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Agentic AI automates genetic programming configuration

By PulseAugur Editorial · [1 sources] ·

Researchers have developed an agentic AI framework to automate the configuration of parent selection algorithms in genetic programming. This framework utilizes large language model reasoning and retrieval-augmented generation to identify and implement these algorithms. In tests using symbolic regression, the agentic setup with 5 mini--AR demonstrated competitive performance, generating established epsilon-lexicase implementations and outperforming tournament selection on several problems. AI

IMPACT Demonstrates potential for AI to automate complex system design, potentially accelerating research and development in evolutionary computation.

RANK_REASON Academic paper detailing a novel application of AI in automating a component of evolutionary algorithms. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.NE (Neural & Evolutionary) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Agentic AI automates genetic programming configuration

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Academic paper detailing a novel application of AI in automating a component of evolutionary algorithms. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Jason H. Moore ·

    Automating Parent Selection Configuration in Genetic Programming with Agentic AI

    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 retrieva…

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