Most people think of evolution as a long running process that spans over millions of years. But we can use evolution as a general and fast optimisation process that generates good solutions very efficiently for a wide range of problems. This talk will present the elements of evolution and the main steps of implementation as a simulated process. One example will be the evolution or “breeding” of a control program of a simulated robot that navigates in a specific environment.
Required audience experience
Basic programming skills in any programming language
Objective of the talk
The talk will show the main elements of a simulated evolution as a general optimisation process that is suitable to create “innovative” solutions for problems that are hard to solve.