Abstract
In this paper we explain how we applied genetic programming to behavior-based team coordination in the RoboCup Soccer Server domain. Genetic programming is a promising new method for automatically generating functions and algorithms through natural selection. In contrast to other learning methods, genetic programming's automatic programming makes it a natural approach for developing algorithmic robot behaviors. The RoboCup Soccer Server was a very challenging domain for genetic programming, but we were pleased with the results. At the end, genetic programming had produced teams of soccer softbots which had learned to cooperate to play a good game of simulator soccer.
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© 1998 Springer-Verlag Berlin Heidelberg
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Luke, S., Hohn, C., Farris, J., Jackson, G., Hendler, J. (1998). Co-evolving Soccer Softbot team coordination with genetic programming. In: Kitano, H. (eds) RoboCup-97: Robot Soccer World Cup I. RoboCup 1997. Lecture Notes in Computer Science, vol 1395. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64473-3_76
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DOI: https://doi.org/10.1007/3-540-64473-3_76
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