TierOptimizer | Genetic algorithm to find the best teams in a pokemon tier

TierOptimizer is a Python library. TierOptimizer has no bugs, it has no vulnerabilities and it has low support. However TierOptimizer build file is not available. You can download it from GitHub.

More than an utility, this is a proof of concept. It's a python script that receives a tier listing and through a genetic algorythm makes a ranking of the best sets of pokemons in the tier. For low complexity fitting (only attending to type weakness, type diversity and overall stats) it's easy as it gets. Genes of 6 elements, one for each pokemon then fit the population and make a ranking. As the fitting function can be altered and parametrized this can reach high levels of complexity if I decide to start taking into account type coverage and role diversity, maybe even strategies, but for this I may have to include some deeper level of knowledge through something like answer set programming. ##Setup You need python 3.4 or greater installed and in the system's PATH. Other than that you also need the requests module. To get it just: pip install requests and done. The GUI version of the program runs on Qt so if you also want to use it, you need 'pySide', to get it use: pip install pyside. ##Running Right now there aren't any binaries or makefile, just a couple of python of scripts which you can run. There aren't any command line parameters yet, but there's a configuration file lib/Const.py which you can edit to change the behaviour of the script and the console output. The names of the constants are pretty much self-explanatory.