Gurantor department | Department of Computer Science | Credits | 4 |

Subject guarantor | prof. Ing. Ivan Zelinka, Ph.D. | Subject version guarantor | prof. Ing. Ivan Zelinka, Ph.D. |

Study level | undergraduate or graduate | ||

Study language | Czech | ||

Year of introduction | 2015/2016 | Year of cancellation | |

Intended for the faculties | FEI | Intended for study types | Follow-up Master |

Instruction secured by | |||
---|---|---|---|

Login | Name | Tuitor | Teacher giving lectures |

SKA206 | Ing. Lenka Skanderová, Ph.D. | ||

ZEL01 | prof. Ing. Ivan Zelinka, Ph.D. |

Extent of instruction for forms of study | ||
---|---|---|

Form of study | Way of compl. | Extent |

Full-time | Credit and Examination | 2+2 |

Combined | Credit and Examination | 10+0 |

The goal is to introduce the students with modern unconventional algorithms derived from physical and biological processes of complex systems. Student will gain an overview of modern computer-based algorithms based on observation of complex processes and dynamics. Upon successful completion of graduate course will be able to apply the methods discussed in the course to real problems.

Lectures

Tutorials

The aim of the lectures is to introduce to the students the problems of non-conventional algorithms, their biological - physical origin. In the lectures will be discussed the various areas of their origin, usually from natural complex systems with emphasis of their physical-mathematical and algorithmic description and implementation of the PC. The lectures will give the students an interdisciplinary perspective on the issue of non-conventional algorithms, complex systems and their dynamic behavior. Students get an overview of modern computational algorithms allowing to model and simulate the otherwise very complicated and complex systems (deterministic chaos, Thom's catastrophe theory, fractal geometry, swarm intelligence, algorithms, quantum mechanics, cellular automata, "physarium machines", "Self-Organized criticality", ...) and vice-versa will get insight on how are unconventional algorithms derived from above mentioned complex systems. After successfully completing the course will have an interdisciplinary graduate survey knowledge of unconventional algorithms and will be able to apply the methods discussed in the course to real problems. Students should be able to continue further in deeper self-study in this topic.

1. Back T., Fogel D. B. & Michalewicz Z., Handbook of Evolutionary Computation, (Institute of Physics, London), 1997
2. Hilborn R.C.1994, Chaos and Nonlinear Dynamics, Oxford University Press, ISBN 0-19-508816-8, 1994
3. Ilachinsky A., Cellular Automata: A Discrete Universe, World Scientific Publishing, ISBN 978-9812381835, 2001

Bekenstein J. D., Information in the Holographic Universe, Scientific American, August, 2003
R. Gilmore 1993, Catastrophe Theory for Scientists and Engineers, John Wiley and Sons, ISBN 0-486-67-539-4, 1993
Gheorghe Paun (Author), Grzegorz Rozenberg (Author), Arto Salomaa, DNA Computing: New Computing Paradigms, Springer, ISBN 978-3540641964
Zelinka I, Celikovsky S, Richter H and Chen G., (2010) Evolutionary Algorithms and Chaotic Systems, (Eds), Springer, Germany, 550s, 2010.

The examination is based on the elaboration of the protocols of the subject, by which the student demonstrates not only the understanding of the lecture information but also the ability to implement them in the given programming environment. To obtain a credit, you must hand over all the required protocols and have at least 80% of physical attendance at the laboratories. Credit is a vital condition for admission to the exam. The exam is oral.

It is required the ability to create programs in arbitrary programming language and apply lecture knowledge into algorithms.
Additional requirements are not defined.

Subject has no prerequisities.

Subject has no co-requisities.

