Introduction to Artificial Intelligence

Relations:

It is not possible to register for the course AE4B33ZUI if the student is concurrently registered for or has already completed the course A4B33ZUI (mutually exclusive courses).

It is not possible to register for the course AE4B33ZUI if the student is concurrently registered for or has previously completed the course A4B33ZUI (mutually exclusive courses).

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Computer Science

Synopsis:

This course provides introduction to symbolic artificial intelligence. It presents the algorithms for informed and non-informed state space search, nontraditional methods of problem solving, knowledge representation by means of formal logic, methods of automated reasoning and introduction to markovian decision making.

Requirements:

Topics contained in course A0B01LGR.

Syllabus of lectures:

1. Introduction to artificial intelligence.

2. Problem solving using state space search.

3. Non-informed state space search.

4. Informed state space search - A* algorithm.

5. Nontraditional state space search methods.

6. Knowledge representation and rule-based systems reasoning.

7. Introduction to two-player games.

8. Logics and knowledge representation.

9. Reasoning in first-order predicate logic, situation calculus.

10. Introduction to uncertainty in knowledge representation. Markov models.

11. Markov chains and decision processes.

12. Modal logic - definitions and applications.

13. Temporal logic - definitions and applications.

14. Back-up class.

Syllabus of tutorials:

1. Non-informed state space search.

2. Informed state space search.

3. A* algorithm.

4. Constraint satisfaction problem.

5. Two-player games.

6. Two-player games.

7. Genetic algorithms and neural networks.

8. Review of mathematical logic, resolution principle.

9. Automated theorem provers.

10. Markov chains and decision processes.

11. Markov Decision Process toolbox.

12. Modal logic - examples.

13. Temporal logic - examples.

14. Back-up class, credits.

Study Objective:

This course provides an overview of the key issues of symbolic artificial intelligence.

Study materials:

Stuart Russell and Peter Norvig: Artificial Intelligence: A Modern Approach,

Prentice Hall, Second Edition, 2003.

Note:

Further information:

http://cw.felk.cvut.cz/doku.php/courses/ae4b33zui/start

No time-table has been prepared for this course

The course is a part of the following study plans: