Abstract
This paper defends the employment of Evolutive Algorithms (EAs) in action games by showing their virtues for both offline and online opponent controlling. The paper proposes (and also compares) several EAs applied offline in the solving of a classical path finding problem and used to provide intelligence to autonomous agents (e.g., the opponents) in an action computer game. The paper also presents an EA that has been successfully employed in real time (i.e., online) in an action game in which a player controls a military vehicle in a hostile enemy region.
This work has been partially supported by projects TIC2001-2705-C03-02, and TIC2002-04498-C05-02 funded by both the Spanish Ministry of Science and Technology and FEDER.
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Fernández, A.J., González, J.J. (2005). Action Games: Evolutive Experiences. In: Reusch, B. (eds) Computational Intelligence, Theory and Applications. Advances in Soft Computing, vol 33. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31182-3_45
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DOI: https://doi.org/10.1007/3-540-31182-3_45
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