Computational intelligence techniques Field of study: Computer Science
Programme code: W4-N2IN19.2021

Module name: Computational intelligence techniques
Module code: W4-IN-N2-20-F-TIO
Programme code: W4-N2IN19.2021
Semester:
  • winter semester 2023/2024
  • summer semester 2022/2023
  • winter semester 2022/2023
  • summer semester 2021/2022
Language of instruction: Polish
Form of verification: course work
ECTS credits: 4
Description:
The metaheuristic algorithm can be used to solve any problem that can be described with some terms defined by the algorithm. However, it is most often used to solve optimization problems. A disadvantage of metaheuristic algorithms is the fact that they do not guarantee finding a solution and, moreover, usually it is not possible to give the time of their operation. The effectiveness of metaheuristics also depends largely on the parameters that appear in such algorithms. Unfortunately, there are no universal values of these parameters that behave best for all possible input data.
Prerequisites:
(no information given)
Key reading:
1. Arabas J., Lectures on evolutionary algorithms, Warsaw, 2004, WNT. 2. I. Rechenberg. Evolution strategy: Nature’s way of optimization. In Optimization: Methods and Applications, Possibilities and Limitations, pages 106-126. Springer Science & BusinessMedia, 1989. doi: 10.1007 / 978-3-642-83814-96. 3. Michalewicz Z., Genetic algorithms + data structures = evolutionary programs, Warsaw, 2001, WNT. 4. Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Kluwer Academic Publishers. ISBN 978-0-201-15767-3. 5. Glover, F .; Kochenberger, G.A. (2003). Handbook of metaheuristics. Springer, International Series in Operations Research & Management Science. ISBN 978-1-4020-7263-5.
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
Knows advanced metaheuristics and their applications in selected optimization problems. [M_001]
 K_W01 [1/5] K_W02 [1/5]
Is able to select a method to solve a presented optimization problem [M_002]
 K_U01 [1/5] K_U05 [1/5]
Can write a program that implements a selected metaheuristics for the purpose of optimization calculations [M_003]
 K_U02 [1/5] K_U03 [1/5] K_U04 [1/5]
Understands the need to develop decision-making methods for optimisation problems [M_004]
 K_K01 [1/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Colloquium [W_001]
Written work on the description of existing techniques and their adaptation to selected optimization problems.
 M_001
Presentation of the programme related to the implemented project. [W_002]
Presentation of the program and verification of its effectiveness for the selected optimization problem.
 M_001 M_002 M_003
Preparation of the multimedia presentation [W_003]
Presentation of advantages and disadvantages of the selected computational intelligence technique and its verification on a specific optimization problem
 M_001 M_002 M_004
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [Z_001]
Giving the educational content in verbal form with the use of content visualization. Focusing on conceptually difficult material and indicating addresses of websites and e-learning package
 15
Getting to know the topic of the lecture using the existing packages of methods: script, websites and e-learning package
 30 Colloquium [W_001]
laboratory classes [Z_002]
Detailed preparation of students for the implementation of algorithms with indication of the methodology of conduct, indication of the sequence of activities to be performed
 30
Self-development and preparation of students for the colloquiums of the laboratory. Project execution - implementation of a given system in a multi-person group
 45 Colloquium [W_001] Presentation of the programme related to the implemented project. [W_002] Preparation of the multimedia presentation [W_003]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)