In this project i will development different genetic algorithm that allow us to solve some basic problem. Most of the time, the genetic algorithms are used to solve optimization problems.
In this genetic algorithm I use a population of random numbers to find the square root of a given number. The "difficulty" must be given as a float number, this way if the difficulty is 0.01, the algorithm evolve util the best cantidate square root multiplied by himself have a difference to the given number inferior or iqual to 0.01.
In this genetic algorithm I use a series of abstract class that allow the user to use whatever combination of "algorithm" and "creature" that respect the given standard.
- finish Basic_genetic_algorithm
- finish Polymorphic_genetic_algorithm
- increment doxygen documentation to Basic_genetic_algorithm
- increment doxygen documentation to Polymorphic_genetic_algorithm
Use the following command to compile the code on Windows
g++ -o algo *.cpp
For the moment the code doesn't need parameter at the momento of the execution, so we can easily execute the code with the following command line
algo.exe