Andrea Carbonati

Multi-Agent LLMs for Adaptive Acquisition in Bayesian Optimization

This work presents a metric-level study of LLM-mediated search policy learning, studying how LLMs construct and adapt exploration-exploitation strategies under multiple operational definitions of exploration, including informativeness, diversity, and representativeness.