Limited Information Aggregation for Collaborative Driving in Multi-Agent Autonomous Vehicles
Multi-agent reinforcement learning (MARL) methods have emerged as a promising solution
for multi-agent collaborative driving in the intersection and roundabout scenarios. However …
for multi-agent collaborative driving in the intersection and roundabout scenarios. However …
Efficient Collaborative Multi-Agent Driving via Cross-Attention and Concise Communication
Q Liang, Z Jiang, J Yin, L Peng, J Liu… - 2024 IEEE Intelligent …, 2024 - ieeexplore.ieee.org
Reinforcement learning has been shown to have great potential applications in autonomous
driving. For collaborative driving scenarios, multi-agent reinforcement learning can be used …
driving. For collaborative driving scenarios, multi-agent reinforcement learning can be used …
[PDF][PDF] Safety-Constrained Multi-Agent Reinforcement Learning for Power Quality Control in Distributed Renewable Energy Networks
This paper examines the difficulties of managing distributed power systems, notably due to
the increasing use of renewable energy sources, and focuses on voltage control challenges …
the increasing use of renewable energy sources, and focuses on voltage control challenges …