Genetic Algorithms

By Isuru Abeysinghe

Examines the application of genetic algorithms in order to solve technical problems. Provides a working case study of a robotic spider and how it can learn to walk without being instructed in physics or explicitly programmed to perform that function.

• Language: English
• Publisher: Isuru Abeysinghe
• Release date: Jul 14, 2012
• ISBN: 9781476111032

Isuru Abeysinghe

My life has generally been devoted to the pursuit of technical ambitions, being a graduate of Software Engineering and working for a financial services company as a software developer. However, I have many interests in humanities - history and politics mainly - providing fuel for my creative outlet of writing. I try and integrate equal parts of bleak and almost brutal analysis together with sardonic comedy to produce works that I hope will offer new perspectives and reflect actual social issues in the real world.

Book preview

INTRODUCTION

Genetic algorithms are a class of algorithms that harness the power of evolutionary mechanics in order to solve a generic class of problem. When a developer is faced with a situation whereby the problem is not clearly defined, or the nature of the problem has the propensity to change over time, the practicality of applying traditional structured logic to engineer a solution is soon eroded. For this reason a programmer needs to develop a system that in itself can learn and adapt when the nature of the problem being solved is ever-changing.

The following are examples of problems that can and have been solved using genetic algorithms:

Handwriting recognition.

Automated vehicles (cars that can follow the road

Reviews for Genetic Algorithms

[Murray Steele · Rating: 4 out of 5 stars]

A really nice introduction to Genetic Algorithms! Real world examples help you understand the basic concepts of Genetic Algorithms.