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.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
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
eBook Packages: Computer ScienceComputer Science (R0)