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Joint Movement and Compression Ratio Design for Mobile Embodied AI Networks (MEAN)

Ding, Yahao et al.
arXiv (All) · Papers
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information-theorymachine-learning
Mobile embodied AI networks (MEAN) enable embodied agents to perceive, reason, communicate, and act in wireless environments. In such networks, agent mobility can improve channel conditions, while semantic compression can reduce transmission payloads. However, movement consumes energy, and stronger
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