JSPM

A Genetic Algorithm

Multiprocessing genetic algorithm implementation library

An advanced cryptocurrency trading framework for TypeScript

Simple genetic algorithm helper class. Supports asynchronous fitness evaluation.

Tiny, zero-dependency GA/GP engine for TypeScript/JS with first-class types, deterministic RNG, and budget-aware runs.

Multiprocessing genetic algorithm implementation library extension

Shared solver library for floorplan optimization - compatible with Node.js and Deno

TypeScript implementation of GEPA (Gradient-free Evolution of Prompts and Agents) - Complete port with 100% feature parity

Genetic algorithm

TinyNEAT is a tiny, js-native NEAT (NeuroEvolution of Augmenting Topologies) library, meant to easily incorporate into any codebase.

This is an ongoing project intended to make it easier to use neural network creation, genetic algorithms, and other data science and machine learning skills.

A simplistic neural network library.

Small framework for genetic algorithms

Genetic-Pareto prompt optimizer to evolve system prompts from a few rollouts with modular support and intelligent crossover

Simple and clear JavaScript class for genetic algorithms. Contains helpful functions to get you going.

A lightweight genetic algorithm library.

Lightweight TypeScript neural network library with back-propagation and genetic algorithms, supporting a wide range of activation functions, all without extra build or native dependencies.

This is an ongoing project intended to make it easier to use neural network creation, genetic algorithms, and other data science and machine learning skills.

A Node-RED node to simulate a basic genetic algorithm

Machine learning library written in javascript

A Node.js module to calculate an adaptive mutation rate for genetic algorithms.

A functional genetic algorithm library

Simple genetic algorithm implementation

Self-learning evolutionary game theory with multi-agent tournaments, replicator dynamics, and ESS calculation