6 citations · 18 across the 10 of their papers we have counts for
3 papers · 1 filter
The Holy Grail of Multi-Robot Planning: Learning to Generate Online-Scalable Solutions from Offline-Optimal Experts
Amanda Prorok, Jan Blumenkamp, Qingbiao Li +3
Many multi-robot planning problems are burdened by the curse of dimensionality, which compounds the difficulty of applying solutions to large-scale problem instances. The use of le…
Graph Convolutional Memory using Topological Priors
Steven D. Morad, Stephan Liwicki, Ryan Kortvelesy +2
Solving partially-observable Markov decision processes (POMDPs) is critical when applying reinforcement learning to real-world problems, where agents have an incomplete view of the…
ModGNN: Expert Policy Approximation in Multi-Agent Systems with a Modular Graph Neural Network Architecture
Ryan Kortvelesy, Amanda Prorok
Recent work in the multi-agent domain has shown the promise of Graph Neural Networks (GNNs) to learn complex coordination strategies. However, most current approaches use minor var…