Cyclic reproduction scheme in genetic algorithm for evolutionary game

Authors:
Sang-Won Um;Suk-Han Lee;Tae-Yong Kim;Jong-Soo Choi
Affiliations:
Department of Image Engineering Graduate School of Advanced, Imaging Science, Multi-media, and Film, Chung-Ang University, Seoul, South Korea;Department of Image Engineering Graduate School of Advanced, Imaging Science, Multi-media, and Film, Chung-Ang University, Seoul, South Korea;Department of Image Engineering Graduate School of Advanced, Imaging Science, Multi-media, and Film, Chung-Ang University, Seoul, South Korea;Department of Image Engineering Graduate School of Advanced, Imaging Science, Multi-media, and Film, Chung-Ang University, Seoul, South Korea
Venue:
Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment
Year:
2006

Citing 2
Cited 0

Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
The Games Computers (and People) Play

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence

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Abstract

This paper describes how Genetic Algorithm can be used to control the level of difficulty in a game based on a user's skill. An algorithm is proposed to control the difficulty of a game according to user's propensity in our previous work [1], [2]. But the searching spaces are very narrow and convergence of chromosomes is also slow because the game progresses step-by-step and chromosomes are evaluated simultaneously while playing the game. Thus, a method is presented to expand the searching spaces and converge quickly on the Genetic Algorithm in the domain of sequential progress.