V. Akhmerov

Evolving Multi-Agent Systems with Large Language Models: Surrogate Fitness Limitations and Empirical Insights

We investigate the use of large language models (LLMs) as evolutionary operators for optimizing the architecture of multi-agent systems (MAS) - a representative instance of LLM-driven optimization over attributed-graph artifacts that arise in generative design. Given a task description, an initial MAS configuration is...