31 citations · 70 across the 20 of their papers we have counts for
3 papers · 1 filter
Flatland-RL : Multi-Agent Reinforcement Learning on Trains
Sharada Mohanty, Erik Nygren, Florian Laurent +11
Efficient automated scheduling of trains remains a major challenge for modern railway systems. The underlying vehicle rescheduling problem (VRSP) has been a major focus of Operatio…
PRIMAL2: Pathfinding via Reinforcement and Imitation Multi-Agent Learning -- Lifelong
Mehul Damani, Zhiyao Luo, Emerson Wenzel +1
Multi-agent path finding (MAPF) is an indispensable component of large-scale robot deployments in numerous domains ranging from airport management to warehouse automation. In parti…
ForMIC: Foraging via Multiagent RL with Implicit Communication
Samuel Shaw, Emerson Wenzel, Alexis Walker +1
Multi-agent foraging (MAF) involves distributing a team of agents to search an environment and extract resources from it. Nature provides several examples of highly effective forag…