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Computer Science > Neural and Evolutionary Computing

arXiv:2302.12600 (cs)
[Submitted on 24 Feb 2023 (v1), last revised 21 May 2023 (this version, v3)]

Title:EvoTorch: Scalable Evolutionary Computation in Python

Authors:Nihat Engin Toklu, Timothy Atkinson, Vojtěch Micka, Paweł Liskowski, Rupesh Kumar Srivastava
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Abstract:Evolutionary computation is an important component within various fields such as artificial intelligence research, reinforcement learning, robotics, industrial automation and/or optimization, engineering design, etc. Considering the increasing computational demands and the dimensionalities of modern optimization problems, the requirement for scalable, re-usable, and practical evolutionary algorithm implementations has been growing. To address this requirement, we present EvoTorch: an evolutionary computation library designed to work with high-dimensional optimization problems, with GPU support and with high parallelization capabilities. EvoTorch is based on and seamlessly works with the PyTorch library, and therefore, allows the users to define their optimization problems using a well-known API.
Subjects: Neural and Evolutionary Computing (cs.NE); Artificial Intelligence (cs.AI)
Cite as: arXiv:2302.12600 [cs.NE]
  (or arXiv:2302.12600v3 [cs.NE] for this version)
  https://doi.org/10.48550/arXiv.2302.12600

Submission history

From: Nihat Engin Toklu [view email]
[v1] Fri, 24 Feb 2023 12:37:45 UTC (946 KB)
[v2] Mon, 27 Feb 2023 16:40:47 UTC (946 KB)
[v3] Sun, 21 May 2023 16:21:03 UTC (946 KB)
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