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Proceedings Paper

Self-organization by fuzzy clustering
Author(s): Gerardo Beni; Susan Hackwood; Xiaomin Liu
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Paper Abstract

New types of robot systems have recently been suggested based on the idea of distributed, collective intelligence analogous to biological systems. In this paper we investigate the relationship between fuzzy clustering (FC) and problems of self-organization in such systems, referred collectively as distributed robotic systems (DRS). The particular problem of self- organization in DRS prompts a reconsideration of the available FC techniques. Recent advances in FC are reviewed with the intent of adapting them to thy DRS problem. A `minimally biased' clustering algorithm producing a validity ranked hierarchy of partitions is applied to the self-organizing evolution of DRS. Two cases are considered: a bottom up self organization into increasing larger groups and a top down dispersion of a group to optimally cover a sensory field.

Paper Details

Date Published: 1 July 1992
PDF: 11 pages
Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140125
Show Author Affiliations
Gerardo Beni, Univ. of California/Riverside (United States)
Susan Hackwood, Univ. of California/Riverside (United States)
Xiaomin Liu, Univ. of California/Riverside (United States)

Published in SPIE Proceedings Vol. 1710:
Science of Artificial Neural Networks
Dennis W. Ruck, Editor(s)

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