Quantifying the effects of environment and population diversity in multi-agent reinforcement learning

16 February 2021

Papers citing "Quantifying the effects of environment and population diversity in multi-agent reinforcement learning"

7 / 7 papers shown

Title
Implicitly Aligning Humans and Autonomous Agents through Shared Task Abstractions Stéphane Aroca-Ouellette Miguel Aroca-Ouellette K. Wense A. Roncone 27 0 0 07 May 2025
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 social path to human-like artificial intelligence Edgar A. Duénez-Guzmán Suzanne Sadedin Jane X. Wang Kevin R. McKee Joel Z. Leibo GNN 18 28 0 22 May 2024
Symmetry-Breaking Augmentations for Ad Hoc Teamwork Ravi Hammond Dustin Craggs Mingyu Guo Jakob Foerster Ian Reid 23 1 0 15 Feb 2024
A Survey on Context-Aware Multi-Agent Systems: Techniques, Challenges and Future Directions Hung Du Srikanth Thudumu Rajesh Vasa K. Mouzakis LLMAG 29 7 0 03 Feb 2024
ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination Xihuai Wang Shao Zhang Wenhao Zhang Wentao Dong Jingxiao Chen Ying Wen Weinan Zhang 20 8 0 08 Oct 2023
"Other-Play" for Zero-Shot Coordination Hengyuan Hu Adam Lerer A. Peysakhovich Jakob N. Foerster VLM OffRL 130 213 0 06 Mar 2020