1. A variant of the SOM algorithm and its interpretation in the viewpoint of social influence and learning.
- Author
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Su, Mu-Chun and Zhao, Yu-Xiang
- Subjects
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SELF-organizing maps , *ALGORITHMS , *MATHEMATICAL models , *MATHEMATICAL optimization , *SOCIAL influence , *SOCIAL learning , *SIMULATION methods & models - Abstract
The conventional self-organizing feature map (SOM) algorithm is usually interpreted as a computational model, which can capture main features of computational maps in the brain. In this paper, we present a variant of the SOM algorithm called the SOM-based optimization (SOMO) algorithm. The development of the SOMO algorithm was motivated by exploring the possibility of applying the SOM algorithm in continuous optimization problems. Through the self-organizing process, good solutions to an optimization problem can be simultaneously explored and exploited by the SOMO algorithm. In our opinion, the SOMO algorithm not only can be regarded as a biologically inspired computational model but also may be regarded as a new approach to a model of social influence and social learning. Several simulations are used to illustrate the effectiveness of the proposed optimization algorithm. [ABSTRACT FROM AUTHOR]
- Published
- 2009
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