How can LLMs improve team formation in adversarial games?
Transformer Guided Coevolution: Improved Team Formation in Multiagent Adversarial Games
October 18, 2024
https://arxiv.org/pdf/2410.13769This paper proposes BERTeam, a novel algorithm using a transformer-based neural network to improve team formation in multi-agent adversarial games.
Key points for LLM-based multi-agent systems:
- Sequence generation for team selection: BERTeam treats team selection as a sequence completion task, using a transformer to predict optimal agent combinations.
- Trained alongside coevolution: BERTeam learns concurrently with individual agent policy training, leveraging game outcomes to refine its understanding of successful teams.
- Learns agent similarities: Similar to word embeddings in NLP, BERTeam learns vector representations of agents, encoding their behavior and enabling it to infer missing information about potential team compositions.