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Computational Intelligence

Computational Intelligence

Code	15642
Year	1
Semester	S2
ECTS Credits	6
Workload	PL(30H)/T(30H)
Scientific area	Informatics
Entry requirements	Does not have.
Learning outcomes	The main goal of this CU is that the students acquire knowledge and competencies in the area of computational intelligence: they should master the models and language related to neural networks, evolutionary computation,swarm intelligence and fuzzy systems. They should be able to explain the key models and ideas in each of these areas and implement their main algorithms. They should also be able to solve problems using the methods from this CU.
Syllabus	1-Neural networks 1.1-The artificial neuron 1.2-Supervised learning 1.3-Practical issues regarding supervised learning 1.4-Unsupervised learning 2-Evolutionary computation 2.1-Genetic algorithms 2.2-Genetic programming 2.3-Evolutionary strategies 2.4-Coevolution 3-Swarm intelligence 3.1-Particle swarm optimization 3.2-Ant colony optimization 4-Fuzzy systems 4.1-Fuzzy systems 4.2-Fuzzy inference 4.3-Fuzzy control
Main Bibliography	-Os PDFs das aulas teóricas elaborados pelo docente / The PDFs presented on the theoretical classes. -James M. Keller, Derong Liu, David B. Fogel, Fundamentals of Computational Intelligence: Neural Networks, Fuzzy Systems, and Evolutionary Computation, 2016- -Andries P. Engelbrecht, Computational Intelligence, An Introduction, John Wiley & Sons, 2007. -J. Kennedy, R.C. Eberhart, Y. Shi, Swarm Intelligence, Morgan Kaufmann Publishers, 2001. -Aboul Ella Hassanien, Eid Emary, Swarm Intelligence: Principles, Advances, and Applications, 2015 -Simon O. Haykin, Neural Networks and Learning Machines (3rd Edition), 2008
Language	Portuguese. Tutorial support is available in English.