<ul><li>Cellular Vehicle-to-Everything (C-V2X) evolving towards 6G networks with Connected Autonomous Vehicles (CAVs) as a key application.</li><li>Machine Learning, including Deep Reinforcement Learning (DRL), to enhance CAV decision-making in vehicle control and V2X communication.</li><li>Introduction of Sequential Stochastic Decision Process (SSDP) models to define and assess the value of information (VoI) for optimizing communication systems for CAVs.</li><li>Proposal of a systematic VoI modeling framework grounded in MDP, Reinforcement Learning, and Optimal Control theories for decision-making in networked control systems.</li></ul>

Learning Value of Information towards Joint Communication and Control in 6G V2X

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