Explainable Multi-Agent Reinforcement Learning for Extended Reality Codec Adaptation

Extended Reality (XR) services are set to transform applications over <inline-formula> <tex-math notation="LaTeX">${\mathbf {5}}^{th}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${\mathbf {6}}^{th}$ </tex-math></inline-formula> generation wireless networks, deliveri...

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Bibliographic Details

Main Authors:	Pedro Enrique Iturria-Rivera, Raimundas Gaigalas, Medhat Elsayed, Majid Bavand, Yigit Ozcan, Melike Erol-Kantarci
Format:	Artigo
Language:	Inglês
Published:	IEEE 2026-01-01
Series:	IEEE Transactions on Machine Learning in Communications and Networking
Subjects:	Extended reality explainable reinforcement learning interpretability quality of experience value function factorization
Online Access:	https://ieeexplore.ieee.org/document/11303975/
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