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Learning Cooperative Control Policies for Multi-Robot Systems

Wednesday, January 25th, 4:10pm Tel Aviv time (3:10pm CET, 9:10am NY time)

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Amanda Prorok, Cambridge University

Abstract:

In this talk, I discuss how we leverage machine learning methods to generate cooperative policies for multi-agent / multi-robot systems. I describe how we use Graph Neural Networks (GNNs) to learn effective communication strategies for decentralized coordination across various multi-agent tasks. In particular, I will discuss recent work on the role of agent heterogeneity and its impact on transferring learned cooperative policies to real-world experimental settings.
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