61 citations · 73 across the 4 of their papers we have counts for
4 papers
Empirical Hardness in Multi-Agent Pathfinding: Research Challenges and Opportunities
Jingyao Ren, Eric Ewing, T. K. Satish Kumar +2
Multi-agent pathfinding (MAPF) is the problem of finding collision-free paths for a team of agents on a map. Although MAPF is NP-hard, the hardness of solving individual instances…
MAPFAST: A Deep Algorithm Selector for Multi Agent Path Finding using Shortest Path Embeddings
Jingyao Ren, Vikraman Sathiyanarayanan, Eric Ewing +2
Solving the Multi-Agent Path Finding (MAPF) problem optimally is known to be NP-Hard for both make-span and total arrival time minimization. While many algorithms have been develop…
End to end learning and optimization on graphs
Bryan Wilder, Eric Ewing, Bistra Dilkina +1
Real-world applications often combine learning and optimization problems on graphs. For instance, our objective may be to cluster the graph in order to detect meaningful communitie…
End-to-End Game-Focused Learning of Adversary Behavior in Security Games
Andrew Perrault, Bryan Wilder, Eric Ewing +3
Stackelberg security games are a critical tool for maximizing the utility of limited defense resources to protect important targets from an intelligent adversary. Motivated by gree…