Zobrazeno 1 - 10
of 58 155
pro vyhledávání: '"Variational Inequality"'
The main goal of this paper is to investigate the multi-parameter stability result for a stochastic fractional differential variational inequality with L\'{e}vy jump (SFDVI with L\'{e}vy jump) under some mild conditions. We verify that Mosco converge
Externí odkaz:
http://arxiv.org/abs/2411.07557
Autor:
Guo, Mingxin, Xu, Zuo Quan
In this paper, we explore a new class of stochastic control problems characterized by specific control constraints. Specifically, the admissible controls are subject to the ratcheting constraint, meaning they must be non-decreasing over time and are
Externí odkaz:
http://arxiv.org/abs/2412.11383
A Halpern-type relaxed inertial inexact progressive hedging algorithm (PHA) is proposed for solving multi-stage stochastic variational inequalities in general probability spaces. The subproblems in this algorithm are allowed to be calculated inexactl
Externí odkaz:
http://arxiv.org/abs/2412.05928
Autor:
Yazdi, Maryam1 (AUTHOR) msh_yazdi@yahoo.com, Hashemi Sababe, Saeed2 (AUTHOR) s.hashemi@ualberta.ca
Publikováno v:
Mathematics (2227-7390). Nov2024, Vol. 12 Issue 22, p3466. 19p.
Publikováno v:
Iranian Journal of Numerical Analysis and Optimization, Vol 14, Iss Issue 4, Pp 991-1015 (2024)
In this article, we apply three numerical methods to study the L∞-convergence of the Newton-multigrid method for parabolic quasi-variational inequalities with a nonlinear right-hand side. To discretize the problem, we utilize a finite element metho
Externí odkaz:
https://doaj.org/article/669f0f9809ed47c5b03a4b42034bb3d1
Autor:
Jia Li, Zhipeng Tong
Publikováno v:
Journal of Inequalities and Applications, Vol 2024, Iss 1, Pp 1-16 (2024)
Abstract The objective of this paper is to investigate a class of initial boundary value problems for inverse variational inequalities that arise from financial matters. By utilizing the energy inequality on a localized cylindrical region and the Caf
Externí odkaz:
https://doaj.org/article/cbeb0e76084f4667b9869b368c92a161
Multi-agent reinforcement learning (MARL) presents unique challenges as agents learn strategies through experiences. Gradient-based methods are often sensitive to hyperparameter selection and initial random seed variations. Concurrently, significant
Externí odkaz:
http://arxiv.org/abs/2410.07976
Autor:
Berinde, Vasile1,2 (AUTHOR) vasile.berinde@mi.utcluj.ro, Saleh, Khairul3 (AUTHOR) khairul@kfupm.edu.sa
Publikováno v:
Axioms (2075-1680). Nov2024, Vol. 13 Issue 11, p756. 16p.