شماره ركورد كنفرانس :
3541
عنوان مقاله :
A Self Organizing Architecture for Adjusting Level of Difficulty in Games
Author/Authors :
Adeleh Ebrahimi Artificial Intelligence Student - Islamic Azad University Mashhad Branch, Mashhad, Iran , Mohammad-R Akbarzadeh-T Center of Excellence on Soft Computing and Intelligent Information Processing - Ferdowsi University of Mashhad, Iran
كليدواژه :
NPC , Co-Operative Coevolution , Interactive Evolutionary Algorithm , Self Organizng System
عنوان كنفرانس :
همايش بين المللي علوم كامپيوتر و مهندسي نرم افزار
چكيده لاتين :
Games are played by players with different strategies; a game could be frustrating or disappointing, if level of difficulty does not match player’s skills. In this paper we use Non-Player Characters (NPCs) to build a Self-Organizing System (SOS) for adjusting level of difficulty in games. For this purpose we apply Artificial Neural Network and Interactive Evolutionary Algo-rithms, and concentrate on player’s hidden responses. Results show that this SOS can adapt itself with different level of skills.
