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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Updated
Dec 20, 2021 - Jupyter Notebook
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.
This collection of algorithms is part of a lecture on computational intelligence at ZHAW.
Design of a surrogate-assisted (mu/mu,lambda)-ES
Weight optimization of a truss structure via evolution strategy.
My Evolutionary Computing Lecture Project Codes Relies Here In Peace.
(EvoApps2022) "Towards a Principled Learning Rate Adaptation for Natural Evolution Strategies"
Gentech, A Genetic Algorithm Solver
Evolution Strategy Histogram Equalization
(GECCO2023 Best Paper Nomination) CMA-ES with Learning Rate Adaptation
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.
(GECCO 2023) Natural Evolution Strategy for Mixed-Integer Black-Box Optimization
(CEC2022) Fast Moving Natural Evolution Strategy for High-Dimensional Problems
Minimal PyTorch Library for Natural Evolution Strategies
CMA-ES in MATLAB
Unity In Editor Deep Learning Tools. Using KerasSharp, TensorflowSharp, Unity MLAgent. In-Editor training and no python needed.
Flappy Bird AI using Evolution Strategies
Python library for CMA Evolution Strategy.
Evolutionary Algorithm using Python, 莫烦Python 中文AI教学
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