General Systems Theory

Lecturer:

Tutor:

Supervisor:

Department of Cybernetics

Synopsis:

In this class students will learn the general, broadly founded methodology of Systems Theory to gain a sufficient insight in general systems principles and their theoretical limits. The course aims a wrapping up knowledge from other special classes and giving a common frame for many special engineering problems encountered in practice. It is dealt with such concepts like identification, decomposition and self-organization.

Requirements:

Each group: consultations, written and oral presentation.

Syllabus of lectures:

1. Introduction: the role of GST in cybernetics, object, model, distinctions, system hierarchy.

2. Data system, generalized dynamic system, generative system and relations among them.

3. Entropy, basic definitions, properties, conditional entropy and mutual information and their properties

4. The problem of generative system parameter identification, generalization of data system to generative system.

5. Generative system simplification, variable elimination, resolution reduction, the best simplification selection

6. System structure identification: sub-system and super-system of a generative system, system decomposition

7. System reconstruction, mutual consistency of generalized dynamic systems, the join procedure

8. The problem of structure identification, reconstruction hypothesis generator, identification procedure

9. Applications of generalized dynamic system structure identification on real problems

10. Distributed and autonomous systems: principles of distributivity, autonomy of elements

11. Multiagent systems, self-organization of a community of autonomous systems, emergent behaviour

12. Methods of system engineering work

13. Work with bibliographic resources, written and oral form of communication, preparation of a presentation

14. Course summary, putting it into context with applied disciplines

Syllabus of tutorials:

For the „individual projects“, small working groups of students will be established.

1. Organisational matters, seminars/labs detailed contents

2. Sample individual projects assignment

3. Individual work on the sample individual project - part I.

4. Individual work on the sample individual project - part II.

5. Presentation of individual work partial results - requirement specification documents

6. Individual work on the sample individual project - part III.

7. Individual work on the sample individual project - part IV.

8. Individual work on the sample individual project - part V.

9. Presentation of individual work partial results - resource analysis an timing

10. Individual work on the sample individual project - part VI.

11. Individual work on the sample individual project - part VII.

12. Presentation of individual work results - discussion on results part I.

13. Presentation of individual work results - discussion on results part II.

14. Summary, (spare space)

Study Objective:

Study materials:

[1] Klir, G. J.: Architecture of Systems Problem Solving. Plenum Press, 1985 [2] Papoulis, A.: Probability, Random Variables and Stochastic Processes. McGraw-Hill, 1991

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 - Artificial Intelligence- structured studies (compulsory course)