Machine Learning · Statistics
Discussion of Kallus (2020) and Mo, Qi, and Liu (2020): New Objectives for Policy Learning
Sijia Li, Xiudi Li, Alex Luedtke
2020-10-13
Machine Learning · Computer Science
Trajectory Data Suffices for Statistically Efficient Policy Evaluation in Finite-Horizon Offline RL with Linear $q^\pi$-Realizability and Concentrability
Volodymyr Tkachuk, Csaba Szepesvári, Xiaoqi Tan
2025-10-07
Machine Learning · Computer Science
More Efficient Off-Policy Evaluation through Regularized Targeted Learning
Aurélien F. Bibaut, Ivana Malenica, Nikos Vlassis, Mark J. van der Laan
2019-12-16
Machine Learning · Computer Science
Acceleration in Policy Optimization
Veronica Chelu, Tom Zahavy, Arthur Guez, Doina Precup +1
2023-09-07
Artificial Intelligence · Computer Science
Improving Sample Efficiency and Multi-Agent Communication in RL-based Train Rescheduling
Dano Roost, Ralph Meier, Stephan Huschauer, Erik Nygren +3
2020-04-29
Artificial Intelligence · Computer Science
Learning to act: a Reinforcement Learning approach to recommend the best next activities
Stefano Branchi, Chiara Di Francescomarino, Chiara Ghidini, David Massimo +2
2025-07-25
Machine Learning · Computer Science
Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning
Tianyi Chen, Kaiqing Zhang, Georgios B. Giannakis, Tamer Başar
2021-04-21
Machine Learning · Computer Science
Policy composition in reinforcement learning via multi-objective policy optimization
Shruti Mishra, Ankit Anand, Jordan Hoffmann, Nicolas Heess +3
2023-08-31