Abstract
Through robotic soccer issue, we focus on “perception” and “situation and behavior” problem among RoboCup physical agent challenges [1]. So far, we have implemented some behaviors for playing soccer by combining four primitve processes (motor control, camera control, vision, and behavior generation processes)[2]. Such behaviors were not sophisticated very much because they were fully implemented by the human programmer. In order to improve the performance of such behaviors, a kind of learning algorithm would be useful during off/on-line skill development phase.
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References
M. Asada, Y. Kuniyoshi, A. Drogoul, and et. al. “The RoboCup Physical Agent Challenge:Phase I(Draft)”. In Proc. of The First International Workshop on RoboCup, pages 51–56, 1997.
T. Nakamura, K. Terada, and et al. “Development of a Cheap On-board Vision Mobile Robot for Robotic Soccer Research”. In Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems 1998 (IROS’ 98), pages 431–436, 1998.
T. Nakamura and T. Ogasawara. “On-Line Visual Learning Method for Color Image Segmentation and Object Tracking”. In Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems 1999 (to appear), 1999.
Hema R. Madala and Alexy G. Ivakhnenko. Inductive Learning Algorithm for Complex System Modeling. CRC Press, 1993.
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© 2000 Springer-Verlag Berlin Heidelberg
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Nakamura, T., Terada, K., Takeda, H., Ebina, A., Fujiwara, H. (2000). The RoboCup-NAIST. In: Veloso, M., Pagello, E., Kitano, H. (eds) RoboCup-99: Robot Soccer World Cup III. RoboCup 1999. Lecture Notes in Computer Science(), vol 1856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45327-X_92
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DOI: https://doi.org/10.1007/3-540-45327-X_92
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