A digital twin-based INC-MEC framework models XR user interactions as a Stackelberg Markov game and uses a Nash-asynchronous hybrid multi-agent RL algorithm to achieve Nash Equilibrium, improving system utility, uplink rate, and energy efficiency in simulations.
Asynchronous hybrid reinforcement learning for latency and reliability optimization in the metaverse over wireless communications
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Digital Twin-Assisted In-Network and Edge Collaboration for Joint User Association, Task Offloading, and Resource Allocation in the Metaverse
A digital twin-based INC-MEC framework models XR user interactions as a Stackelberg Markov game and uses a Nash-asynchronous hybrid multi-agent RL algorithm to achieve Nash Equilibrium, improving system utility, uplink rate, and energy efficiency in simulations.