Game implementation: An interesting strategy to teach genetic algorithms

Abstract

This chapter captures the experience acquired in the development of applications based on genetic algorithms. Specifically, we implemented two games that show an intelligent behaviour by executing genetic algorithms. They both show good results as well, because they are able to play successfully against human players. Moreover, the genetic algorithms parameters are user-configurable; so, the user can modify the number of individuals per generation, the number of generations, the mutation probability of each individual, the crossover function to generate new individuals, etc. This is very useful because the applications developed also generate statistical reports that show how individuals evolve in each generation. Therefore, the user can understand the evolution and analyze results easily. With this approach the user can test several combinations of parameters to study and compare them by analyzing their behaviour, speed, etc. In conclusion, as we are going to see in this chapter, the implementation of these two genetic games is an interesting strategy in order to teach and learn genetic algorithms. © 2007 Springer.