TO-Agents: A Multi-Agent AI Pipeline for Preference-Guided Topology Optimization

This paper introduces TO-Agents, a multi-agent AI framework that links natural-language design intent with iterative topology optimization. It converts human-provided problem descriptions into validated solver inputs, runs the optimization, and employs an independent judge agent to critique and revise solver parameters based on designer aesthetic preferences.