Dynamic Difficulty Adjustment in Games by Using an Interactive Self-Organizing Architecture

If difficulty level of a game does not match player’s skills, the game could be frustrating or disappointing. In this paper we propose a self-organizingsystem (SOS) to adjust difficulty level of games. For this purpose, we use Artificial Neural Network and Interactive Evolutionary Algorithms to evolve Non-Player Characters (NPCs), and focus on player’s hidden responses to determine fitness of the system. Results show that the proposed interactive SOS can adapt itself with different level of skills

کلیدواژه ها:

Self Organizng System ، Interactive Evolutionary Algorithm ، CoOperative Coevolution ، Non-Player Character