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  "headline": "Swarm and Evolutionary Intelligence: Genetic Algorithms, NEAT, and Particle Swarms",
  "description": "Evolutionary computation draws inspiration from biological evolution — mutation, crossover, selection — to optimize without gradients. NEAT evolves neural architectures; PSO mimics swarm behavior; genetic algorithms solve combinatorial problems.",
  "dateCreated": "2026-05-24T02:49:13.663Z",
  "dateModified": "2026-05-24",
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    "@type": "Organization",
    "name": "AnchorFact",
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  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "ai_assisted",
  "citation": [
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      "name": "Evolving Neural Networks through Augmenting Topologies (NEAT)",
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      "@type": "CreativeWork",
      "name": "Particle Swarm Optimization: A Comprehensive Survey",
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