Results 101 to 110 of about 8,699 (152)

Precise error bounds for numerical approximations of fractional HJB equations

IMA Journal of Numerical Analysis
Abstract We prove precise rates of convergence for monotone approximation schemes of fractional and nonlocal Hamilton–Jacobi–Bellman equations. We consider diffusion-corrected difference-quadrature schemes from the literature and new approximations based on powers of discrete Laplacians, approximations that are (formally) fractional ...
Chowdhury, Indranil, Jakobsen, Espen R.
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Verification Theorems for HJB equations [PDF]

Proceedings of Control Systems: Theory, Numerics and Applications — PoS(CSTNA2005), 2006
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Viscosity Solutions to First Order Path-Dependent HJB Equations

, 2020
25 ...
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Optimal control of nonlinear systems using Multi-Layer Perceptron Neural Network and adaptive extended Kalman Filter

Majlesi Journal of Electrical Engineering
In this paper we present a nonlinear optimal control method based on approximating the solution of Hamilton-Jacobi-Bellman (HJB) equation. Value function is approximated as the output of Multilayer Perceptron Neural Network (MLPNN).
Esmat Sadat Alaviyan Shahri, Saeed Balochian   +1 more
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Viscosity Solutions to Path-Dependent HJB Equation and Applications

, 2016
There is a error in the proof of ...
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Tractable Representations for Convergent Approximation of Distributional HJB Equations

In reinforcement learning (RL), the long-term behavior of decision-making policies is evaluated based on their average returns. Distributional RL has emerged, presenting techniques for learning return distributions, which provide additional statistics for evaluating policies, incorporating risk-sensitive considerations.
Alhosh, Julie, Wiltzer, Harley, Meger, David   +2 more
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A fixed point approach for nonlinear HJB equations

International Journal of Mathematical Analysis, 2015
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L^\infty-Error estimate for nonlinear HJB equations

International Journal of Mathematical Analysis, 2015
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On Computation of Optimal Switching HJB Equation

Proceedings of the 45th IEEE Conference on Decision and Control, 2006
This paper proposes an algorithm to compute the optimal switching cost from the dynamic programming Hamilton-Jacobi-Bellman (HJB) equations. For the optimal switching control problem, the HJB equation is a System of Quasi-Variational Inequalities (SQVIs) coupled by a nonlinear operator. By exploring the fundamental limit on the number of switches could
Huan Zhang, Matthew R. James
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HJB Equations Through Backward Stochastic Differential Equations

2017
This last chapter of the book completes the picture of the main methods used to study second-order HJB equations in Hilbert spaces and related optimal control problems by presenting a survey of results that can be achieved with the techniques of Backward SDEs in infinite dimension.
Fuhrman, M, Tessitore, G.
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