University of Illinois Urbana-Champaign researchers develop a method to train multiple agents to work together

Original Link: https://www.sciencedaily.com/releases/2022/07/220725124120.htm

Short summary of the article

The most crucial idea in this article is that Tran and his colleagues have developed a method to train multiple agents to work together using multi-agent reinforcement learning, a type of artificial intelligence. This method can be used to solve complex problems in which communication lines are blocked or the agents are not equipped with the right hardware.

Why I chose this article

The reason this is important is that the method allows agents to work together to solve complex problems even when communication is difficult or impossible. This can be used in many real-life situations, such as military surveillance, robots working together in a warehouse, traffic signal control, autonomous vehicles coordinating deliveries, or controlling an electric power grid.

Reference

Seung Hyun Kim, Neale Van Stralen, Girish Chowdhary, Huy T. Tran. Disentangling Successor Features for Coordination in Multi-agent Reinforcement Learning. Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022