The course offers introduction into some parts of nature-inspired
computing. The topics of the course are self-organisation in nature and
artificial systems, swarm intelligence algorithms, social insects
colonies organisation. Organisms can co-operate to achieve certain tasks,
their methods are effective in general optimisation and learning tasks.
The aim of the course is to show a collection of these algorithms, and
examine their components and their behavior.
Last update: T_UFAL (17.05.2012)
Přednáška je úvodem do některých algoritmů inspirovaných přírodou. Tématy
budou samoorganisace v přirozených a umělých systémech, algoritmy
inteligentních rojů, organisace sociálního hmyzu. Organismy umí
spolupracovat k dosažení určitého cíle, tyto metody je možné využít i v
obecných optimalisačních a učících úlohách. Cílem přednášky je představit
skupinu těchto algoritmů, prozkoumat jejich komponenty a chování.
Course completion requirements -
Last update: Mgr. Nino Peterek, Ph.D. (10.06.2019)
Presentation of own implementation of two selected algorithms from the course.
Last update: Mgr. Nino Peterek, Ph.D. (10.06.2019)
Předvedení vlastní implementace dvou algoritmů přírodního učení.
Literature -
Last update: Mgr. Nino Peterek, Ph.D. (01.10.2013)
D. Corne, A. Reynolds, E. Bonabeau (2010). Swarm Intelligence, in Handbook of Natural Computing (G. Rozenberg, T. Back, J.N. Kok, eds.), vol. II: Broader Perspective. Springer
D. W. Corne, K. Deb, J. Knowles, X. Yao (2010). Selected Applications of Natural Computing, (G. Rozenberg, T. Back, J.N. Kok, eds.), vol. II: Broader Perspective. Springer
Blum, C. and Li, X. , Swarm Intelligence in Optimization, in Blum, C. and Merkle, D. (eds.), Swarm Intelligence - Introduction and Applications, Springer, 2008: 43-85, 2008
M. Dorigo, M. Birattari, and T. Stützle (2006). Ant Colony Optimization: Artificial Ants as a Computational Intelligence Technique, IEEE Computational Intelligence Magazine, November:28-39.
X.S. Yang and S. Deb (2010). Engineering Optimisation by Cuckoo Search, International Journal of Mathematical Modelling and Numerical Numerical Optimisation, 1(4):330-343.
C.-R. Wang, C.-L. Zhou, and J.-W. Ma (2005). An Improved Artificial Fish-Swarm Algorithm and Its Application in Feed-forward Neural Networks, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, vol. 5:2890-2894
Omidvar, M., Li, X., and Yao, X. , Smart Use of Computational Resource Based on Contribution for Cooperative Co-evolutionary Algorithms, in Proceedings of Genetic and Evolutionary Computation Conference (GECCO'11), ACM Press: 1115-1122, 2011
Last update: Mgr. Nino Peterek, Ph.D. (01.10.2013)
D. Corne, A. Reynolds, E. Bonabeau (2010). Swarm Intelligence, in Handbook of Natural Computing (G. Rozenberg, T. Back, J.N. Kok, eds.), vol. II: Broader Perspective. Springer
D. W. Corne, K. Deb, J. Knowles, X. Yao (2010). Selected Applications of Natural Computing, (G. Rozenberg, T. Back, J.N. Kok, eds.), vol. II: Broader Perspective. Springer
Blum, C. and Li, X. , Swarm Intelligence in Optimization, in Blum, C. and Merkle, D. (eds.), Swarm Intelligence - Introduction and Applications, Springer, 2008: 43-85, 2008
M. Dorigo, M. Birattari, and T. Stützle (2006). Ant Colony Optimization: Artificial Ants as a Computational Intelligence Technique, IEEE Computational Intelligence Magazine, November:28-39.
X.S. Yang and S. Deb (2010). Engineering Optimisation by Cuckoo Search, International Journal of Mathematical Modelling and Numerical Numerical Optimisation, 1(4):330-343.
C.-R. Wang, C.-L. Zhou, and J.-W. Ma (2005). An Improved Artificial Fish-Swarm Algorithm and Its Application in Feed-forward Neural Networks, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, vol. 5:2890-2894
Omidvar, M., Li, X., and Yao, X. , Smart Use of Computational Resource Based on Contribution for Cooperative Co-evolutionary Algorithms, in Proceedings of Genetic and Evolutionary Computation Conference (GECCO'11), ACM Press: 1115-1122, 2011
Requirements to the exam -
Last update: Mgr. Nino Peterek, Ph.D. (13.10.2017)
Implementation of two selected algorithms from the course.
Last update: Mgr. Nino Peterek, Ph.D. (13.10.2017)
Zkouška spočívá v předvedení vlastní implementace dvou algoritmů přírodního učení.
Syllabus -
Last update: Mgr. Nino Peterek, Ph.D. (01.10.2013)
Self-Organisation
Self-organisation in nature, physics, chemistry, biology, mathematics,
computer science, linguistics, human society.
Swarm intelligence algorithms
Ant colony optimisation, the bacterial foraging algorithm, particle swarm
optimisation, the bee colony algorithm, cuckoo search, the firefly