Module gep 

Gene Expression Programming (GEP).

GEP (Ferreira, 2001) evolves programs encoded as fixed-length linear chromosomes that decode into expression trees. Each chromosome is a head (whose loci may hold any symbol) followed by a tail (terminals only), sized so that every chromosome respecting that split decodes to a complete tree — no repair pass is ever needed. This makes the genetic operators simple, position-aligned array edits, which is GEP’s headline advantage over tree-based GP.

Module map

• config — GepConfig: runtime head/tail/population parameters; the tail length is derived and the head/tail constraint asserted at construction.
• alphabet — Alphabet and SymbolKind: the function set plus the variable/constant terminal layer, with the contiguous id-space and the tail terminal_range.
• tree — ExpressionTree: the level-order decoded phenotype with eval/depth/node_count.
• decode — GenotypePhenotypeMap and GepDecoder: the deterministic ORF-scan + BFS decoder.
• operators — point mutation (locus-class aware), IS/RIS transposition, and one-/two-point crossover, all valid by construction.
• strategy — GepStrategy, GepState, and the GepSymRegression fitness function.

Genotype storage is a Tensor<B, 2, Int> of shape (pop_size, head_len + tail_len); decoding and evaluation run host-side, per chromosome, because the decode is an inherently sequential ORF scan that does not vectorise.

Reference

• Ferreira (2001), Gene Expression Programming: a New Adaptive Algorithm for Solving Problems, Complex Systems 13(2).

Re-exports

pub use alphabet::Alphabet;

pub use alphabet::SymbolKind;

pub use config::GepConfig;

pub use decode::GenotypePhenotypeMap;

pub use decode::GepDecoder;

pub use strategy::GepState;

pub use strategy::GepStrategy;

pub use strategy::GepSymRegression;

pub use tree::ExpressionTree;

Modules

alphabet

The GEP symbol alphabet: functions plus a terminal layer.

config

Runtime configuration for a Gene Expression Programming run.

decode

Genotype → phenotype decoding (the head/tail → expression-tree map).

operators

GEP genetic operators, all valid by construction (no repair pass).

strategy

The GepStrategy evolutionary engine and a symbolic-regression fitness.

tree

The decoded GEP phenotype: a level-order expression tree.