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EASE-ing into Global Optimization with LLMs A competition entry on LLM-designed Evolutionary Algorithms at The Genetic and Evolutionary Computation Conference (GECCO) 2025

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F25%3A63599938" target="_blank" >RIV/70883521:28140/25:63599938 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1145/3712255.3735096" target="_blank" >http://dx.doi.org/10.1145/3712255.3735096</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3712255.3735096" target="_blank" >10.1145/3712255.3735096</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    EASE-ing into Global Optimization with LLMs A competition entry on LLM-designed Evolutionary Algorithms at The Genetic and Evolutionary Computation Conference (GECCO) 2025

  • Original language description

    This paper presents an extended abstract describing an entry into the LLM for evolutionary algorithms tailored benchmarking competition using a GNBG-generated test suite. This study explores the generative design of optimization algorithms using large language models (LLMs) within the EASE modular framework, which supports iterative prompting and feedback-driven refinement. Across five successive generations, we observed a progressive transformation in algorithmic structure. The findings suggest opportunities for further research into the role of prompt design, feedback phrasing, and framework architecture in guiding the emergence of more task-adaptive, domain-specialized algorithmic behavior.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    PROCEEDINGS OF THE 2025 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2025 COMPANION

  • ISBN

    979-8-4007-1464-1

  • ISSN

  • e-ISSN

  • Number of pages

    2

  • Pages from-to

    7-8

  • Publisher name

    Association for Computing Machinery, Inc

  • Place of publication

    New York

  • Event location

    Malaga

  • Event date

    Jul 14, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001564494900004