Lectures:
1. Complexity. The current state of understanding of the issue of complex systems and their classification. Synergetics. Demonstration-motivational examples and videos demonstrating the occurrence of the behavior of complex systems in everyday real life.
2. Fractal geometry algorithms and visualization of complex structures. History, definition of fractals, basic types of algorithms generating fractals. Fractal dimension interpolation and compression. Algorithms of growth systems and artificial life. L-systems, turtle graphics, parametric L-systems, algorithm L-systems from the perspective of fractal geometry. Graphic design, art and fractal geometry.
3. Algorithms of deterministic chaos. Historical outline and classification of dynamical systems, generating chaos. Simple models and examples. Determinism and the edge of chaos (according to Kaufmann) .Typical chaotic systems: Lorenz model weather and strange attractor, electronic and three body problem (model binary star and the planet). Divergence nearby trajectory. Determinism and unpredictability.
4. Invariants of chaotic behavior. Feigenbaum constant, self-similarity, U-sequence, and computer chaos. Discrete dynamical systems. Basic simple models, Poincare sections, bifurcations, bifurcation diagram as a holistic view of system behavior, algorithms and examples.
5. Algorithms of deterministic chaos, from order to chaos: the path leading to chaotic behavior. Period doubling, quasiperiodicity, intermittence and crisis. Bifurcation and Thom's catastrophe. Algorithm of chaotic behavior and methods of reconstruction. Use of the cryptographic techniques of chaos control and its occurrence in economic systems
6. Thom's catastrophe theory and continuity with chaotic behavior. Introduction, basic models and hierarchies disasters. Their occurrence in the dynamics of systems and algorithms to identify the signs in the data. Examples of occurrence: economic systems, physical systems, mechanical systems.
7. Algorithms and complex systems. Complex systems generating the effect of "Self-Organized Criticality" (SOC), modeling (models of a pile of sand, ...) and real occurrence in complex systems (evolution, earthquakes, avalanches).
8. Cellular Automata (CA) and complex systems. Formalism CA, dynamics and classification of cellular automata by Wolfram, Conway's Game of Life, modeling using CA. Cellular automata and spatio-temporal chaos. CA and generation of music. And CA-effective solution to complex problems. CA complex algorithmic behavior based on simple rules.
9. Algorithms and complex networks. Introduction to complex networks, visualization methods and algorithms of their dynamics. Examples of the occurrence of complex networks (social networks, the dynamics of evolutionary processes, ...). Visualization of the dynamics of complex networks by using models of chaotic systems. Visualization techniques using evolutionary dynamics of complex networks.
10. Biological systems and their mathematical models. Dynamical systems and Lotka-Volterra equations for two coexisting species Lotka-Volterra equations for more than two coexisting species. Eco equation showing the interaction between multiple species. Nash equilibrium. Evolutionarily stable strategies (evolutionary stability, population game theory), replication, adaptive dynamics, replication of the network. Stability of N coexisting communities.
11. Swarm intelligence. Swarm algorithms, dynamic of swarm, examples, swarm algorithms, swarm robotics solutions of complex problems.
12. Physarum Machines: Computers from Slime Mould. Basic principles and structure of physarium. From Reaction–Diffusion (automata) to Physarum Computing. Routing Physarum with Repellents, Physarum Manipulators. Physarum Boats. Experimenting with Physarum.
13. Membrane Computing in Systems and Synthetic Biology. Basic principles, definitions and examples. Infobiotics as
information in Biotic Systems.
14. Summarizing the course. Relationships between different types of algorithms, their dynamics and behavior of complex systems.
Laboratories (for PC classrooms):
The seminar will focus on the practical application of the discussed techniques and solutions of selected problem examples.
- Creation of a single basic framework for unconventional algorithms on the principles of GUI, 1 week
- Module for fractal geometry, 2 weeks
- Module for deterministic chaos, 2 weeks
- Module for cellular automata, 2 weeks
- Module for the simulation of fundamental biological systems, 2 weeks
- Module for swarm intelligence, 2 weeks
- Module for simulating physarium, 2 weeks

Task name | Type of task | Max. number of points
(act. for subtasks) | Min. number of points |
---|---|---|---|

Credit and Examination | Credit and Examination | 100 (100) | 51 |

Credit | Credit | 45 | 20 |

Examination | Examination | 55 | 6 |

Show history

Task name | Type of task | Max. number of points
(act. for subtasks) | Min. number of points |
---|---|---|---|

Credit and Examination | Credit and Examination | 100 (100) | 51 |

Credit | Credit | 45 | 20 |

Examination | Examination | 55 | 6 |

Show history

Academic year | Programme | Field of study | Spec. | Form | Study language | Tut. centre | Year | W | S | Type of duty | |
---|---|---|---|---|---|---|---|---|---|---|---|

2019/2020 | (N2647) Information and Communication Technology | (1801T064) Information and Communication Security | P | Czech | Ostrava | 1 | Optional | study plan | |||

2019/2020 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | Czech | Ostrava | Choice-compulsory | study plan | ||||

2019/2020 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | Czech | Ostrava | Choice-compulsory | study plan | ||||

2019/2020 | (N0541A170007) Computational and Applied Mathematics | (S01) Applied Mathematics | P | Czech | Ostrava | Optional | study plan | ||||

2019/2020 | (N0541A170007) Computational and Applied Mathematics | (S02) Computational Methods and HPC | P | Czech | Ostrava | Optional | study plan | ||||

2018/2019 | (N2647) Information and Communication Technology | (1801T064) Information and Communication Security | P | Czech | Ostrava | 1 | Optional | study plan | |||

2018/2019 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | Czech | Ostrava | Choice-compulsory | study plan | ||||

2018/2019 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | Czech | Ostrava | Choice-compulsory | study plan | ||||

2017/2018 | (N2647) Information and Communication Technology | (1801T064) Information and Communication Security | P | Czech | Ostrava | 1 | Optional | study plan | |||

2017/2018 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | Czech | Ostrava | Choice-compulsory | study plan | ||||

2017/2018 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | Czech | Ostrava | Choice-compulsory | study plan | ||||

2016/2017 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | Czech | Ostrava | Choice-compulsory | study plan | ||||

2016/2017 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | Czech | Ostrava | Choice-compulsory | study plan | ||||

2016/2017 | (N2647) Information and Communication Technology | (1801T064) Information and Communication Security | P | Czech | Ostrava | 1 | Optional | study plan | |||

2015/2016 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | Czech | Ostrava | Choice-compulsory | study plan | ||||

2015/2016 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | Czech | Ostrava | Choice-compulsory | study plan |

Block name | Academic year | Form of study | Study language | Year | W | S | Type of block | Block owner |
---|