lgp

Core Rust library for Linear Genetic Programming.

Overview

lgp provides a trait-based framework for evolving sequences of register-based instructions to solve reinforcement learning and classification tasks. It includes built-in support for OpenAI Gym environments, Iris classification, and hybrid LGP + Q-Learning.

Installation

Add to your Cargo.toml:

[dependencies]
lgp = "1.3"

To enable OpenAI Gym environment support:

[dependencies]
lgp = { version = "1.3", features = ["gym"] }

Core Traits

The framework is built around these key traits:

• State - Represents an environment state with value access and action execution
• RlState - Extends State for RL environments with terminal state detection
• Core - Main trait defining the genetic algorithm components (registers, instructions, individuals)
• Fitness - Evaluates individual performance on a set of states
• Breed - Two-point crossover for creating offspring
• Mutate - Mutation operators for genetic variation

Modules

Quick Example

use lgp::core::engines::core_engine::CoreEngine;
use lgp::problems::iris::IrisLgp;

fn main() {
    // Configure and run an Iris classification experiment
    let engine = CoreEngine::<IrisLgp>::builder()
        .n_generations(100)
        .n_individuals(100)
        .build()
        .unwrap();

    engine.run();
}

See the examples directory and extension guide for more.

Features

Supported Environments