Agentic AI can automate parts of genetic programming system design using LLM reasoning and retrieval-augmented generation

We investigate whether agentic artificial intelligence can automate parts of the process of designing genetic programming systems by introducing an agentic framework that identifies and implements parent selection algorithms using large language model (LLM) reasoning and retrieval-augmented generation.

http://arxiv.org/abs/2608.17172v2