Genetic Algorithms has been an interesting topic to me since the early of 2004. It takes the idea of genetic operations and applies in computation process. The applications of Genetic Algorithms can be in a very broad area, not necessary in computer science. For example, the picture above is generated using Human-Based Crossover operation.

In June of 2004, I participated in Genetic Algorithms in GECCO ( The Genetic and Evolutionary Computation Conference) in Seattle, USA. Here is the introduction of my paper:

Interactive one-max problem allows to compare the performance of Interactive and Human-Based Genetic Algorithms

This paper suggests an experiment to compare the performance of Interactive Genetic Algorithms (IGA) and Human-Based Genetic Algorithms (HBGA).

IGA and HBGA are two Genetic Algorithms that use human interaction. IGA uses human evaluation. HBGA, in addition, brings human innovation into computational process. Now we have a question. Can HBGA be applied to IGA domain? And will it work better?

This is not a simple question. First, Human Based innovation is better, however computational innovation, such as crossover and mutation, is a lot faster. We design an experiment to answer. We measure how long does it take to achieve the same goal using IGA and HBGA.

If you want to learn more about this project, you can go to the information website of this project by clicking the following link:

http://www.derrickcheng.com/Project/HBGA

If you have any question, please send me an email at:
research@derrickcheng.com