Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.
An Advanced Evolutionary library or algorithm has been a dream of scientists and AI/ML enthusiasts since the concept was introduced. This vision has come true thanks to the scientists at NNAISENSE, a Switzerland-based AI Enterprise. They created an open-source platform called EvoTorch. When operated in combination with Machine Learning, it can solve complex operational problems in a fraction of time, with lower costs, and at a larger scale. Evolutionary algorithms act as a step toward solving cascading problems that occur when the problem’s size and complexity increase. Evolutionary algorithms make the situations easier to handle the complexity without adding to the cost, they are also much easier to connect through GPUs and CPUs parallelly to ease up the calculation time and the complexity associated with it, that the only limit to your computational power becomes your budget. The evolutionary algorithms are built in the open framework EvoTorch.
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[P] EvoTorch 0.4.0 dropped with GPU-accelerated implementations of CMA-ES, MAP-Elites and NSGA-II.
2 projects | /r/MachineLearning | 26 Jan 2023
Question on how to model a "discontinuous" action space
4 projects | /r/reinforcementlearning | 9 Dec 2022
Should I pursue Evolutionary Strategies?
5 projects | /r/reinforcementlearning | 4 Dec 2022
[P] We’ve released EvoTorch 0.3.0, with VecGymNE, memory usage improvements, Colab support and more! VecGymNE enables evolutionary RL with vectorized environments and policies, especially massively parallel simulators like Brax!
1 project | /r/MachineLearning | 25 Oct 2022
[P] Participating in the Myosuite challenge at NeurIPS2022 on dexterous control? We are releasing a baseline and starter code to help you get started using EvoTorch!
2 projects | /r/MachineLearning | 28 Sep 2022