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EvoTorch

Freemium
EvoTorch screenshot
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About

EvoTorch™ is a cutting-edge open-source library built to accelerate research and applications of Evolutionary Algorithms (EAs), with a strong focus on NeuroEvolution. It provides state-of-the-art algorithms and utilities, leveraging PyTorch for defining objective functions and supporting GPU acceleration. EvoTorch is designed to reduce boilerplate code, allowing users to focus on solving problems at scale. Its features include scalable parallelism across multiple CPU and GPU nodes, built on Ray and PyTorch. It offers flexibility for various tasks such as searching the space of images, programs, or designs; optimizing large-scale single/multiobjective engineering problems; implementing fast Model Predictive Control with learned dynamics models; and evolving high-performance neural controllers for complex reinforcement learning tasks (neuroevolution). Enterprise support for customization and deployment is also available from NNAISENSE.

Platform
Web
Task
algorithm optimization

Features

designed to reduce boilerplate for complex problem solving

provides state-of-the-art evolutionary algorithms and utilities

supports model predictive control and reinforcement learning tasks

facilitates large-scale single and multi-objective optimization

enables scalable parallelism across multiple cpu and gpu nodes

supports gpu acceleration for faster computations

integrates seamlessly with pytorch for defining objective functions

accelerates evolutionary algorithms and neuroevolution research

Pricing Plans

Enterprise Support
Unknown Price

Customization for domain-specific problems

Support for preferred compute environments

Production deployments

Maintenance of trained solutions

Open-Source
Free Plan

GPU acceleration

Multiple objectives

Parallelized RL

Scalable parallelism

Exploration and optimization

Model Predictive Control

Neuroevolution

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