Everything is true to a certain degree. FMsquare uses the idea of graded truth to help leverage collective and individual intelligence for a human-centered digital transformation.
The International Foundation Fuzzy Modeling Methods (FMsquare) promotes fuzzy logic infinite truth values for business, governmental and societal challenges. With a holistic approach, fuzzy logic combines biological and artificial intelligence and is inclusive, not exclusive. This mindset supports life in harmony with each other and with nature.
Fuzzy logic can handle vague semantic information. It results in algorithms and systems that support human reasoning, leveraging interactive, understandable, and evident digital tools that complement human intelligence instead of replacing it. We thereby help empower individuals in a humanistic tradition, emphasizing the value of human beings in a digital and globalized world.
The International Foundation FMsquare has a charitable character and does not pursue any profit-making purpose. The donor reserves are based on Art. 86a ZGB (Swiss law) and under consideration the statutory conditions expressly the right to change the purpose of the foundation.
Jose M. Alonso Moral is with the Centro Singular de Investigación en Tecnoloxías Intelixentes (CiTIUS) at the University de Santiago de Compostela. Dr. Alonso holds a Master’s and Ph.D. degree in Telecommunication Engineering from the Technical University of Madrid. He is a board member of several the ACL Special Interest Group on Natural Language Generation, the European Society for Fuzzy Logic and Technology (EUSFLAT), Chair of the Task Force on Explainable Fuzzy Systems in the IEEE Computational Intelligence Society (IEEE-CIS), Associate Editor of the IEEE Computational Intelligence Magazine, member of the Editorial Board of the International Journal of Computational Intelligence Systems and member of the IEEE-CIS Task Forces on Explainable Machine Learning and Fuzzy Systems Software.
Sara D’Onofrio is IT Business Partner Manager of one of the largest retail companies in Switzerland, author and editor of the journal HMD Praxis der Wirtschaftsinformatik at Springer, guest lecturer at universities, and member of the FMsquare Foundation. She studied business administration and information systems and holds a Ph.D. in computer science. Her research and consulting interests include innovation, smart cities, and cognitive computing.
Miroslav Hudec is an associate professor at the VSB – Technical University of Ostrava and at the University of Economics in Bratislava, as well as visiting professor at the University of Belgrade. He received a Master’s degree in information sciences and a Ph.D. degree in operations research from the University of Belgrade. He has a Habilitation in System engineering and informatics from the VSB – Technical University of Ostrava. His work is mainly focused on fuzzy logic, knowledge discovery, aggregation functions, and business intelligence.
Michael Kaufmann is professor at the Lucerne University of Applied Sciences and Arts, School of Information Technology. He is coordinator of the research team Data Intelligence, examining methods and technologies for intelligent data management. Michael Kaufmann studied computer science, law and psychology at the University of Fribourg. With extra-occupational doctoral studies, he received his Ph.D. in Computer science on the topic of inductive fuzzy classification in marketing analytics. He worked at PostFinance as a data warehouse poweruser in corporate development; Later on, at Mobiliar Insurance as a data architect in the enterprise architecture unit; and as a business analyst at FIVE Informatik AG. Since 2014 he works at the Lucerne University of Applied Sciences in teaching and research.
Andreas Meier is an emeritus professor of data science at the faculty of economics and social sciences of the University of Fribourg. After music studies in Vienna, he graduated in mathematics at the Federal Institute of Technology (ETH) in Zurich and got a Ph.D. and habilitation degree at the institute for computer science. He conducted research at the IBM Research Lab in California, was a systems engineer at IBM Switzerland, a director at a swiss bank corporation, and a member of the executive board of the CSS insurance company. His research areas included eBusiness, eGovernment, and information management.
Prof. Vil ́em Nov ́ak, Ph.D., DSc. is the founder and former director of the Institute for Research and Applications of Fuzzy Modeling of the University of Ostrava, Czech Republic. The institute (established in 1996) is one of the world-renowned scientific workplaces that significantly contributed to the theory and applications of fuzzy modeling. He is the author or co-author of 5 scientific monographs, two edited mono- graphs, and over 300 scientific papers with over 7000 citations. He was awarded in the International Conference FLINS 2010 in China and obtained the title “IFSA fellow” in 2017 for his scientific achievements. He is currently the vice- president of IFSA.
