Genetic Algorithm for optimizing Game using users' adaptation

This paper describes how we use Genetic Algorithm to modify the level of difficulty in a game based on a user. We use Factor of Difficulty Control (next FDC) as Gene and Factor of Users' Adaptation to a game (next FUA) as Fitness. Then we implemented a game that matches gamers' adaptation in our previous research. Games are composed of occurring sequential events and playing time is limited. In a game, because group searching is impossible, we must find the optimum as quickly as possible, like Genetic Algorithm finding the optimum as a Generation search. So we propose Cyclic Search Algorithm (next CSA) to create Genes quickly and evaluate the Fitness of Genes faster. By using CSA, we compose a game with more appropriate Genes for a gamer within a playing-time, therefore reaching an improved result than our previous research.