These video lessons accompany Chapter 9 (Genetic Algorithms) from The Nature of Code book.
Genetic Algorithm Introduction29 Jul 2016
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.
Genetic Algorithm How it works29 Jul 2016
In part 2 of this genetic algorithm series, I explain how the concepts behind Darwinian Natural Selection are applied to a computational evolutionary algorithm.
Genetic Algorithm Shakespeare Monkey Example31 Jul 2016
Part 3 of the Genetic Algorithm series is dedicated to the Shakespeare Monkey Example. In this video, I use the evolutionary concepts from the previous video to compute a problem that a brute force algorithm wouldn’t be able to solve.
Genetic Algorithm Looking at Code31 Jul 2016
Genetic Algorithm Fitness, Genotype vs Phenotype01 Aug 2016
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).
Genetic Algorithm Improved Fitness Function05 Aug 2016
In this video I look at strategies for improving the genetic algorithm’s fitness function to improve efficiency and accuracy.
Genetic Algorithm Pool Selection05 Aug 2016
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.
Genetic Algorithm Improved Pool Selection03 May 2017
In this video, I look at yet another technique for “pool selection” – how to pick an item randomly from an array with a non-uniform distribution, i.e. some elements have higher probability of being picked than others. I use this same method in my Traveling Salesperson coding challenge, but it can be applied more broadly.
Genetic Algorithm Interactive Selection09 Aug 2016
In this genetic algorithms video, I discuss a technique known as “interactive selection” where the algorithm’s fitness function is calculated based on user / viewer interaction.
Genetic Algorithm Continuous Evolutionary System11 Aug 2016
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.
Genetic Algorithms and Evolutionary Computing11 Aug 2015
This video covers genetic algorithms and looks at how they are applied in 3 scenarios.