Multi-agent neural business control system

  • Authors:

  • M. Lourdes Borrajo;Juan M. Corchado;Emilio S. Corchado;María A. Pellicer;Javier Bajo

  • Affiliations:

  • Departamento de Informática, University of Vigo, Escuela Superior de Ingeniería Informática, Edificio Politécnico, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain;Departamento de Informática y Automática, University of Salamanca, Plaza de la Merced s/n, 37008 Salamanca, Spain;Departamento de Ingeniería Civil, University of Burgos, Esc. Politécnica Superior, Edificio C, C/ Francisco de Vitoria, 09006 Burgos, Spain;Departamento de Ingeniería Civil, University of Burgos, Esc. Politécnica Superior, Edificio C, C/ Francisco de Vitoria, 09006 Burgos, Spain;Departamento de Informática y Automática, University of Salamanca, Plaza de la Merced s/n, 37008 Salamanca, Spain

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2010

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Abstract

Small to medium sized companies require a business control mechanism in order to monitor their modus operandi and analyse whether they are achieving their goals. A tool for the decision support process was developed based on a multi-agent system that incorporates a case-based reasoning system and automates the business control process. The case-based reasoning system automates the organization of cases and the retrieval stage by means of a Maximum Likelihood Hebbian Learning-based method, an extension of the Principal Component Analysis which groups similar cases by automatically identifying clusters in a data set in an unsupervised mode. The multi-agent system was tested with 22 small and medium sized companies in the textile sector located in the northwest of Spain during 29 months, and the results obtained have been very satisfactory.