<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Machine - Tag - Lewis Watson</title><link>http://lnwatson.co.uk/tags/machine/</link><description>Machine - Tag - Lewis Watson</description><generator>Hugo -- gohugo.io</generator><language>en</language><lastBuildDate>Sun, 08 Jan 2023 00:00:00 +0000</lastBuildDate><atom:link href="http://lnwatson.co.uk/tags/machine/" rel="self" type="application/rss+xml"/><item><title>Understanding Evolutionary and Genetic Algorithms and Optimisation Problems</title><link>http://lnwatson.co.uk/posts/intro_to_ga/</link><pubDate>Sun, 08 Jan 2023 00:00:00 +0000</pubDate><author>Author</author><guid>http://lnwatson.co.uk/posts/intro_to_ga/</guid><description>Evolutionary Computing A Evolutionary Algorithm (EA) is a subset of Artificial Intelligence (AI), drawing inspiration from natural selection and biological evolution. These algorithms are particularly useful for solving complex optimisation problems (see P, NP, NP-Complete and NP-Hard Problems in Computer Science by Baeldung) where traditional methods may fall short. Often referred to as Genetic Algorithms (GAs), a specific type of evolutionary algorithm, they mimic the process of natural evolution to optimise towards a solution.</description></item></channel></rss>