MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement
Learning

MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning

6 March 2023

Mikayel Samvelyan

Jack Parker-Holder

Jakob N. Foerster

Roberta Raileanu

Tim Rocktaschel

Papers citing "MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning"

10 / 10 papers shown

Title
Cross-environment Cooperation Enables Zero-shot Multi-agent Coordination Kunal Jha Wilka Carvalho Yancheng Liang S. Du Max Kleiman-Weiner Natasha Jaques 22 0 0 17 Apr 2025
A Generalist Hanabi Agent Arjun Vaithilingam Sudhakar Hadi Nekoei Mathieu Reymond Miao Liu Janarthanan Rajendran Sarath Chandar 41 0 0 17 Mar 2025
Three Dogmas of Reinforcement Learning David Abel Mark K. Ho A. Harutyunyan 21 4 0 15 Jul 2024
The Overcooked Generalisation Challenge Constantin Ruhdorfer Matteo Bortoletto Anna Penzkofer Andreas Bulling 34 3 0 25 Jun 2024
Open-Endedness is Essential for Artificial Superhuman Intelligence Edward Hughes Michael Dennis Jack Parker-Holder Feryal M. P. Behbahani Aditi Mavalankar Yuge Shi Tom Schaul Tim Rocktaschel LRM 21 18 0 06 Jun 2024
Curriculum Learning for Cooperation in Multi-Agent Reinforcement Learning R. Bhati S. Gottipati Clodéric Mars Matthew E. Taylor 20 0 0 19 Dec 2023
Generalization in Cooperative Multi-Agent Systems Anuj Mahajan Mikayel Samvelyan Tarun Gupta Benjamin Ellis Mingfei Sun Tim Rocktaschel Shimon Whiteson AI4CE 29 15 0 31 Jan 2022
Replay-Guided Adversarial Environment Design Minqi Jiang Michael Dennis Jack Parker-Holder Jakob N. Foerster Edward Grefenstette Tim Rocktaschel 116 94 0 06 Oct 2021
Transferring End-to-End Visuomotor Control from Simulation to Real World for a Multi-Stage Task Stephen James Andrew J. Davison Edward Johns 153 275 0 07 Jul 2017
CAD2RL: Real Single-Image Flight without a Single Real Image Fereshteh Sadeghi Sergey Levine SSL 212 808 0 13 Nov 2016