# EvoPrompt

> EvoPrompt optimizes prompts with evolutionary algorithms, such as genetic algorithms and differential evolution, in which a language model performs the crossover and mutation steps on a population of prompts.

- Identifier: PTL-0154
- Category: Prompt Optimization
- Canonical URL: https://protologue.com/t/evoprompt/
- Introduced: 2023

## Description

Using the model as the evolutionary operator keeps every candidate a readable, coherent prompt while borrowing the exploration properties of classical evolutionary search. It needs only API access to the model, not its gradients.

## Broader terms

- [Prompt Optimization](https://protologue.com/t/prompt-optimization/)

## Related terms

- [Promptbreeder](https://protologue.com/t/promptbreeder/)
- [Automatic Prompt Engineer](https://protologue.com/t/automatic-prompt-engineer/)

## Sources

- Guo et al. (2023). EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers. https://arxiv.org/abs/2309.08532

## Cite this entry

Protologue. (2026). EvoPrompt. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.4.0, PTL-0154). https://protologue.com/t/evoprompt/

License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)