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Does Complex Learning Require Complex Connectivity?

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4140))

Abstract

Small World and Scale Free network properties characterize many real complex phenomena. We assume that low level connectivity with such topological properties, e.g., anatomical or functional connectivity in brains, is compulsory to achieve high level cognitive functionality, as language. The study of these network properties provides tools to approach different issues in behavior based Artificial Intelligence (AI) that usually have been ill defined, e.g., complexity and autonomy. In this paper, we propose a model in which situated agents evolve knowledge networks holding both Small World and Scale Free properties. Experimental results in the context of Pragmatic Games, elucidate some required conditions to obtain the expected network properties when performing complex learning.

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© 2006 Springer-Verlag Berlin Heidelberg

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de la Mora-Basáñez, C.R., Guerra-Hernández, A., Steels, L. (2006). Does Complex Learning Require Complex Connectivity?. In: Sichman, J.S., Coelho, H., Rezende, S.O. (eds) Advances in Artificial Intelligence - IBERAMIA-SBIA 2006. IBERAMIA SBIA 2006 2006. Lecture Notes in Computer Science(), vol 4140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11874850_61

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  • DOI: https://doi.org/10.1007/11874850_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45462-5

  • Online ISBN: 978-3-540-45464-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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