Abstract
Over the last few years, my research group has begun exploring the issues involved in learning when there are hundreds to thousands of agents. We have been using the idea of organization control as a low overhead way of coordinating the learning of such large agent collectives. In this lecture, the results of this research will be discussed and its relationship to issues in distributed data mining.
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© 2013 Springer-Verlag Berlin Heidelberg
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Lesser, V. (2013). Organizational Control for Data Mining with Large Numbers of Agents. In: Cao, L., Zeng, Y., Symeonidis, A.L., Gorodetsky, V.I., Yu, P.S., Singh, M.P. (eds) Agents and Data Mining Interaction. ADMI 2012. Lecture Notes in Computer Science(), vol 7607. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36288-0_1
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DOI: https://doi.org/10.1007/978-3-642-36288-0_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36287-3
Online ISBN: 978-3-642-36288-0
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