CEDAR: Agent-Orchestrated Tree Search for Goal-Directed Optimization of Complex Systems
CEDAR is an autonomous method that uses Large Language Model agents to discover complex systems satisfying user-specified behavioral goals, enabling goal-directed discovery of complex system behaviors while preserving solution diversity, and its LLM-based interpretability reveals how structural changes drive emergent behavior.