Dynamic difficulty adjustment in games by using an interactive self-organizing architecture

Author

Ebrahimi, Amir ; Akbarzadeh-T, Mohammad-R

Author_Institution

Dept. of Comput. Eng., Islamic Azad Univ., Mashhad, Iran

fYear

2014

fDate

4-6 Feb. 2014

Firstpage

1

Lastpage

6

Abstract

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-organizing system (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.

Keywords

computer games; evolutionary computation; neural nets; NPC; SOS; artificial neural network; dynamic difficulty adjustment; games; interactive evolutionary algorithms; interactive self-organizing architecture; nonplayer characters; player hidden response; self-organizing system; Biological cells; Biological neural networks; Computer architecture; Evolutionary computation; Games; Microprocessors; CoOperative Coevolution; Interactive Evolutionary Algorithm; Non-Player Character; Self Organizng System;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems (ICIS), 2014 Iranian Conference on

Conference_Location

Bam

Print_ISBN

978-1-4799-3350-1

Type

conf

DOI

10.1109/IranianCIS.2014.6802557

Filename

6802557