Table of Contents

AE3M33UI: Artificial Intelligence

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.

Assessment requirements

Exam

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 %.

Literature

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