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Improving Sample Efficiency and Multi-Agent Communication in RL-based
  Train Rescheduling

Improving Sample Efficiency and Multi-Agent Communication in RL-based Train Rescheduling

28 April 2020
Dano Roost
Ralph Meier
Stephan Huschauer
Erik Nygren
A. Egli
Andreas Weiler
Thilo Stadelmann
ArXiv (abs)PDFHTML

Papers citing "Improving Sample Efficiency and Multi-Agent Communication in RL-based Train Rescheduling"

2 / 2 papers shown
Title
Standardized feature extraction from pairwise conflicts applied to the
  train rescheduling problem
Standardized feature extraction from pairwise conflicts applied to the train rescheduling problem
Anikó Kopacz
Ágnes Mester
Sándor Kolumbán
Lehel Csató
58
0
0
06 Apr 2022
PRIMAL2: Pathfinding via Reinforcement and Imitation Multi-Agent
  Learning -- Lifelong
PRIMAL2: Pathfinding via Reinforcement and Imitation Multi-Agent Learning -- Lifelong
Mehul Damani
Zhiyao Luo
Emerson Wenzel
Guillaume Sartoretti
AI4CE
168
127
0
16 Oct 2020
1