Abstract
We propose a concept generation method based on mutual information smong multiple self-organizing maps. There have been many reports on concept generation in various fields such as linguistics and robotics. In the context of language acquisition, however, they mainly deal with letters, i.e. symbols, in general. Since both the concept and language acquisitions progress in parallel, we notice the importance to investigate concept generation without symbols existing a priori. In this paper, we propose a non-symbol-based method that pays attention to multimodal mutual information.
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Kitahara, K., Hirose, A. (2009). A Concept Generation Method Based on Mutual Information Quantity among Multiple Self-organizing Maps. In: Leung, C.S., Lee, M., Chan, J.H. (eds) Neural Information Processing. ICONIP 2009. Lecture Notes in Computer Science, vol 5864. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10684-2_29
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DOI: https://doi.org/10.1007/978-3-642-10684-2_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10682-8
Online ISBN: 978-3-642-10684-2
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