören Hohmann

The aim of this work is to deal with a discontinuous Hamilton-Jacobi equation in the whole euclidian N-dimensional space, associated to a possibly unbounded optimal control problem. Here, the discontinuities are located on a hyperplane and…

Optimization and Control · Mathematics 2024-05-16 Emmanuel Chasseigne , Robson Carlos Reis , Silvia Sastre-Gomez

In this note, we study a class of indefinite stochastic McKean-Vlasov linear-quadratic (LQ in short) control problem under the control taking nonnegative values. In contrast to the conventional issue, both the classical dynamic programming…

Optimization and Control · Mathematics 2023-10-05 Xun Li , Liangquan Zhang

We establish existence and uniqueness of minimax solutions for a fairly general class of path-dependent Hamilton-Jacobi equations. In particular, the relevant Hamiltonians can contain the solution and they only need to be measurable with…

Analysis of PDEs · Mathematics 2025-01-28 Elena Bandini , Christian Keller

Maximum entropy reinforcement learning (RL) methods have been successfully applied to a range of challenging sequential decision-making and control tasks. However, most of existing techniques are designed for discrete-time systems. As a…

Optimization and Control · Mathematics 2020-09-29 Jeongho Kim , Insoon Yang