Evolutionary strategies for function optimization
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Updated
Sep 27, 2021 - MATLAB
Evolutionary strategies for function optimization
Projekt na przedmiot Algorytmy Genetyczne
Python implementation of evolution strategy based on Information Geometry. This library includes CMA-ES, NES, CompactGA and PBIL.
Various studies show that criticality is an attractor in biological evolution. Which conditions have to be fulfilled, such that criticality acts as an attractor in our neuroevolution simulation? -- Masters Thesis Project ---
Paper: https://doi.org/10.1162/isal_a_00412 Which dynamical regime is beneficial for biological systems? Agent-based evolutionary foraging game with experiments to evaluate generalizability, ability to perform complex tasks and evolvability.
Two simulations that may explain the origin of morality within the framework of evolutionary game theory.
Evolution Strategy (ES) in MATLAB according to the generational ES algorithm that search for a real-valued vector of length 30, which represents the thickness of each layer in a 30-layered optical system.
Cyber therapy ,experimental concept 0f social engineering for the good
Course of Stochastic Optimization in ISAE-SUPAERO
Multi Objective Evolutionary Algorithm for Soft Computing Applications
https://www.researchgate.net/publication/350344034_Sequence-based_model_of_cumulative_cultural_evolution Evolutionary Algorithm based on Cumulative Cultural Evolution. Uses a mix of gradient descent - individual learning - and inheritance - copying - that selection acts upon. Serves as sequene-based model of cumulative cultural evolution - Focus…
High performance implementation of Deep neuroevolution in pytorch using mpi4py. Intended for use on HPC clusters
Implementation of EDCA-Net published in International Journal of Neural System.
Implementation of the "Evolutionary Strategy" algorithm in Java. It can be used to optimize parameters using evolutionary computation.
ES using GP as objective function approximation
Particle Swarm Optimization and Evolutionary Strategy
Dissertation for Imperial BEng Maths and CS
Small experiments on MNIST to evaluate ES and GA against SGD
Genetic algorithms and evolutionary strategy implementation to solve Ackley function
Meta-Evolver is a tool for a visual representation of the various dynamic environment models that correlate in multi-layered system. Meta-Evolved provides the environment for testing dynamic spatial adaptation, where the environment is composed of algorithms and parametric definitions.
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