An actor-critic reinforcement learning framework for dynamic multichannel access matches or beats DQN in simulations, scales to 64 channels, and supports decentralized multi-user decisions without information exchange.
Deep reinforcement learning for dynamic multichannel access in wireless networks,
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A Deep Actor-Critic Reinforcement Learning Framework for Dynamic Multichannel Access
An actor-critic reinforcement learning framework for dynamic multichannel access matches or beats DQN in simulations, scales to 64 channels, and supports decentralized multi-user decisions without information exchange.