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Deep dives into evolutionary computation, project updates, and community news.
EvoGO: GPU Compute × Generative Learning → A New Paradigm for Evolutionary Algorithms with 10-Generation Convergence
EvoGO is a fully data-driven evolutionary optimization framework that learns how to generate better solutions from past search experience and achieves fast, strong performance on complex high-dimensional tasks.
iStratDE: GPU Computing x Ultra-Large Populations Unlock the Full Potential of Differential Evolution
The EvoX team introduces iStratDE, a GPU-accelerated differential evolution method that assigns fixed strategies at the individual level, enabling communication-free large-scale parallel search with strong empirical performance and theoretical convergence guarantees.
EvoX Quickstart: Run GPU-Accelerated Evolutionary Computation in Just 10 Minutes
A beginner's tutorial to get started with GPU-accelerated evolutionary computation using EvoX in just 10 minutes.
GPU-Accelerated Evolutionary Multiobjective Optimization
Bridging Evolutionary Multiobjective Optimization and GPU Acceleration via Tensorization, introducing the EvoMO library.
MetaDE: Evolving Differential Evolution by Differential Evolution
MetaDE is a meta-evolutionary method that uses Differential Evolution to evolve its own hyperparameters and strategies, published in IEEE TEVC.
EvoRL: A GPU-Accelerated Framework for Evolutionary Reinforcement Learning
EvoRL is an open-source Evolutionary Reinforcement Learning framework that integrates evolutionary algorithms with RL for improved exploration and adaptability.
EvoGP: A GPU-Accelerated Framework for Tree-Based Genetic Programming
EvoGP is a fully GPU-accelerated Tree-Based Genetic Programming framework built on PyTorch, achieving up to 100x speedup over CPU implementations.