Collaboration Promotes Group Resilience in Multi-Agent RL
; 6:231−243, 2025.
Presented at the Reinforcement Learning Conference (RLC), Edmonton, Alberta, Canada, August 5–9, 2025.
Abstract
To effectively operate in various dynamic scenarios, RL agents must be resilient to unexpected changes in their environment. Previous work on this form of resilience has focused on single-agent settings. In this work, we introduce and formalize a multi-agent variant of resilience, which we term group resilience. We further hypothesize that collaboration with other agents is key to achieving group resilience; collaborating agents adapt better to environmental perturbations in multi-agent reinforcement learning (MARL) settings. We test our hypothesis empirically by evaluating different collaboration protocols and examining their effect on group resilience. Our experiments show that all the examined collaborative approaches achieve higher group resilience than their non-collaborative counterparts.
[abs][pdf]
BibTeX
@article{shraga2025collaboration,
title={Collaboration Promotes Group Resilience in Multi-Agent {RL}},
author={Shraga, Ilai and Azran, Guy and Gerstgrasser, Matthias and Abu, Ofir and Rosenschein, Jeffrey and Keren, Sarah},
journal={Reinforcement Learning Journal},
volume={6},
pages={231--243},
year={2025}
}