Realism in fuzzy cognitive maps: incorporating synergies and conditional effects

Fuzzy cognitive maps constitute one of the most dynamically evolving areas of qualitative network representation. The origin of this progress ties mainly in their endogenous advantageous modeling features, which are simplicity, adaptability, capability of approximating abstractive structures, and white box operation. These characteristics prove their significance when managing cognitive processes. Attempting to broaden FCM functionality and applicability, developers should stress on real world problems and situations, sustaining in parallel the aforementioned modeling capabilities. Following this direction, two distinctive elements of typical cognition and decision making systems can be taken into account: the conditional effects and the notion of synergy. This paper captures the importance of these concepts when pursuing the accuracy and effectiveness in causal network representations and introduces mathematical formalisms for incorporating them in the FCM inference engine. Most of all, the benefits of the proposed schemes are in accordance to the practical framework of FCMs - ease of use combined with operational flexibility and wide adaptability