460-4086/02 – Biologically Inspired Algorithms (BIA)

Gurantor departmentDepartment of Computer ScienceCredits4
Subject guarantorprof. Ing. Ivan Zelinka, Ph.D.Subject version guarantorprof. Ing. Ivan Zelinka, Ph.D.
Study levelundergraduate or graduateRequirementOptional
Year1Semesterwinter
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesFEI, HGF, USPIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
SKA206 Ing. Lenka Skanderová, Ph.D.
ZEL01 prof. Ing. Ivan Zelinka, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Combined Credit and Examination 10+0

Subject aims expressed by acquired skills and competences

The goal is to introduce the students with modern methods of calculation derived from evolutionary and biological processes (evolutionary algorithms, cellular automata etc.). Student will gain an overview of modern computer-based procedures principles of observation of biological processes and dynamics. Upon successful completion of graduate course will be able to apply the methods discussed in the course to real problems.

Teaching methods

Lectures
Tutorials

Summary

The course will discuss a wider range of evolutionary computation. They mentioned as historically classic techniques and modern algorithms. There will also be discussed at the introductory level, cellular automata, artificial life, neural networks, evolutionary hardware, DNA computing, etc. Great emphasis will be placed on the practical side of things - the ability to most discussed methods applied to practical examples. Students should have the comprehensive knowledge of the course of the above areas, including the possibility its use. The course includes laboratory exercises in which students will practice how to program the selected algorithms and their application to solving practical problems.

Compulsory literature:

Back, T., Fogel, B., Michalewicz, Z.: Handbook of Evolutionary Computation, Institute of Physics, London Davis L. 1996, Handbook of Genetic Algorithms, International Thomson Computer Press, ISBN 1850328250 Koza J.R. 1998, Genetic Programming, MIT Press, ISBN 0-262-11189-6 Price,K.,Storn,R.,etal.:DifferentialEvolution-APracticalApproachtoGlobalOptimization. Springer, Heidelberg

Recommended literature:

Ilachinsky A., Cellular Automata: A Discrete Universe, World Scientific Publishing, ISBN 978-9812381835, 2001 Hilborn R.C.1994, Chaos and Nonlinear Dynamics, Oxford University Press, ISBN 0-19-508816-8, 1994 Gheorghe Paun (Author), Grzegorz Rozenberg (Author), Arto Salomaa, DNA Computing: New Computing Paradigms, Springer, ISBN 978-3540641964

Way of continuous check of knowledge in the course of semester

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.

