Using Fuzzy Cognitive Maps to Arouse Learning Processes in Cities

  • Sara D’OnofrioEmail author
  • Elpiniki Papageorgiou
  • Edy Portmann
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 176)


Processing information in a city is simultaneously a primary task and a pivotal challenge. Urban data are usually expressed in natural language and thus imprecise but can contain relevant information that should be processed to advance the city. Fuzzy cognitive maps (FCMs) can be used to model interconnected and imprecise urban data and are therefore suitable to both address this challenge and to fulfil the primary task. Cognitive cities are based on connectivism, which assumes that knowledge is built through the experiences and perceptions of different people. Hence, the design of a cognitive learning process in a city is crucial. In this article, the current state-of-the-art research in the field of FCMs and FCMs combined with learning algorithms is presented based on an extensive literature review and grounded theory. In total, 59 research papers were gathered and analyzed. The results show that the application of FCMs already facilitates the acquisition and representation of urban data and, thus, helps to make a city smarter. However, using FCMs combined with learning algorithms optimizes this smartness and helps to foster the development of cognitive cities.


Cognitive city Connectivism Fuzzy logic Fuzzy cognitive maps Learning algorithms Smart city 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sara D’Onofrio
    • 1
    Email author
  • Elpiniki Papageorgiou
    • 2
  • Edy Portmann
    • 1
  1. 1.Human-IST Institute, University of FribourgFribourgSwitzerland
  2. 2.Department of Electrical EngineeringUniversity of Applied Sciences (TEI) of ThessalyLarisaGreece

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