Sistemas Inteligentes
Objectives
Introducing the basis of optimization heuristics and machine learning
General characterization
Code
100097
Credits
6.0
Responsible teacher
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
Basis of computer programming is a necessary requirement to enroll this discipline.
Bibliography
Machine Learning. Tom Mitchell; Genetic programming: on the programming of computers by means of natural selection. J. Koza; 0; 0; 0
Teaching method
Classes are partitioned into theoetical classes and practical classes.
Theoretical classes will be held using the board and slides.
In the practical classes students will implement the algorithms presented in the theoretical classes.
Evaluation method
In both the first and the second examination epochs, the final evaluation is given by a weighted average between exam and project
Subject matter
Optimization problems: definition of problem and instance of a problem
Search space, neighborhood structure and related concept
No free lunch theorem
Local search
Simulated annealing
Genetic algorithms
Genetic Programming
Pareto dominance
Multi objective optimization (NSGA II)
Machine Learning
Classification and clustering
Performance of a Classifier
Generalization and overfitting
Feature selection
Artificial Neural Networks