Softcomputing

Lecturer:

Tutor:

Supervisor:

Department of Cybernetics

Synopsis:

The aim of this course is to get the students knowledgeable with non-traditional computational techniques of optimisation, state-space search, control and decision-making. Many of the softcomputing methods utilise analogies with various phenomena in nature and/or society. Results obtained by these methods often have a high quality, but their absolute reliability is never guaranteed. During the seminars the students will get a chance to get basic practical skills with a sample softcomputing problem.

Requirements:

For successful completion of the course, it is necessary to present the results of the individual work to other students and explain the approaches used.

Syllabus of lectures:

1. Introduction to softcomputing methods, relationship to phenomena known from other scientific fields

2. Fuzzy sets and fuzzy logics

3. Fuzzy logics and decision-making

4. Fuzzy control

5. Neural networks - basic principles, their learning and set-up

6. Neural networks with backward propagation

7. Kohonen's learning networks

8. Evolutionary computing - basic principles and operators

9. Genetic algorithms - function principles

10. Genetic algorithms - problem representation, convergence

11. Genetic algorithms in constrained problems, special representations

12. Genetic programming - principles and comparison with genetic algorithms

13. Specific problems of evolutionary computing techniques, softcomputing applications

14. Summary (spare space)

Syllabus of tutorials:

1. Organisational matters, seminars/labs detailed contents

2. Softcomputing in general

3. Fuzzy logics principles

4. Fuzzy logics for control and decision-making - part 1.

5. Fuzzy logics for control and decision-making - part 2.

6. Neural networks - part 1.

7. Neural networks - part 2.

8. Neural networks - part 3.

9. Evolutionary computing (EC) - basic operators, their implementation, individual task of EC given

10. Individual work on the EC task - part 1.

11. Individual work on the EC task - part 2.

12. Individual work on the EC task - part 3.

13. Presentation of individual work results - discussion on the results

14. Summary, (spare space)

Study Objective:

Study materials:

There is no text-book covering the course completely; any book on modern operating systems can be used. The lecturer will hint resources to particular topics.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Cybernetics and Measurements - Control Engineering- structured studies (compulsory elective course)
• Cybernetics and Measurements - Artificial Intelligence- structured studies (compulsory elective course)
• Cybernetics and Measurements - Measurement and Instrumentation Systems- structured studies (compulsory elective course)
• Cybernetics and Measurements - Aeronautical Engineering and Control Systems- structured studies (compulsory elective course)