MobiU-MAC deploys a new DRL algorithm, CHILL-STER, that learns optimal ranging-free channel access policies equivalent to standard MDPs despite long delays and node mobility in underwater networks.
Leveraging propagation delays: A delay-aware mul- tiagent reinforcement learning mac protocol for underwater acoustic networks
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Delay-Robust Deep Reinforcement Learning for Ranging-Free Channel Access under Mobility in Underwater Acoustic Networks
MobiU-MAC deploys a new DRL algorithm, CHILL-STER, that learns optimal ranging-free channel access policies equivalent to standard MDPs despite long delays and node mobility in underwater networks.