Title: A MULTI-AGENT MODEL OF KNOWLEDGE SOCIETY FOR BUSINESS AND MANAGEMENT SYSTEM: MODELING DISTRIBUTED AGENCY USING DATA MINING AND NEURO-FUZZY SYSTEM

Issue Number: Vol. 1, No. 2
Year of Publication: 2011
Page Numbers: 479-488
Authors: Eduardo Ahumada-Tello, Manuel Castanon-Puga, Juan Ramon Castro, Eugenio D.Suarez, Bogart Yail Marquez, Carelia Gaxiola-Pacheco, Dora Luz Flores
Journal Name: International Journal of Digital Information and Wireless Communications (IJDIWC)
- Hong Kong

Abstract:


This work is motivated by the need for a model that addresses the study of Knowledge Society in specific environments such as Business and Management, where several situations are very difficult to be analyze in conventional ways and therefore is insufficient in describing the complications of represent a realistic social phenomena and their social actors. We use Distributed Agency methodology that requires the use of all available computational techniques and interdisciplinary theories as an approach to describe the interactions between agents in the development of social phenomena. We also use Data Mining and Neuro-Fuzzy System as part of the methodology to discover and assign rules on agents that represent real-world companies and employees. The case study is based on several IT companies in the region of Baja California México and in the policies they implement to achieve greater competitiveness based on knowledge.