Logo ČVUT
CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2023/2024

Cybernetics and Artificial Intelligence

Login to KOS for course enrollment Display time-table
Code Completion Credits Range Language
BE5B33KUI Z,ZK 6 2P+2C English

It is not possible to register for the course BE5B33KUI if the student is concurrently registered for or has already completed the course B3B33KUI (mutually exclusive courses).

During a review of study plans, the course B3B33KUI can be substituted for the course BE5B33KUI.

During a review of study plans, the course AE3B33KUI can be substituted for the course BE5B33KUI.

During a review of study plans, the course A3B33KUI can be substituted for the course BE5B33KUI.

It is not possible to register for the course BE5B33KUI if the student is concurrently registered for or has already completed the course AE3B33KUI (mutually exclusive courses).

It is not possible to register for the course BE5B33KUI if the student is concurrently registered for or has already completed the course A3B33KUI (mutually exclusive courses).

In order to register for the course BE5B33KUI, the student must have registered for the required number of courses in the group BEZBM no later than in the same semester.

It is not possible to register for the course BE5B33KUI if the student is concurrently registered for or has previously completed the course B3B33KUI (mutually exclusive courses).

It is not possible to register for the course BE5B33KUI if the student is concurrently registered for or has previously completed the course A3B33KUI (mutually exclusive courses).

It is not possible to register for the course BE5B33KUI if the student is concurrently registered for or has previously completed the course AE3B33KUI (mutually exclusive courses).

Garant předmětu:
Tomáš Svoboda
Lecturer:
Petr Pošík, Tomáš Svoboda
Tutor:
Swati Dantu, Filipe Gama, Jana Kostlivá, Petr Pošík, Tomáš Svoboda, Pavel Šindler
Supervisor:
Department of Cybernetics
Synopsis:

The course introduces the students into the field of artificial intelligence and gives the necessary basis for designing machine control algorithms. It advances the knowledge of state space search algorithms by including uncertainty in state transition. Students are introduced into reinforcement learning for solving problems when the state transitions are unknown, which also connects the artificial intelligence and cybernetics fields. Bayesian decision task introduces supervised learning. Learning from data is demonstrated on a linear classifier. Students practice the algoritms in computer labs.

Requirements:

Basic knowledge of linear algebra and programming is assumed. Experience in Python and basics of probability is an advantage.

Syllabus of lectures:

What is artificial intelligence and what cybernetics.

Solving problems by search. State space.

Informed search, heuristics.

Games, adversarial search.

Making sequential decisions, Markov decision process.

Reinforcement learning.

Bayesian decision task.

Paramater estimation for probablistic models. Maximum likelihood.

Learning from examples. Linear classifier.

Empirical evaluation of classifiers ROC curves.

Unsupervised learning, clustering.

Syllabus of tutorials:

Computer lab organization.

Search.

Informed search and heuristics.

Sequential decision problems.

Reinforcement learning.

Pattern Recognition.

Study Objective:

The course introduces the students into the field of artificial intelligence and gives the necessary basis for designing machine control algorithms. It advances the knowledge of state space search algorithms by including uncertainty in state transition. Students are introduced into reinforcement learning for solving problems when the state transitions are unknown, which also connects the artificial intelligence and cybernetics fields. Bayesian decision task introduces supervised learning. Learning from data is demonstrated on a linear classifier. Students practice the algoritms in computer labs.

Study materials:

Stuart J. Russel and Peter Norvig. Artificial Intelligence, a Modern Approach, 3rd edition, 2010

Note:
Further information:
https://cw.fel.cvut.cz/wiki/courses/be5b33kui/start
Time-table for winter semester 2023/2024:
Time-table is not available yet
Time-table for summer semester 2023/2024:
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
roomKN:E-127
Pošík P.
Svoboda T.

11:00–12:30
(lecture parallel1)
Karlovo nám.
Kotkova cvičebna K4
roomKN:E-132
Dantu S.
12:45–14:15
(lecture parallel1
parallel nr.101)

Karlovo nám.
Laboratoř PC
Tue
Wed
Thu
room
Dantu S.
17:00–18:45
(lecture parallel1
parallel nr.102)

Fri
The course is a part of the following study plans:
Data valid to 2024-04-17
Aktualizace výše uvedených informací naleznete na adrese https://bilakniha.cvut.cz/en/predmet4358106.html