Intelligent Systems are systems that exhibit reasoning, learning, and skills of making logical decisions without human intervention.
This course offers an exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments.
Introducing concepts, models, algorithms, and tools for development of intelligent systems.
This course provides an introduction to Computational Intelligence methodologies and more specifically: Fuzzy Ssytems and Evolutionary Computation.
Evolutionary Computation: Introduction, Main paradigms of Evolutionary Computation, (Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming). Basic elements in implementing an evolutionary algorithm. Mechanisms, operators, parameters. Use in search, optimization and problem solving. Demos and applications.
Fuzzy Systems: Introduction, fuzzy sets, operations, and relations, fuzzy sets and rules, Mamdani and TSK fuzzy rules and systems, design and implementation of fuzzy systems.
Evaluation is based on final exams and optional assignments/projects.
Projets and oral exams
The course aims to develop a substancial understanding of computational intelligence methodologies with a focus on Evolutionary Computation and Fuzzy Systems.
On completing the course, students should have achieved reasonable competence in these technologies.
They should also be able to:
– identify the reasons for proposing a problem solution based on a biological metaphor,
– design and implement an evolutionary algorithm to solve a problem,
– represent “vague” and “less” mathematical knowledge,
– combine some of the traditional design approaches with fuzzy-logic concepts,
– design and implement fuzzy-logic based systems and explore their unique characteristics,
– idenfity limitations of, and suitable applications.
– Engelbrecht Andries P. (2007), Computational Intelligence: An Introduction 2nd Edition, Wiley
– Eberhart, E. and Y. Shi., Computational Intelligence: Concepts and Implementations, Morgan Kaufmann, San Diego, 2007
– Kruse, R., Borgelt, C., Klawonn, F., Moewes, C., Steinbrecher, M., Held, P.(2013), Computational Intelligence – A Methodological Introduction, Springer
– Russell C. Eberhart, Yuhui Shi (2007), Computational Intelligence: Concepts and Implementations, Morgan Kaufmann
– Ross-Timothy (2010), Fuzzy Logic with Engineering Applications, 3rd Edition, Wiley
– Klir-George-J, Yuan-Bo, (1995) Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice-Hall
– Thomas Back, D.B Fogel, Z Michalewicz (2000), Evolutionary Computation 1: Basic Algorithms and Operators 1st Edition, CRC Press
– A.E. Eiben (Author), James E Smith (2015), Introduction to Evolutionary Computing, 2nd ed., Springer
– Mitchell-Melamie, “”An introduction to genetic algorithms””, MIT Press, 1996
