Refining Minimax Regret for Unsupervised Environment Design

Refining Minimax Regret for Unsupervised Environment Design

19 February 2024

Michael Beukman

Michael T. Matthews

Papers citing "Refining Minimax Regret for Unsupervised Environment Design"

10 / 10 papers shown

Title
Task Scheduling & Forgetting in Multi-Task Reinforcement Learning Marc Speckmann Theresa Eimer CLL 40 0 0 03 Mar 2025
Improving Environment Novelty Quantification for Effective Unsupervised Environment Design Jayden Teoh Wenjun Li Pradeep Varakantham 58 1 0 08 Feb 2025
No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery Alexander Rutherford Michael Beukman Timon Willi Bruno Lacerda Nick Hawes Jakob Foerster 48 6 0 27 Aug 2024
The Overcooked Generalisation Challenge Constantin Ruhdorfer Matteo Bortoletto Anna Penzkofer Andreas Bulling 48 4 0 25 Jun 2024
minimax: Efficient Baselines for Autocurricula in JAX Minqi Jiang Michael Dennis Edward Grefenstette Tim Rocktaschel 27 8 0 21 Nov 2023
Adversarial Model for Offline Reinforcement Learning M. Bhardwaj Tengyang Xie Byron Boots Nan Jiang Ching-An Cheng AAML OffRL 37 26 0 21 Feb 2023
Grounding Aleatoric Uncertainty for Unsupervised Environment Design Minqi Jiang Michael Dennis Jack Parker-Holder Andrei Lupu Heinrich Küttler Edward Grefenstette Tim Rocktaschel Jakob N. Foerster 43 13 0 11 Jul 2022
Provably Efficient Model-Free Constrained RL with Linear Function Approximation A. Ghosh Xingyu Zhou Ness B. Shroff 69 23 0 23 Jun 2022
Replay-Guided Adversarial Environment Design Minqi Jiang Michael Dennis Jack Parker-Holder Jakob N. Foerster Edward Grefenstette Tim Rocktaschel 129 95 0 06 Oct 2021
"Other-Play" for Zero-Shot Coordination Hengyuan Hu Adam Lerer A. Peysakhovich Jakob N. Foerster VLM OffRL 136 218 0 06 Mar 2020