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By Isuru Abeysinghe

Smashwords Edition

Copyright 2012 Isuru Abeysinghe

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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 rules in any country and drive without assistance.)

  • Teaching robotic legs to walk in diverse environments.

All of these problems have the typical applicable nature for genetic algorithms, that is:

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