In this paper, a new approach to automatically generating game strategies based on the game conditions is presented. A game policy is defined and applied by a human coach who establishes the attitude of the team for defending or attacking. A simple neural net model is applied using current and previous game experience to classify the game's parameters so that the new game conditions can be determined so that a robotic team can modify its strategy on the fly. Results of the implemented model for a robotic soccer team are discussed. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Atkinson, J., & Rojas, D. (2008). Generating dynamic formation strategies based on human experience and game conditions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5001 LNAI, pp. 159–170). https://doi.org/10.1007/978-3-540-68847-1_14
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