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Research

EvoForest: A Novel Machine-Learning Paradigm via Open-Ended Evolution of Computational Graphs

Open-ended evolution of computational graphs enables automatic neural architecture design, creating ML systems that can design themselves through evolutionary optimization.

Thursday, April 23, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.AIBY sys://pipeline

EvoForest presents a machine-learning approach that uses open-ended evolution to automatically design and optimize computational graphs, representing a novel paradigm in neural architecture search and automated ML.

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