9.2: Genetic Algorithm: How it works - The Nature of Code
In part 2 of this genetic algorithm series, I explain how the concepts behind Darwinian Natural Selection are applied to a computational evolutionary algorithm. 🎥 Previous video: https://youtu.be/9zfeTw-uFCw?list=RxTfc4JLYKs&list=PLRqwX-V7Uu6bJM3VgzjNV5YxVxUwzALHV 🎥 Next video: https://yo
From playlist Session 2 - Genetic Algorithms - Intelligence and Learning
Selective Breeding | Evolution | Biology | FuseSchool
Selective Breeding | Evolution | Biology | FuseSchool Selective breeding is also known as artificial selection. It is the process by which humans breed plants and animals for particular genetic characteristics. We have been doing this for thousands of years - ever since we first bred fo
From playlist BIOLOGY: Evolution
9.1: Genetic Algorithm: Introduction - The Nature of Code
Welcome to part 1 of a new series of videos focused on Evolutionary Computing, and more specifically, Genetic Algorithms. In this tutorial, I introduce the concept of a genetic algorithm, how it can be used to approach "search" problems and how it relates to brute force algorithms. 🎥 Next
From playlist Session 2 - Genetic Algorithms - Intelligence and Learning
Mechanisms of Natural Selection Part 1: Types of Sexual Selection
We touched upon sexual selection when we learned about natural selection. Essentially when there is a variance in the reproductive success of a particular sex for a given species, secondary sex characteristics will develop in that species, because one sex has the opportunity to choose a ma
From playlist Biology/Genetics
Support Stated Clearly on Patreon: https://www.patreon.com/statedclearly Special thanks to Rosemary at Bird and Moon Comics for supplying a handful of the critter illustrations: http://www.birdandmoon.com/ Special thanks to AD for the music! http://www.proofavenue.com/ Natural Selectio
From playlist Most popular from Stated Clearly & Friends
Data Science - Part XIV - Genetic Algorithms
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview on biological evolution and genetic algorithms in a machine learning context. W
From playlist Data Science
Binary Genetic Algorithm - Part 5: Crossover and Mutation Operations
This video is about Binary Genetic Algorithm - Part 5: Crossover and Mutation Operations
From playlist Optimization
Continuous Genetic Algorithm - Part 1
This video is about Continuous Genetic Algorithm - Part 1
From playlist Optimization
Machine Learning Control: Genetic Algorithms
This lecture provides an overview of genetic algorithms, which can be used to tune the parameters of a control law. Machine Learning Control T. Duriez, S. L. Brunton, and B. R. Noack https://www.springer.com/us/book/9783319406237 Closed-Loop Turbulence Control: Progress and Challenges
From playlist Data-Driven Control with Machine Learning
9.7: Genetic Algorithm: Pool Selection - The Nature of Code
In this Genetic Algorithm video, I discuss improvements and strategies for "pool selection" (such as rejection sampling / monte carlo simulation) to pick "parents" based on probabilities mapped to their fitness score. https://thecodingtrain.com/more/archive/nature-of-code/9-genetic-algorit
From playlist Session 2 - Genetic Algorithms - Intelligence and Learning
Paul Andersen explains the importance of selection in biology. Artificial selection occurs when humans choose traits that will be selected for or against. This has created the variety of domesticated animals and crops. He then describes the three main types of ecological natural selecti
From playlist Biology
my first attempt at a genetic algorithm -- Watch live at https://www.twitch.tv/simuleios
From playlist Genetic Algorithms!
Intro Into Multi Objective Optimization
Multi-objective optimization (also known as multi-objective programming, vector optimization, multiattribute optimization or Pareto optimization) is an area of multiple criteria decision making that is concerned with mathematical optimization problems involving more than one objective func
From playlist Software Development
9.4: Genetic Algorithm: Looking at Code - The Nature of Code
In part 4 of the series on Genetic Algorithm, I finally look at code! Using p5.js (and Processing / Java in the addendum), I implement the Shakespeare Monkey genetic algorithm example in JavaScript. https://thecodingtrain.com/more/archive/nature-of-code/9-genetic-algorithms/9.4-looking-at-
From playlist Session 2 - Genetic Algorithms - Intelligence and Learning
9.x: Genetic Algorithms and Evolutionary Computing - The Nature of Code
This video covers genetic algorithms and looks at how they are applied in 3 scenarios. 1: search problems where brute force is an impossibility (infinite monkey theorem). 2: physics-based systems 3: Interactive selection (i.e. user behavior driven fitness). This video is excerpted
From playlist The Nature of Code: Simulating Natural Systems
9.5: Genetic Algorithm: Fitness, Genotype vs Phenotype - The Nature of Code
In part 5 of my genetic algorithm series I discuss how you can adapt the algorithm for your own creative project. The key pieces are designing and implementing a custom "fitness function" as well as how you choose to encode your DNA (genotype vs phenotype). https://thecodingtrain.com/more/
From playlist Session 2 - Genetic Algorithms - Intelligence and Learning