FCMpy: a python module for constructing and analyzing fuzzy cognitive maps

• Published in: PeerJ. Computer science Vol. 8; p. e1078
• Main Authors: Mkhitaryan, Samvel, Giabbanelli, Philippe, Wozniak, Maciej K, Nápoles, Gonzalo, De Vries, Nanne, Crutzen, Rik
• Format: Journal Article
• Language: English
• Published: San Diego PeerJ, Inc 23.09.2022; PeerJ Inc
• Subjects: Active Hebbian learning; Classification; Cognitive maps; Cognitive models; Digital Libraries; Entropy; FCM; Fuzzy logic; Genetic algorithm; Genetic algorithms; Linguistics; Machine learning; Methods; Modules; Network Science and Online Social Networks; Nonlinear Hebbian learning; Programming Languages; Psychology; Python; Qualitative analysis; Ratings & rankings; Scientific Computing and Simulation; Social Computing; Software; Subject specialists
• ISSN: 2376-5992; 2376-5992
• DOI: 10.7717/peerj-cs.1078

FCMpy is an open-source Python module for building and analyzing Fuzzy Cognitive Maps (FCMs). The module provides tools for end-to-end projects involving FCMs. It is able to derive fuzzy causal weights from qualitative data or simulating the system behavior. Additionally, it includes machine learning algorithms ( e.g ., Nonlinear Hebbian Learning, Active Hebbian Learning, Genetic Algorithms, and Deterministic Learning) to adjust the FCM causal weight matrix and to solve classification problems. Finally, users can easily implement scenario analysis by simulating hypothetical interventions ( i.e ., analyzing what-if scenarios). FCMpy is the first open-source module that contains all the functionalities necessary for FCM oriented projects. This work aims to enable researchers from different areas, such as psychology, cognitive science, or engineering, to easily and efficiently develop and test their FCM models without the need for extensive programming knowledge.