Genetic Programming
Objectives
To present an overview of the most commonly used evolutionary algorithms, including genetic algorithms, genetic programming, and particle swarm optimization.
In the course advanced research topics will be discussed.
General characterization
Code
300029
Credits
7.5
Responsible teacher
Mauro Castelli
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
Some familiarity with machine learning is expected.
Bibliography
Material e artigos fornecidos pelo professor.
Teaching method
Slides will be used to present the topics of the course. Research papers will be used to complement some of the advanced topics.
Evaluation method
Project (first and second epoch).
Subject matter
Introductive concepts on optimization.
Hill climbing and the properties of local search algorithms.
Tabu search.
Simulated Annealing.
Genetic Algorithms.
Genetic Programming.
Semantics in Genetic Programming
Particle Swarm Optimization.