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faber_tweann

2.2.0
2.4.0 2.2.0 2.1.0 2.0.1 2.0.0 retired 1.2.0 1.1.0 1.0.0 0.1.0

Faber TWEANN - Topology and Weight Evolving Artificial Neural Networks

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faber_tweann assets neat-evolution.svg
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assets/neat-evolution.svg 

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  <!-- Title -->

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    NEAT Topology Evolution: Structural Mutations

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    Generation 0: Initial Network

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    Genes: [(1,2,0.8,enabled)]

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    Innovation: 1

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    add_node Mutation

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    Genes: [(1,3,1.0,en), (3,2,0.8,en), (1,2,disabled)]

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    Innovations: 1, 2, 3

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    add_link Mutation

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    Skip connection added

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    Innovation: 4

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    Weight Mutation

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    w = 0.8

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    w = 0.8 + gaussian(0, 0.1) = 0.73

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    Perturb or replace with new random value

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    Crossover (Sexual Reproduction)

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    Speciation

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    Compatibility Distance:

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    d = c1*E/N + c2*D/N + c3*W

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    NEAT Innovation Numbers

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    Each new structural mutation gets a unique innovation number, enabling:

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    1. Tracking homologous genes across genomes (same innovation = same structure)

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    2. Meaningful crossover alignment

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    3. Computing compatibility distance for speciation

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    4. Historical markings that persist across generations

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    Based on: K. Stanley and R. Miikkulainen, "Evolving Neural Networks through Augmenting Topologies" (2002)

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    Innovation Timeline

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