Description
Evolutionary computation provides approximate solutions to various scientific and engineering problems in polynomial time. This class of problems includes search, optimization and learning problems. This course offers a broad introduction to the field of Genetic Algorithms and other fields of Evolutionary Computation leading to the exploration of recent techniques.
Objectives
Students should be able to:
- formulate and assess problems in evolutionary computation.
- assess the strengths and weaknesses of several approaches to evolutionary computation.
- assess and understand the key commonalities and differences in various evolutionary computation models.
- apply techniques in evolutionary computation to problems such as optimization, automatic programming, control, and biological modeling.
Students will implement some of these techniques and present latest achievements in the field.
Topics to be covered
Genetic Algorithms, Genetic Programming, Evolution Strategies, Evolutionary Programming and other nature-inspired global optimization techniques. For each topic the problem representation, the evolutionary operators and constraint handling will be studied.
Student Assessment
Oral discussion of the main topics and class participation (quasi-weekly assignments): 40%
- Book chapters
- Papers
- Reviews
Project proposal: 10%
Project report: 35%
Project presentation:15%
Instructor Information
Prof. Paulo Fazendeiro
Office: Room 4.12
Email: pandre (at) di.ubi.pt
URL: http://www.di.ubi.pt/~pandre
Class: Wednesday, 12h-13h
Office hours: Tuesday, 17h-18h or by email appointment
Resources and references
Scientific papers available at
Serviços de Documentação - Biblioteca da Universidade da Beira Interior.
Introduction to Evolutionary Computing, Eiben and Smith. Springer-Verlag, New York, 2003.
Evolutionary computation: a unified approach, Kenneth A. De Jong, MIT Press, 2006.
Evolutionary Computation for Modeling and Optimization, Daniel Ashlock, Springer Verlag, 2006.
Handbook of Evolutionary Computation, Bäck, T., Fogel, D., Michalewicz, Z., Oxford Univ. Press, 1997.
How to Read a Paper. S. Keshav. ACM SIGCOMM Computer Communication Review 37(3) 83-84, 2007.
