Giving MARL agents supervised language targets for describing observations improves task performance, representation structure, and robustness to new teammates compared to emergent communication baselines.
In:Advances in Neu- ral Information Processing Systems
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.MA 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Towards Language-Augmented Multi-Agent Deep Reinforcement Learning
Giving MARL agents supervised language targets for describing observations improves task performance, representation structure, and robustness to new teammates compared to emergent communication baselines.