This collection of algorithms is part of a lecture on computational intelligence at ZHAW.
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Updated
May 22, 2015 - Python
This collection of algorithms is part of a lecture on computational intelligence at ZHAW.
Design of a surrogate-assisted (mu/mu,lambda)-ES
Unity In Editor Deep Learning Tools. Using KerasSharp, TensorflowSharp, Unity MLAgent. In-Editor training and no python needed.
CMA-ES in MATLAB
My Evolutionary Computing Lecture Project Codes Relies Here In Peace.
Minimal PyTorch Library for Natural Evolution Strategies
Flappy Bird AI using Evolution Strategies
Java (optimization) and Python (hypertuning, plots) code with implementation of many global random optimization methods written as part of my MSc in Data Science degree.
Evolution Strategy Histogram Equalization
(EvoApps2022) "Towards a Principled Learning Rate Adaptation for Natural Evolution Strategies"
Gentech, A Genetic Algorithm Solver
Weight optimization of a truss structure via evolution strategy.
(CEC2022) Fast Moving Natural Evolution Strategy for High-Dimensional Problems
Evolutionary Algorithm using Python, 莫烦Python 中文AI教学
(GECCO2023 Best Paper Nomination) CMA-ES with Learning Rate Adaptation
(GECCO 2023) Natural Evolution Strategy for Mixed-Integer Black-Box Optimization
Python library for CMA Evolution Strategy.
Optimziation includes a class of methods to find global or local optimums for discrete or continuous objectives; from evolutionary-based algorithms to swarm-based ones.
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