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The course provides theoretically deeper knowledge of artificial intelligence in the range required by the Robotics branch of study. It consists of several parts: selected topics in pattern recognition and machine learning, basics of multiagent systems theory, and artificial life. The course emphasizes the relation of theoretical foundations and applications.

- Master study program Cybernetics and robotics, compulsory course of Robotics branch.
- The course is finished with an
**assessment**and an**exam**. - After completion of this course, students get
**6 credits**. - This corresponds to 2 hours of lecture, 2 hours of excercises and
**6 hours of home work each week**!

- We will tolerate
**at most 2 absences**. - In both parts of the semester (machine learning, multiagent systems), students can gain at most 20 points, i.e. 40 points in total.
- Each part will contain 1 or more evaluated assignments (homeworks); students must hand in their solutions (report and/or program code).
**Late policy:**late solutions will be penalized by 4 points for each started week of delay.

- Students must get
**at least 20 points**, i.e.**at least 10 points from each part**.

During the semester, students can get at most 100 points: 40 points for task solutions and 60 points for exam. To successfully pass the exam, students need to get at least 30 points out of 60, i.e. 50 %.

- Mařík V., Štěpánková O., Lažanský J. a kol: Umělá inteligence 1-5, Academia, Praha, 1993-2007
- [AIMA3] Russel S. a Norvig P.: Artificial Intelligence: A Modern Approach (3rd edition), Prentice Hall, 2010
- [AIMA] Russel S. a Norvig P.: Artificial Intelligence: A Modern Approach (2nd edition), Prentice Hall, 2003
- [RLAI] Sutton, S. R. Barto, A. G.: Reinforcement Learning: An Introduction, The MIT Press, 1998, available on-line
- Vidal, J. M.: Fundamentals of Multiagent Systems with NetLogo Examples, 2009, available on-line

courses/ae3m33ui/start.txt · Last modified: 2016/05/20 12:02 by xposik