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Source codes for HHO paper: Harris hawks optimization: Algorithm and applications: https://www.sciencedirect.com/science/article/pii/S0167739X18313530. In this paper, a novel population-based, nature-inspired optimization paradigm is proposed, which is called Harris Hawks Optimizer (HHO).

computer-science engineering optimization modeling artificial-intelligence evolutionary-algorithms evolutionary-computation optimization-algorithms evolutionary-strategy computational-intelligence metaheuristics swarm-intelligence algorithms-and-data-structures

Updated Jun 16, 2022
MATLAB

jbrea / CMAEvolutionStrategy.jl

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optimization evolutionary-algorithm evolutionary-strategy stochastic-optimization derivative-free blackbox-optimization cma-es derivative-free-optimization

Updated Oct 28, 2022
Julia

scheckmedia / cgp-cnn-design

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Using Cartesian Genetic Programming to find an efficient Convolutional Neural Network architecture

python tensorflow keras python3 evolutionary-algorithms evolutionary-strategy cnn-architecture cgp cartesian-genetic-programming

Updated Feb 6, 2018
Python

sash-a / es_pytorch

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High performance implementation of Deep neuroevolution in pytorch using mpi4py. Intended for use on HPC clusters

reinforcement-learning ai mpi neuroevolution pytorch gym evolutionary-strategy mpi4py deep-neuroevolution

Updated Jan 24, 2022
Python

sgonzalez / SwiftCMA

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A pure-Swift implementation of Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES).

evolutionary-algorithms evolutionary-strategy covariance-matrix-adaptation

Updated Apr 24, 2020
Swift

NiMlr / High-Dim-ES-RL

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Paper: Challenges in High-dimensional Reinforcement Learning with Evolution Strategies

machine-learning reinforcement-learning optimization neuroevolution neural-networks evolutionary-algorithms evolutionary-computation control-theory evolutionary-strategy evolution-strategies derivative-free stochastic-control

Updated May 30, 2022
Python

shashankkotyan / RobustArchitectureSearch

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This github repository contains the official code for the paper, "Evolving Robust Neural Architectures to Defend from Adversarial Attacks"

deep-neural-networks deep-learning neural-network paper neuroevolution neural-networks evolutionary-algorithms evolutionary-algorithm evolutionary-computation neuralnetwork neural-nets evolutionary-strategy robustness neuralnetworks evolution-strategies neural-architecture-search adversarial-machine-learning architecture-search robustness-verification robustness-experiments

Updated Jun 22, 2022
Python

giuse / machine_learning_workbench

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Workbench for practical machine learning in Ruby.

machine-learning reinforcement-learning neural-network optimization modeling machine-learning-algorithms neuroevolution neural-networks evolutionary-algorithms evolutionary-algorithm black-box-optimization evolutionary-computation optimization-algorithms evolutionary-strategy evolution-strategies rubyml natural-evolution-strategies machine-learning-workbench

Updated Nov 2, 2021
Ruby

entrpn / fingym

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A tool for developing reinforcement learning algorithms focused in stock prediction

python reinforcement-learning q-learning artificial-intelligence stock-market stock-price-prediction evolutionary-algorithms evolutionary-strategy artificial-intelligence-algorithms evolution-strategies reinforcement-agents reinforcement-learning-playground reinforcement-learning-environments

Updated May 4, 2022
Python

AStupidBear / GCMAES.jl

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Gradient-based Covariance Matrix Adaptation Evolutionary Strategy for Real Blackbox Optimization

optimization parallel mpi distributed-computing gradient evolutionary-computation elemental evolutionary-strategy cma evolution-strategies

Updated Aug 4, 2022
Julia

satuma777 / evoltier

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[WIP] Python implementation of evolution strategy based on Information Geometry. This library includes CMA-ES, NES, CompactGA and PBIL.

python evolutionary-algorithms evolutionary-computation optimization-algorithms evolutionary-strategy

Updated May 2, 2019
Python

underwit / agentsmith

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Нейронная сеть оптимизируемая с помощью генетического алгоритма. Задача агента контролируемого при помощи нейронной сети состоит в том, чтобы избегать контакта с противниками, как можно более длительное время.