Graph Neural Networks for Multi-Agent Learning

Explore the application of Graph Neural Networks in multi-agent learning systems through this insightful webinar presented by Amanda Prorok from the University of Cambridge. Gain valuable knowledge about the intersection of graph-based machine learning techniques and multi-agent systems as part of the Data sciEnce on GrAphS (DEGAS) Webinar Series. Delve into the potential of Graph Neural Networks to enhance collaborative decision-making and improve coordination among multiple agents in complex environments. Discover how these advanced neural network architectures can be leveraged to tackle challenges in distributed systems, robotics, and artificial intelligence. Learn from an expert in the field and expand your understanding of cutting-edge research in this hour-long presentation, organized by the IEEE Signal Processing Society Data Science Initiative.