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

Samvel Mkhitaryan1, Philippe Giabbanelli2, Maciej K Wozniak3

  • 1Health Promotion, Maastricht University, Maastricht, Netherlands.

Peerj. Computer Science
|October 20, 2022
PubMed
Summary
This summary is machine-generated.

FCMpy is a new Python module for Fuzzy Cognitive Maps (FCMs), offering tools for analysis, simulation, and machine learning. It empowers researchers to build and test FCM models efficiently without extensive programming skills.

Keywords:
Active Hebbian learningFCMGenetic algorithmNonlinear Hebbian learningPython

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Area of Science:

  • Computational Intelligence
  • Cognitive Science
  • Systems Engineering

Background:

  • Fuzzy Cognitive Maps (FCMs) are powerful tools for modeling complex systems.
  • Existing FCM tools often lack comprehensive functionality or require advanced programming expertise.
  • There is a need for an accessible, integrated platform for FCM development and analysis.

Purpose of the Study:

  • Introduce FCMpy, an open-source Python module for end-to-end Fuzzy Cognitive Map projects.
  • Provide tools for deriving fuzzy causal weights, simulating system behavior, and adjusting FCM parameters.
  • Facilitate scenario analysis and classification tasks using integrated machine learning algorithms.

Main Methods:

  • FCMpy offers functionalities for qualitative data analysis to derive fuzzy causal weights.
  • The module incorporates machine learning algorithms such as Nonlinear Hebbian Learning, Active Hebbian Learning, Genetic Algorithms, and Deterministic Learning.
  • Users can perform "what-if" scenario analyses through simulation of hypothetical interventions.

Main Results:

  • FCMpy is the first open-source module providing a complete suite of tools for FCM projects.
  • The module enables efficient development and testing of FCM models across various disciplines.
  • It lowers the barrier to entry for researchers lacking extensive programming knowledge.

Conclusions:

  • FCMpy democratizes the use of Fuzzy Cognitive Maps in research.
  • The module supports diverse applications in psychology, cognitive science, and engineering.
  • It facilitates robust FCM model development, analysis, and application.