In genetic algorithms, a chromosome (also sometimes called a genotype) is a set of parameters which define a proposed solution to the problem that the genetic algorithm is trying to solve. The set of all solutions is known as the population. The chromosome is often represented as a binary string, although a wide variety of other data structures are also used. (Wikipedia).
https://www.patreon.com/statedclearly Ever get confused about the difference between DNA, genes, and Chromosomes? If so, don't worry. We straighten it all out here! Arabic CC by Mustafa Farqad and Mohammed Baset #chromosome #gene #biology
From playlist Most popular from Stated Clearly & Friends
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
What Are Chromosomes | Genetics | Biology | FuseSchool
In the nucleus of each eukaryotic cell, the DNA is packaged together into chromosomes. Each chromosome is made up of DNA that is tightly coiled around proteins that give it the structure. Chromosomes usually occur in pairs, except for gametes (eggs and sperm cells) but the number of ch
From playlist BIOLOGY: Genetics
9.10: Genetic Algorithm: Continuous Evolutionary System - The Nature of Code
In this video, I apply the Genetic Algorithm to an "Ecosystem Simulation", a system in which models biological life more closely, where elements live and die continuously evolving over time. 💻Code : https://github.com/CodingTrain/Rainbow-Code 🎥Previous video : https://youtu.be/Zy_obitkyO
From playlist Session 2 - Genetic Algorithms - Intelligence and Learning
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
Continuous Genetic Algorithm - Part 1
This video is about Continuous Genetic Algorithm - Part 1
From playlist Optimization
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
What can a postman teach us about genetics? (Travelling Salesman Problem)
Thanks for watching! Chapters: 0:00 Introduction and Overview 0:18 The Problem 0:49 Genetic Algorithms 3:14 Abstraction and Problem Solving 4:43 Test and Visualization 5:30 Ending #geneticalgorithm #artificialintelligence #some2 #programming #algorithm #algorithms #machinelearning #genet
From playlist Summer of Math Exposition 2 videos
Teach Astronomy - Genetic Code
http://www.teachastronomy.com/ The sequence of base pairs along the long DNA chain molecule is the genetic code. Think of it as a four letter alphabet, A,T,G, and C, combining according to particular rules and many base pairs in sequence. The basic piece of information in the genetic cod
From playlist 25. Early Earth and Life Processes
How algorithms evolve (Genetic Algorithms)
So, here's the deal: this video was made in collaboration with a bunch of other cool content creators who all wanted to talk about evolution. Check out their work here: https://www.youtube.com/watch?v=ehuEaLvA1B4&list=PLnQX-jgAF5pQVXOaTu7BSB6AMjtbnS3b_ Outside of that, thanks so much for
From playlist Evolution Collaboration
Jean Philippe Vert - Machine learning against cancer
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From playlist Conférence IA / 16 et 17 novembre 2021 à l'IHP
Binary Genetic Algorithm - Part 3: Decision Variables, Costs, Population, Natural Selection Process
This video is about Binary Genetic Algorithm - Part 3: Decision Variables, Cost Functions and Population and Natural Selection Process
From playlist Optimization
13. Learning: Genetic Algorithms
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston This lecture explores genetic algorithms at a conceptual level. We consider three approaches to how a population evolves towards desirable traits, ending with ra
From playlist MIT 6.034 Artificial Intelligence, Fall 2010
Binary Genetic Algorithm - Part 2: Working Principle and Coding/Encoding Processes
This video is about Binary Genetic Algorithm - Part 2: Working Principle and Coding/Encoding Processes
From playlist Optimization
Evolutionary Genetics in the Crush of Genomics
Charles H. Langley, UC Davis Simons Institute Open Lectures http://simons.berkeley.edu/events/openlectures2014-spring-3
From playlist Simons Institute Berkeley
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
Sexual vs. asexual reproduction, multiple loci by Nick Barton
Second Bangalore School on Population Genetics and Evolution URL: http://www.icts.res.in/program/popgen2016 DESCRIPTION: Just as evolution is central to our understanding of biology, population genetics theory provides the basic framework to comprehend evolutionary processes. Population
From playlist Second Bangalore School on Population Genetics and Evolution