Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Static and dynamic difficulty level design for edutainment game using artificial neural networks
Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment
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In this paper, we examine the use of Artificial Neural Networks (ANNs) for designing an adaptive computer game system. This adaptive computer game system will enhance the game play experience of a player by adopting the concept of player centred game design. In this paper, the ANN is used to handle the dynamic difficulty level adjustment for each individual player. The difficulty level for each player can be customised using the proposed method, thus allowing game player to have a more personalised game play experience.