Video games provide an opportunity and challenge for the soft computational intelligence methods like the symbolic games did for good old-fashioned artificial intelligence.'' This article reviews the achievements and future prospects of one particular approach, that of evolving neural networks, or neuroevolution. This approach can be used to construct adaptive characters in existing video games, and it can serve as a foundation for a new genre of games based on machine learning. Evolution can be guided by human knowledge, allowing the designer to control the kinds of solutions that emerge and encouraging behaviors that appear visibly intelligent to the human player. Such techniques may allow building video games that are more engaging and entertaining than current games, and those that can serve as training environments for people. Techniques developed in these games may also be widely applicable in other fields, such as robotics, resource optimization, and intelligent assistants.

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In Gary Y. Yen and David B. Fogel, editors, Computational Intelligence: Principles and Practice, Piscataway, NJ, 2006. IEEE Computational Intelligence Society.

@incollection{miikkulainen:cigames06, title={Computational Intelligence in Games}, author={Risto Miikkulainen and Bobby D. Bryant and Ryan Cornelius and Igor V. Karpov and Kenneth O. Stanley and Chern Han Yong}, booktitle={Computational Intelligence: Principles and Practice}, editor={Gary Y. Yen and David B. Fogel}, address={Piscataway, NJ}, publisher={IEEE Computational Intelligence Society}, url="http://nn.cs.utexas.edu/?miikkulainen:ci06", year={2006} }