Improved saddle point prediction in stochastic two-player zero-sum games with a deep learning approach-Reference-Cited by-同舟云学术

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Improved saddle point prediction in stochastic two-player zero-sum games with a deep learning approach

Published:2023-11 Issue: Volume:126 Page:106664
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Wu Dawen^ORCID,Lisser Abdel^ORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference54 articles.

1. Artificial neural network methods for the solution of second order boundary value problems;Anitescu;Comput. Mater. Contin.,2019

2. Automatic differentiation in machine learning: a survey;Baydin;J. Mach. Learn. Res.,2018

3. Machine learning for combinatorial optimization: a methodological tour d’horizon;Bengio;European J. Oper. Res.,2021

4. A 3 (2) pair of Runge–Kutta formulas;Bogacki;Appl. Math. Lett.,1989

5. JAX: composable transformations of Python+NumPy programs;Bradbury,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Distributed Non-Cooperative Games and Distributed Learning in Linear and Nonlinear Systems: An Overview;IEEE Transactions on Circuits and Systems I: Regular Papers;2024-08

2. Design and implementation of a game-based activity to promote learning of game theory;Región Científica;2023-07-04

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