Revisiting Regularized Policy Optimization for Stable and Efficient Reinforcement Learning in Two-Player Games

Fuente: arXiv

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Bibliographic Details
Main Authors:	Ota, Kazuki, Osa, Takayuki, Omura, Motoki, Harada, Tatsuya
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2602.10894