E-learning

Další požadavky na studenta

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

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Lectures: 1.Evolutionary algorithms 1. The current state of the field softcomputing, fuzzy logic, neural networks, evolutionary computing (EVT). Classification of evolutionary computation, historical facts, current trends in EVT. The central dogma, according to Darwin, and EVT Mendel. 2. Evolutionary Algorithms 2. No Free Lunch Theorem. Computational complexity and physical limitations algorithms. Multipurpose optimization and Pareto set. 3. Evolutionary algorithms 3. Restrictions placed on the utility function and individual parameters. Penalties and its impact on the geometry of the objective function. Working with real, integer and discrete values ​​of individual parameters. Genetic algorithms. GA terminology. Principle activities, Hybrid GA, messy GA, parallel GA, migration and diffusion models. 4. Evolutionary algorithms 4. Evolutionary Strategy. No-man (1 +1)-EC.Multi-EC (μ + Λ)-ES and (μ, λ)-ES. Multi-EC (μ + λ)-ES and (μ, λ)-ES. Adaptive EC.Particle swarm (Particle Swarm). Search suspended (Scatter Search). Ant colony optimization (ant Colony Optimization). 5. Evoluční algorithms 5. SOMA: Self-Organizing Migrating Algorithm principle of operation and strategies used by the algorithm: ATO, ATR ATAA and ATA. Differential evolution principle activities and used versions: DE/best/1/exp, DE/rand/1/exp, DE/rand-to-best/1/exp, DE/best/2 / exp DE/rand/2/exp, DE/best/1/bin, DE/rand/1/bin, DE/rand-to-best/1/bin, DE/best/2/bin, DE/rand/2/bin. SOMA, DE and permutation test problems. 6. Evolutionary algorithms 6. Techniques of Genetic Programming: Genetic Programming, grammatical evolution. Alternatives: analytical programming, Probabilistic Incremental Program Evolution - PIPE, Gene Expression Programming, Programming Multiexpression and more. 7. Evolutionary Hardware (EH). Inspiration in biology. Computing devices.Reconfigurable equipment. Evolutionary design and digital circuits. EH and cellular automata. Polymorphous electronics. 8. Cellular Automata (BA) and complex systems. Introduction, Formalism BA Dynamics and classification according to Wolfram's cellular automata, Conway's Game of Life, using BA modeling. 9. Artificial life. Basic definitions and existing systems and models. Tierra, biomorf, Sbeat, Sbart, Eden, Galapagos ... Self-reproducing automata according to Turing and von Neumann. Langton's loop, computer viruses and artificial life. Artificial Life and edge chaos (according to Kaufmann) 10. Neural Networks (ANN). History and basic principles of NS. The training set and its use NS. The basic types of networks and their applications to different types of problems. 11. Fractal geometry. History, definition of fractal, basic types of algorithms that generate fractals. Fractal dimension, interpolation and compression. Developmental systems and artificial life. L systems, turtle graphics, parametric L-systems, L-systems from the perspective of fractal geometry. 12. Immunological systems (IS). The principle of the IS, the IS limits, algorithms implementing IS imunotronics. 13. Swarm Intelligence (SI). Basic concepts and definitions, representative algorithms SI - Particle Swarm, scatter search, ant colony optimization, swarm robotic, artificial evolution complex systems. 14. DNA computing. DNA computing as part of bioinformatics, DNA and binary representation according to Adlemann. Watson Crickův machine. Mathematical modeling operations on DNA. 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 bio-inspired algorithms on the principles of GUI, 1 week - Creation of a module for generating population and fitness function, 1 week - Creation of a module selection techniques for parents (suitable candidates) to create offspring (better solution), 1 week - Creation of a module for crossover, 1 week - Creation of a modules of evolutionary algorithms, 4 weeks - Creation of a modules of symbolic regression, 4 weeks - Creation of a module with a simple cellular automaton, 1 week

Conditions for subject completion

Full-time form (validity from: 2015/2016 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 45  25
        Examination Examination 55  6
Mandatory attendence parzicipation:

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2020/2021 (N0688A140015) Industry 4.0 P English Ostrava 2 Choice-compulsory type B study plan
2019/2020 (N2647) Information and Communication Technology (1801T064) Information and Communication Security P English Ostrava 1 Optional study plan
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2019/2020 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2019/2020 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava Choice-compulsory study plan
2019/2020 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan
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2019/2020 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 2 Choice-compulsory study plan
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2019/2020 (N0541A170008) Computational and Applied Mathematics (S02) Computational Methods and HPC P English Ostrava Optional study plan
2019/2020 (N0612A140005) Information and Communication Security P English Ostrava 1 Optional study plan
2018/2019 (N2647) Information and Communication Technology (1801T064) Information and Communication Security P English Ostrava 1 Optional study plan
2018/2019 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava Choice-compulsory study plan
2018/2019 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2018/2019 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava Choice-compulsory study plan
2018/2019 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan
2018/2019 (N2658) Computational Sciences (2612T078) Computational Sciences P English Ostrava 1 Choice-compulsory study plan
2018/2019 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 2 Choice-compulsory study plan
2017/2018 (N2647) Information and Communication Technology (1801T064) Information and Communication Security P English Ostrava 1 Optional study plan
2017/2018 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava Choice-compulsory study plan
2017/2018 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava Choice-compulsory study plan
2017/2018 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2017/2018 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan
2017/2018 (N2658) Computational Sciences (2612T078) Computational Sciences P English Ostrava 1 Choice-compulsory study plan
2016/2017 (N2658) Computational Sciences (2612T078) Computational Sciences P English Ostrava 1 Choice-compulsory study plan
2016/2017 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava Choice-compulsory study plan
2016/2017 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava Choice-compulsory study plan
2016/2017 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2016/2017 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan
2016/2017 (N2647) Information and Communication Technology (1801T064) Information and Communication Security P English Ostrava 1 Optional study plan
2015/2016 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava Choice-compulsory study plan
2015/2016 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava Choice-compulsory study plan
2015/2016 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2015/2016 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner
V - ECTS - mgr. 2020/2021 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2019/2020 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2018/2019 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2017/2018 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2016/2017 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2015/2016 Full-time English Optional 401 - Study Office stu. block