Computational Intelligence

Field of study: Computer Science
Description: In this line of research we are interested in investigating the theoretical basis, methodologies, languages and tools for solving complex problems, such as the problems known as algorithmically intractable (NP-complete or worse) and ill-defined (non-arithmetical) problems.

The resolution of these problems can be studied from three main axes: (a) methods of reasoning (search methods); (b) representation of knowledge; (c) learning mechanisms.

Among the main theoretical approaches considered in our research, we highlight: (a) logical systems (classical logic, temporal logic, fuzzy logic, etc.); (b) neural networks; (c) evolutionary computation; (d) ontologies.

On the other hand, some application classes have specific characteristics due to the importance of these problems in relevant situations in real life as well as the demand for specific methods.

The faculty has developed projects in the following application areas: (a) computer vision; (b) natural language processing; (c) image processing; (d) knowledge-based systems; (e) intelligent design; (f) intelligent environments to support education; (g) automatic proof of theorems; (h) pattern recognition; (i) intelligent retrieval of information.

Abbreviation Titlesort descending Starting date Deadline (months)
2006-36-C (ADD-RPD) 06/12/2006 48
ERCAMADA Teaching Convolutional Networks to Learn from Templates: Applied to Autonomous Driving 01/03/2018 36
AERO 10/04/2018 24
BD 01/03/2014 53
SIEEPEF 06/03/2015 24
2002-10-C 01/06/2002 10
CEVRA 05/05/2016 36
1998-24-C 01/01/1998 24
COCADOIC 01/12/2013 24
2005-15-C 01/10/2005 15
2009-24-A (RPF) 01/08/2009 24
2004-12-C (VOLUME) 01/01/2004 12
AAIISCCA 01/08/2016 24
1999-24-C 01/01/1999 24
PIH 01/03/2016 42
1997-24-C 01/01/1997 24
2006-8-C (MOGVIS) 28/08/2006 8
1997-24-C 01/01/1997 24
2007-12-C (PERCOM) 01/01/2007 12
MLPROD 06/08/2018 24


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