Qualitative Knowledge A cquisition Using
Fuzzy Logic and System Dynamics
Rafael E. Bourguet' and Rogelio Soto”
' Department of Industrial and Systems Engineering, ITESM Campus Monterrey
Av. Garza Sada 2501 Sur, 64849 Monterrey N.L., Mexico
Telephone: (+52-8) 328-4114, Facsimile: (+52-8) 328-4236
rbourgue@ campus.mty.itesm.mx
> Center for Artificial Intelligence, ITESM Campus Monterrey
Av. Garza Sada 2501 Sur, 64849 Monterrey N.L., Mexico
Telephone: (+52-8) 328-4197, Facsimile: (+52-8) 328-4189
r.soto@ ieee.org
Abstract
Research results are exposed on policy representation based on Fuzzy Logic and System
Dynamics. It is pretended to find a method for representing qualitative knowledge on dynamics
of complex systems. Qualitative knowledge is considered the softest part in human organizations
and the hardest part to manage. The set of fuzzy policies represented in the model pretends to
carry out a hotel business administration. This research sustains an effort to integrate some of
the benefits that Fuzzy Logic has brought to the area of control systems by representing
qualitative knowledge of human operators to the discipline of System Dynamics by representing
policies of decision-makers. The set of policies and the hotel models have been implemented
using the “ithing” software. Results show the useful of the method in the learning process of
managers when the attention is explicitly paid on the rules that transforms information into
action.
Key words: policy representation, fuzzy logic, system dynamics, qualitative knowledge.
