Abstract
We formalize a behavior-based learning architecture for an autonomous agent. The IR oven tuning problem is introduced and is investigated as a real industrial application of this architecture. The algorithm we developed was shown to be very robust and was tested through simulation of different intelligent machines, including Genghis [9]. The distinguishing feature of this learning algorithm is that the convergent property can be preserved. This is crucial for achieving the final goals of tuning.
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© 1993 Springer-Verlag Berlin Heidelberg
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Chou, R., Liu, P., Vallino, J., Chiu, M.Y. (1993). Behavior-based learning to control IR oven heating: Preliminary investigations. In: Hanson, S.J., Remmele, W., Rivest, R.L. (eds) Machine Learning: From Theory to Applications. Lecture Notes in Computer Science, vol 661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56483-7_33
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DOI: https://doi.org/10.1007/3-540-56483-7_33
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