Distributed Deep Reinforcement Learning Via Split Computing For Connected Autonomous Vehicles

This paper proposes the application of split computing paradigms for deep reinforcement learning through distributed computation between Connected Autonomous Vehicles (CAVs) and edge servers. While this approach has been explored in computer vision, it remains largely unexplored for reinforcement le...

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Bibliographic Details
Main Authors: Rauch Robert, Gazda Juraj
Format: Article
Language:English
Published: Sciendo 2025-06-01
Series:Acta Electrotechnica et Informatica
Subjects:
Online Access:https://doi.org/10.2478/aei-2025-0008
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