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Found 3 papers, 2 papers with code
Intelligent Resource Allocation in Joint Radar-Communication With Graph Neural Networks
In this paper, we propose a framework for intelligent vehicles to conduct JRC, with minimal prior knowledge of the system model and a tunable performance balance, in an environment where surrounding vehicles execute radar detection periodically, which is typical in contemporary protocols.
Deep Reinforcement Learning for Time Allocation and Directional Transmission in Joint Radar-Communication
In addition, experimental results show that the trained deep reinforcement learning agents are robust to changes in the number of vehicles in the environment.
Demand-Side Scheduling Based on Multi-Agent Deep Actor-Critic Learning for Smart Grids
Each household is a decentralized agent with partial observability, which allows scalability and privacy-preservation in a realistic setting.
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