TY - JOUR
T1 - FCM Expert: Software Tool for Scenario Analysis and Pattern Classification Based on Fuzzy Cognitive Maps
T2 - International Journal on Artificial Intelligence Tools
AU - Nápoles, Gonzalo
AU - Espinosa, Maikel Leon
AU - Grau, Isel
AU - Vanhoof, Koen
N1 - doi: 10.1142/S0218213018600102
PY - 2018
Y1 - 2018
N2 - Fuzzy Cognitive Maps (FCMs) have become a suitable and proven knowledge-based methodology for systems modeling and simulation. This technique is especially attractive when modeling systems characterized by ambiguity, and/or non-trivial causalities among its variables. The rich literature that is found related to FCMs reports very clearly many successful studies solved through the use of FCMs; however, when it comes to software implementations, where domain experts can design FCM-based systems, run simulations or perform more advanced experiments, not much is found or documented. The few existing implementations are not proficient in providing options for experimentation. Therefore, we believe that a gap exists, specifically between the theoretical advances and the development of accurate, transparent and sound FCM-based systems; and we advocate for the creation of more complete and exible software products. The goal of this paper is to introduce ?FCM Expert?, a software tool for fuzzy cognitive modeling, where we focus on scenario analysis and pattern classification. The main features of FCM Expert rely on Machine Learning algorithms to compute the parameters that might define a model, optimize its network topology and improve the system convergence without losing information. Also, FCM Expert allows performing WHAT-IF simulations and studying the system behavior through a friendly, intuitive and easy-to-use graphical user interface.
AB - Fuzzy Cognitive Maps (FCMs) have become a suitable and proven knowledge-based methodology for systems modeling and simulation. This technique is especially attractive when modeling systems characterized by ambiguity, and/or non-trivial causalities among its variables. The rich literature that is found related to FCMs reports very clearly many successful studies solved through the use of FCMs; however, when it comes to software implementations, where domain experts can design FCM-based systems, run simulations or perform more advanced experiments, not much is found or documented. The few existing implementations are not proficient in providing options for experimentation. Therefore, we believe that a gap exists, specifically between the theoretical advances and the development of accurate, transparent and sound FCM-based systems; and we advocate for the creation of more complete and exible software products. The goal of this paper is to introduce ?FCM Expert?, a software tool for fuzzy cognitive modeling, where we focus on scenario analysis and pattern classification. The main features of FCM Expert rely on Machine Learning algorithms to compute the parameters that might define a model, optimize its network topology and improve the system convergence without losing information. Also, FCM Expert allows performing WHAT-IF simulations and studying the system behavior through a friendly, intuitive and easy-to-use graphical user interface.
U2 - 10.1142/S0218213018600102
DO - 10.1142/S0218213018600102
M3 - Article
SN - 0218-2130
VL - 27
JO - INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS
JF - INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS
IS - 07
ER -