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The Computational Intelligence Research group of UNINOVA (CA3) main mission is to actively participate in applied research, supported by projects, by defining new concepts, methods and algorithms capable of solving real-world problems
Intelligent decision making
The growing complexity of real decision making problems requires handling both quantitative and qualitative information. The major challenges of rationalizing decision processes are how to handle heterogeneous information, its intrinsic imprecision/uncertainty and its dynamic nature. The capability of representing and handling imprecise concepts is essential in today's information society, due to the large quantities of information available for decision making.

This research is mainly focused on concepts, methods and algorithms for solving multicriteria decision making and dynamic decision making problems and developing applications with special emphasis in the Space domain.

CA3 Relevant papers in this topic are (for more papers and downloads see publication section):

  • Campanella, G. & Ribeiro, R.A. (2012), "A Framework for dynamic multiple criteria decision making", Decision Support Systems., December, 2012. Vol. 52, pp. 52-60.
  • T. C. Pais, R. A. Ribeiro, L. F. Simões. Uncertainty in dynamically changing input data. In: Computational Intelligence in Complex Decision Systems. DaRuan (Ed), Atlantis Computational Intelligent Systems, Vol 2, Chapter 2, World Scientific (2010).
  • Simões, L., Bourdarias, C. & Ribeiro, R. (2012), "Real-Time Planetary Landing Site Selection -- A Non-Exhaustive Approach", Acta Futura. Vol. 5, pp. 39-52.
  • Campanella, G., Ribeiro, R.A. & Varela, L.R. (2011), "A Model for B2B Supplier Selection" Vol. Vol 107, pp. 221-228.. Series on Advances in Intelligent and Soft Computing, Springer.
  • G. Campanella, A. Pereira, R. A. Ribeiro, and L. R. Varela. Collaborative Dynamic Decision Making: a Case Study from B2B Supplier Selection. In Decision Support Systems - Collaborative Models and Approaches in Real Environments. Hernández, J.E., Zarate, P., Dargam, F. Delibašic, B., Liu, S. and Ribeiro, R. (Eds.), Lecture Notes in Business Information Processing (LNBIP), Springer Berlin Heidelberg, vol 121: 88-102 (2012).
  • R. A. Ribeiro, T. C. Pais, L. F. Simões. Benefits of full-reinforcement operators for spacecraft target landing. In: 'Preferences and Decisions', S. Greco, R. A. M. Pereira, M. Squillante, R. R. Yager, J. Kacprzyk (Eds.) Studies in Fuzziness and Soft Computing, Volume 257, Springer-Verlag (2010)
  • Pais, T., Ribeiro, R., Devouassoux, J. & Reynaud, S. (2008), "Dynamic ranking algorithm for landing site selection", Int. Conference on Information Processing and Management of Uncertainty (IPMU08)., June, 2008.
  • R. Marques-Pereira, Rita A. Ribeiro. Aggregation with generalized mixture operators using weighting functions. Fuzzy Sets and Systems, Vol 137, issue 1, (2003), 43-58.

Apoio FCT – Fundação para a Ciência e a Tecnologia no âmbito da Unidade de Investigação CTS - Centro de Tecnologia e Sistemas, referência UIDB/00066/2020