AIBullisharXiv – CS AI · Mar 166/10
🧠
Efficient and Interpretable Multi-Agent LLM Routing via Ant Colony Optimization
Researchers propose AMRO-S, a new routing framework for multi-agent LLM systems that uses ant colony optimization to improve efficiency and reduce costs. The system addresses key deployment challenges like high inference costs and latency while maintaining performance quality through semantic-aware routing and interpretable decision-making.