A multi-agent reinforcement learning algorithm with pruning is proposed for migrating vehicular AI 'twins' between roadside units, but the equilibrium proof is flawed and experiments are not reproducible.
Generative diffusion-based contract design for efficient AI twin migration in vehicular embodied AI networks,
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Bi-LSTM based Multi-Agent DRL with Computation-aware Pruning for Agent Twins Migration in Vehicular Embodied AI Networks
A multi-agent reinforcement learning algorithm with pruning is proposed for migrating vehicular AI 'twins' between roadside units, but the equilibrium proof is flawed and experiments are not reproducible.