LLM2TEA: An Agentic AI Designer for Discovery with Generative Evolutionary Multitasking

TL;DR

LLM2TEA introduces an innovative agentic AI system that combines large language models with evolutionary algorithms to generate, evaluate, and optimize novel, physically viable designs across multiple domains, demonstrating significant improvements in diversity and performance.

Contribution

This work is the first to integrate LLM-driven generative models with evolutionary multitasking for cross-domain design discovery and optimization.

Findings

Achieved 97% to 174% increase in design diversity over baseline.

Over 73% of generated designs outperform top baseline designs in physical performance.

Successfully 3D printed several AI-generated designs, validating real-world applicability.

Abstract

This paper presents LLM2TEA, a Large Language Model (LLM) driven MultiTask Evolutionary Algorithm, representing the first agentic AI designer of its kind operating with generative evolutionary multitasking (GEM). LLM2TEA enables the crossbreeding of solutions from multiple domains, fostering novel solutions that transcend disciplinary boundaries. Of particular interest is the ability to discover designs that are both novel and conforming to real-world physical specifications. LLM2TEA comprises an LLM to generate genotype samples from text prompts describing target objects, a text-to-3D generative model to produce corresponding phenotypes, a classifier to interpret its semantic representations, and a computational simulator to assess its physical properties. Novel LLM-based multitask evolutionary operators are introduced to guide the search towards high-performing, practically viable designs. Experimental results in conceptual design optimization validate the effectiveness of LLM2TEA, showing 97% to 174% improvements in the diversity of novel designs over the current text-to-3D baseline. Moreover, over 73% of the generated designs outperform the top 1% of designs produced by the text-to-3D baseline in terms of physical performance. The designs produced by LLM2TEA are not only aesthetically creative but also functional in real-world contexts. Several of these designs have been successfully 3D printed, demonstrating the ability of our approach to transform AI-generated outputs into tangible, physical designs. These designs underscore the potential of LLM2TEA as a powerful tool for complex design optimization and discovery, capable of producing novel and physically viable designs.