Capturing player enjoyment in computer games

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Abstract

The current state-of-the-art in intelligent game design using Artificial Intelligence (AI) techniques is mainly focused on generating human-like and intelligent characters. Even though complex opponent behaviors emerge through various machine learning techniques, there is generally no further analysis of whether these behaviors contribute to the satisfaction of the player. The implicit hypothesis motivating this research is that intelligent opponent behaviors enable the player to gain more satisfaction from the game. This hypothesis may well be true; however, since no notion of entertainment or enjoyment is explicitly defined, there is therefore no evidence that a specific opponent behavior generates enjoyable games. © 2007 Springer-Verlag Berlin Heidelberg.

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APA

Yannakakis, G. N., & Hallam, J. (2007). Capturing player enjoyment in computer games. Studies in Computational Intelligence, 71, 175–201. https://doi.org/10.1007/978-3-540-72705-7_8

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