460-6017/02 – Bio-Inspired Computing (BIOIV)
| Gurantor department | Department of Computer Science | Credits | 10 |
| Subject guarantor | prof. RNDr. Václav Snášel, CSc. | Subject version guarantor | prof. RNDr. Václav Snášel, CSc. |
| Study level | postgraduate | Requirement | Choice-compulsory type B |
| Year | | Semester | winter + summer |
| | Study language | English |
| Year of introduction | 2015/2016 | Year of cancellation | |
| Intended for the faculties | FEI | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
Goals of the course: Bio-inspired computing
Teaching methods
Individual consultations
Summary
The content of the subject is following. Current state of the field of softcomputing, fuzzy logic, neural networks, evolutionary computing (EVT). Classification of evolutionary computational techniques, historical facts, current trends in EVT field. The central dogma of EVT by Darwin and Mendel. Basic concepts: individual, population, fitness, fitness function, representation of individuals. Fitness functions, design principles, test functions, computational complexity and theoretical limits of algorithms, P and NP problems. Permutation testing problems. Multipurpose optimization, Paret set, fitness function design for multipurpose optimization, examples. Selected stochastic algorithms: local search method, blind algorithm, climbing algorithm, simulated annealing. Selected stochastic algorithms with evolutionary elements: simulated annealing with elitism, taboo search. Particle swarm, Scatter Search, Ant Colony Optimization. Self-organizing Migration Algorithm, principle of operation and algorithm used: ATO, ATR, ATA and ATAA. SOMA and permutation test problems. Differential evolution.
Compulsory literature:
Maurice Clerc. Particle Swarm Optimization, Wiley-ISTE, 2006.
Marco Dorigo, Thomas Stutzle. Ant Colony Optimization, The MIT Press, 2004.
Andries P. Engelbrecht, Fundamentals of Computational Swarm Intelligence, Wiley, 2006.
Recommended literature:
Kenneth Price, Rainer M. Storn, Jouni A. Lampinen. Differential Evolution: A Practical Approach to Global Optimization, Springer, 2005.
Christine Solnon. Ant Colony Optimization and Constraint Programming, Wiley-ISTE, 2010.
Yang Xiao, Fei Hu. Bio-inspired Computing and Communication Networks, CRC, 2010.
Way of continuous check of knowledge in the course of semester
Student vypracuje článek z vybraného pokročilého tématu. Tento článek odprezentuje v rámci kurzu.
Ústní zkouška.
E-learning
Other requirements
Additional requirements for the student are not.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
The current state of the field softcomputing, fuzzy logic, neural networks, evolutionary computing (EVT), etc.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks