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Author

Sarah Gerner

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Book Open access Jul 2026

Towards Variation via Foundation Model: An Empirical Study of a Problem-Agnostic No-Code LLM-Guided Evolutionary Algorithm

The natural-language-based genetic algorithm (NaLaGA) shows that a generic, problem-independent genetic algorithm (GA) can function by utilizing large language models (LLMs) for all interactions with the solution candidates without ever running any LLM-generated code. We analyze inherent biases in the function of a NaLaGA approach from prior work and propose some architectural changes to increase its generalizability.

Sarah Gerner, Gerhard Stenzel, Thomas Gabor · 0 citations