Coordination Graph
Coordination graphs represent relationships between agents or data points, aiming to model collaboration or identify outliers within complex systems. Current research focuses on developing efficient algorithms for learning these graphs, particularly in multi-agent reinforcement learning, often employing graph neural networks and incorporating temporal or group-level information to improve coordination and scalability. These advancements are significant for improving the performance of multi-agent systems in various applications, such as resource allocation and robotics, and for enhancing outlier detection methods in data analysis.
Papers
September 17, 2024
April 17, 2024
March 28, 2024
February 23, 2024
November 30, 2023
October 26, 2022
July 1, 2022
January 17, 2022
January 10, 2022