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GPStar4: A flexible framework for experimenting with genetic programming

Published: 24 July 2023 Publication History

Abstract

GPStar4 is a flexible workbench for experimenting with population algorithms. It is a framework that defines a genetic cycle, with inflection points for implementing an algorithm's specific behaviors; it also provides a variety of implementations for these inflection points. A user of the system can select from the provided implementations and customize the places where alternative behavior is desired, or even create their own implementations. Components interact through a context mechanism that enables both mutable and immutable information sharing, type checking, computed defaults and event listeners.
Interesting predefined components included in GPStar4 are implementations for classical tree-based expression structures; acyclic multigraphs with named ports, type systems for flat, hierarchical and attribute types, recursively defined populations using both subpopulation and build-from-parts semantics, and numeric and multi-objective fitnesses. Key enabling technologies for this flexibility include context mechanisms, choosers, and a variety of caches.
GPStar4 can be run as an API library for other applications, as a command-line application, or as a stand-alone application with its own GUI.

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  • (2023)MLStar: A System for Synthesis of Machine-Learning ProgramsProceedings of the Companion Conference on Genetic and Evolutionary Computation10.1145/3583133.3596367(1721-1726)Online publication date: 15-Jul-2023

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    cover image ACM Conferences
    GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation
    July 2023
    2519 pages
    ISBN:9798400701207
    DOI:10.1145/3583133
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    Published: 24 July 2023

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    Author Tags

    1. genetic programming
    2. directed acyclic graph representations
    3. population algorithms
    4. experimental framework

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    • (2023)MLStar: A System for Synthesis of Machine-Learning ProgramsProceedings of the Companion Conference on Genetic and Evolutionary Computation10.1145/3583133.3596367(1721-1726)Online publication date: 15-Jul-2023

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