Elpiniki I. Papageorgiou is an associate professor at the Energy Systems Department and director of the MSc program in “Energy and Automation Systems” at the University of Thessaly, Larissa. She holds an MSc degree in Medical Physics from the same University and a Ph.D. in Computer Science from the University of Patras. She has been working for over 17 years as a principal investigator and senior researcher in several European and Greek research projects. She is IEEE Senior Member, IEEE in Women in Computational Intelligence, and member in IEEE CIS. Her research interests include intelligent systems, fuzzy cognitive maps, soft computing methods, decision support systems, cognitive systems, data mining, and machine learning. Her main research specialization is the development of novel algorithms and fuzzy models for intelligent decision support systems focused on Fuzzy Cognitive Maps.
Witold Pedrycz is Professor and Canada Research Chair in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. In 2012 he was elected a Fellow of the Royal Society of Canada and in 2009 he was elected a foreign member of the Polish Academy of Sciences. In 2007 he received a prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society. Besides he is a recipient of the IEEE Canada Computer Engineering Medal, a Cajastur Prize for Soft Computing from the European Centre for Soft Computing, a Killam Prize, a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society, and the 2019 Meritorious Service Award from the IEEE Systems Man and Cybernetics Society. His main research directions involve Computational Intelligence, fuzzy modeling, and Granular Computing, knowledge discovery and data science, pattern recognition, data science, knowledge-based neural networks among others.
Edy Portmann is Swiss Post Professor of Informatics at the Human-IST Institute of the University of Fribourg and member of the board of the Swiss Informatics Society. After an apprenticeship as an electrician, he studied information systems, business as well as economics and, later, got a doctorate in computer science. Among others, he worked for Swisscom, PwC, and EY. In addition, Edy Portmann was also a researcher at the universities of Singapore, Berkeley, and Bern. His transdisciplinary research focuses on cognitive computing and its application to the network industry.
Rudolf Seising is a member of the Research Institute for the History of Science and Technology at the Deutsches Museum in Munich and a College Lecturer at the Faculty of History and Arts at the Ludwig–Maximilians–University (LMU) Munich. He studied Mathematics, Physics, and Philosophy at the Ruhr-University Bochum and obtained a PhD in Philosophy of Science and a German Habilitation in History of Science from LMU. Among others, Dr Seising was a researcher at the European Centre for Soft Computing and the University of California, Berkeley, as well as a Professor for the History of Science at the Friedrich-Schiller-University Jena (Germany) and the LMU. Dr. Seising is Chairman of the IFSA Special Interest Group “History”, the EUSFLAT Working Group “Philosophical Foundations” and the IEEE Computational Intelligence Society (CIS) History Committee.
Martin Štěpnička is Associate Professor of Applied Mathematics at the University of Ostrava, director of the Centre of Excellence IT4Innovations-Institute for Research and Applications of Fuzzy Modeling at the University of Ostrava, and president of the European Society for Fuzzy Logic and Technologies (EUSFLAT). After studying Applied Mathematics at the University of Ostrava, he obtained his Ph.D. in the same field in 2012. His research interests focus on fuzzy modeling, especially on fuzzy relational structures and approximate reasoning (inference systems).
Marco Elio Tabacchi, Ph.D., is a fuzzy logician and a prize-winning printmaker. He is the Scientific Director at Instituto Nazionale di Ricerche Demopolis, where fuzzy logic is used to improve society’s understanding. Dr. Tabacchi is also a researcher at Dipartimento di Fisica e Chimica “Emilio Segré” – Università Degli Studi di Palermo, developing fuzzy Clinical Diagnosis Support Systems.
Luis Terán is a senior researcher in cognitive computing at the Human-IST Institute, University of Fribourg, Switzerland, and external lecturer at the Lucerne University of Applied Sciences and Arts. Dr. Teran holds an M.Sc. degree in communication systems from the Federal Institute of Technology, Lausanne (EPFL), as well as a Ph.D. and a habilitation in computer science from the University of Fribourg. He was a researcher at the Universities of Bern and Zurich, and a Full Professor at Universidad de Las Fuerzas Armadas (ESPE), Ecuador. His research interests include Data Science, digitalization, information systems, machine learning, explainable artificial intelligence, recommender systems, human-centered computing, e-business, e-government, e-participation, e-democracy, e-health, and fuzzy classification.
