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3 repositorios

Awesome GitHub RepositoriesGenetic Program Evolution

Represents solutions as tree structures and applies crossover, mutation, and selection to evolve them over generations.

Distinct from Tree-Based Optimization: Distinct from general Tree-Based Optimization: specifically for evolving programs via genetic operators, not for DP-based tree aggregation.

Explore 3 awesome GitHub repositories matching software engineering & architecture · Genetic Program Evolution. Refine with filters or upvote what's useful.

Awesome Genetic Program Evolution GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • deap/deapAvatar de DEAP

    DEAP/deap

    6,336Ver en GitHub↗

    Represents solutions as tree structures and evolves them using crossover, mutation, and selection.

    Python
    Ver en GitHub↗6,336
  • algorithmicsuperintelligence/openevolveAvatar de algorithmicsuperintelligence

    algorithmicsuperintelligence/openevolve

    5,421Ver en GitHub↗

    OpenEvolve is an open-source framework for evolutionary computation that uses language models to drive automated optimization across multiple domains. It can evolve system prompts for large language models, refine source code across programming languages, search for optimal GPU kernel configurations, discover interpretable mathematical expressions from data, and maintain diverse populations of high-performing solutions. The framework integrates multiple evolutionary strategies, including MAP-Elites diversity mapping and island-based topologies, to avoid premature convergence and preserve a wid

    Evo evolves a program that passes all test cases on an online judge by iteratively mutating and selecting candidate solutions.

    Pythonalpha-evolvealphacodealphaevolve
    Ver en GitHub↗5,421
  • chrxh/alienAvatar de chrxh

    chrxh/alien

    5,354Ver en GitHub↗

    Evolve is an evolution-based organism designer and GPU-accelerated artificial life simulator that combines interactive particle physics with a real-time simulation editor. At its core, it runs genetic algorithm evolution on self-replicating graph structures to evolve digital organisms, offloading particle physics, neural networks, and rendering entirely to the GPU through a compute shader pipeline for real-time performance. The project distinguishes itself with graph-based organism design that uses a directed graph editor to visually define organism structure, connections, and neural controll

    Evolves digital organisms with neural networks and genetic algorithms to develop complex behaviors without manual programming.

    C++agent-based-simulationartificial-lifecuda
    Ver en GitHub↗5,354
  1. Home
  2. Software Engineering & Architecture
  3. Trees
  4. Tree Node Templates
  5. Tree-Based Optimization
  6. Genetic Program Evolution

Explorar subetiquetas

  • Competitive Programming Solution Evolution1 sub-etiquetaEvolving programs that pass all test cases on online judges through iterative mutation and selection. **Distinct from Genetic Program Evolution:** Distinct from Genetic Program Evolution: targets competitive programming problems with test-case validation, not general program evolution.