EvoX Ecosystem
A collection of libraries, tools, and projects designed to accelerate computation and optimization research.
EvoCmo
A fully tensorized, GPU-accelerated multi-population evolutionary algorithm for efficiently solving constrained multi-objective optimization problems (CMOPs).
EvoGit
A decentralized multi-agent framework that reimagines software development as a collaborative, evolutionary process.
EvoGO
A fully data-driven framework for black-box optimization, replacing manual heuristic operators by learning search behaviors from historical data.
EvoGP
A fully GPU-accelerated Tree-based Genetic Programming (TGP) framework built on PyTorch.
EvoMO
A GPU-accelerated library for evolutionary multiobjective optimization (EMO) via advanced tensorization.
EvoNAS
A framework for neural architecture search, implemented with PyTorch. It supports supernet training, evolutionary multi-objective optimization, and seamless integration with modern computer vision training pipelines.
EvoRL
A fully GPU-accelerated framework for Evolutionary Reinforcement Learning.
EvoX
A distributed GPU-accelerated evolutionary computation framework compatible with PyTorch.
EvoXBench
A platform offering instant benchmarking of evolutionary multi-objective optimization (EMO) algorithms in neural architecture search (NAS).
iStratDE
A GPU-accelerated Differential Evolution framework that enhances performance through individual-level strategy diversity.
MetaDE
An advanced evolutionary framework that dynamically optimizes the strategies and hyperparameters of Differential Evolution.
TensorNEAT
A JAX-based library for NeuroEvolution of Augmenting Topologies (NEAT) algorithms.