Gwen Wilke is a lecturer of Data Analytics and Mathematics at the University of Applied Sciences Northwestern Switzerland (FHNW). She studied mathematics at the University of Vienna and the Technical University of Berlin, and received her Ph.D. from the Technical University of Vienna in the field of Geographic Information Science, specializing in Fuzzy Geometries. Among others, she was a guest researcher at the Berkeley Initiative in Soft Computing (BISC) at the University of California, Berkeley. Her research interests focus on Data Analytics and Human Data Interaction.
Andreas Meier, Edy Portmann, Luis Terán
Learn more on springer.com
Andreas Meier, Edy Portmann, Killian Stoffel, Luis Terán
Learn more on springer.com
The article about the history of fuzzy logic in Switzerland can be read here or on the archives for the philosophy and history of soft computing.
vor der Brück, T. and Kaufmann, M. (2021). Hybrid Knowledge-based and Data-driven Text Similarity Estimation based on Fuzzy Sets, Word Embeddings, and the OdeNet Ontology. International Journal on Advances in Intelligent Systems, 14(1 & 2), pp. 114–120. http://www.iariajournals.org/intelligent_systems/
Meier, A., & Seising, R. (2018). Vague Information Processing. HMD Praxis der Wirtschaftsinformatik, 55(3), 465–466. https://doi.org/10.1365/s40702-018-0413-y (in German)
D’Onofrio, S., Müller, S. M., Papageorgiou, E., & Portmann, E. (2018). Fuzzy Reasoning in Cognitive Cities – An Exploratory Work on Fuzzy Analogical Reasoning Using Fuzzy Cognitive Maps. In: 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’18). Rio de Janeiro, Brazil – July 08-13 2018. IEEE
Portmann, E. (2017). The Gradual Arrival of Fuzziness in Switzerland. Archives for the Philosophie and History of Soft Computing. http://www.aphsc.org/index.php/aphsc/article/view/45/51
Kaufmann, M. A. (2015). Fuzzylogik: Eine Revolution des Geistes. Informatik-Spektrum, 1–8. https://doi.org/10.1007/s00287-015-0926-5 (in German)
D’Onofrio, S., & Tschudi, F. (2018). Design Thinking: Ein Videoprojekt zu Computing with Words schlägt neue Brücken zwischen Forschung und Praxis. In: Meier, Andreas; Seising, Rudolf (eds). Vague Information Processing (pp. 510-527). HMD Praxis der Wirtschaftsinformatik. Springer Fachmedien Wiesbaden. https://link.springer.com/article/10.1365%2Fs40702-017-0385-3 (in German)
Portmann, E. (2017). Wozu ist Soft Computing nützlich? Reflexionen anhand der Smart-City-Forschung. HMD Praxis der Wirtschaftsinformatik. https://link.springer.com/article/10.1365/s40702-017-0383-5 (in German)
Kaufmann, M., Meier, A., & Stoffel, K. (2015). IFC-Filter: Membership function generation for inductive fuzzy classification. Expert Systems with Applications, 42(21), 8369–8379. https://doi.org/10.1016/j.eswa.2015.06.034
Portmann, E. Meier, A. Cudré-Mauroux, P. Pedrycz, W. (2014). FORA – A Fuzzy Set Based Framework for Online Reputation Management. Fuzzy sets and systems, 269, pp. 90-114. Elsevier 10.1016/j.fss.2014.06.004.
Kaufmann, M., & Graf, C. (2012). Fuzzy Target Groups in Analytic Customer Relationship Management. In Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications (pp. 168–192). IGI Global. https://www.igi-global.com/chapter/fuzzy-target-groups-analytic-customer/62183
Donzé, L., & Meier, A. (2012). Applying Fuzzy Logic and Fuzzy Methods to Marketing. Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications, 1–14. https://doi.org/10.4018/978-1-4666-0095-9.ch001
Kaufmann, M., & Meier, A. (2009). An inductive fuzzy classification approach applied to individual marketing. In Fuzzy Information Processing Society, 2009. NAFIPS 2009. Annual Meeting of the North American (pp. 1–6). https://ieeexplore.ieee.org/document/5156393
Meier A., Schindler G., Werro N. (2008). Fuzzy Classification on Relational Databases. In Galindo J. (ed): Handbook of Research on Fuzzy Information Processing in Databases, Idea Group Inc., Hershey 2008. https://www.researchgate.net/publication/247930971_Fuzzy_Classification_on_Relational_Databases