12 citations · 18 across the 4 of their papers we have counts for
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cs.AI2020★ 12 cited
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…
cs.AI2020
Improving Sample Efficiency and Multi-Agent Communication in RL-based Train Rescheduling
Dano Roost, Ralph Meier, Stephan Huschauer +4
We present preliminary results from our sixth placed entry to the Flatland international competition for train rescheduling, including two improvements for optimized reinforcement…