Cybernetics and Artificial Intelligence

Lecturer:

Tutor:

Supervisor:

Department of Cybernetics

Synopsis:

A general course enabling to understand the goals and principles of cybernetics and artificial intelligence and to organize different topics studied in the branch of study within a unified framework. The course covers the main principles of dynamic systems, entropy, information theory, algorithmic decidability, AI techniques for problem solving, statistical decision theory, machine learning and formal knowledge representation. The unifying conceptual approach to many diverse parts of cybernetics and artificial intelligence is the key feature of this course.

Requirements:

https://cw.felk.cvut.cz/doku.php/courses/a3b33kui/start

Syllabus of lectures:

During the first consultation clas, the form and frequency of further consultations will be settled, semestral work will be assigned and deadlines agreed.

For more detail on this class content see X33KUI.

Syllabus of tutorials:

Students will elaborate 3 semestral tasks.

Study Objective:

Study materials:

- Rich, E., Knight, K.: Artificial Intelligence. Mc-Graw Hill, 1991

- W. R. Ashby: An Introduction To Cybernetics, available at http://pespmc1.vub.ac.be/books/IntroCyb.pdf

- R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification (2nd ed.), John Wiley and Sons, 2001.

- T. Mitchell: Machine Learning, McGraw Hill, 1997.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Computer Technology- structured studies (compulsory elective course)
• Cybernetics and Measurements- structured studies (compulsory course)
• Inteligentní systémy (elective specialized course)
• Manažerská informatika (elective specialized course)
• Softwarové inženýrství (elective specialized course)
• Web a multimedia (elective specialized course)