5 ECTS cr
|Language of instruction
1. is able to identify the types of problems that can be solved using methods of artificial intelligence.
2. knows the basic concepts of intelligent agents, the common search methods used in artificial intelligence, logic based reasoning and applying planning techniques to problems of artificial intelligence.
3. can also apply simple methods to reasoning under uncertainty and machine learning from observation.
4. In addition the student will be able to implement the most common search methods.
1) Introduction, 2) Rational (Intelligent) Agents and Uninformed Search, 3) Informed Search, 4) Programming Project 1 (Pacman 1), 5) Adversarial Search (Games), 6) Programming Project 2 (Pacman 2), 7) Uncertainty and Utilities, 8) Markov Decision Processes, 9) Reinforcement Learning, 10) Bayesian Networks, 11) Machine Learning (learning from Observation), 12) Advanced Applications, 13) Conclusions
|Mode of delivery
|Learning activities and teaching methods
28 hours of lectures and a programming exercise (approximately 25 hours) during period 3, the rest as independent work.
Computer Science and Engineering students and other Students of the University of Oulu.
|Prerequisites and co-requisites
|Recommended optional programme components
The course is an independent entity and does not require additional studies carried out at the same time.
|Recommended or required reading
The course material is based on the Artificial Intelligence course of Berkely University and the book "Artificial Intelligence, A Modern Approach" by Russell & Norvig.
2) Russell S., Norvig P.: Artificial Intelligence, A Modern Approach, Second Edition, Prentice Hall, 2003.
|Assessment methods and criteria
The course is passed with a final exam and a passed programming exercise.
Read more about assessment criteria at the University of Oulu webpage.
1-5 / fail.
Pekka Sangi and Jaakko Suutala (lecturer)
Mohammad Tavakolian (assistant)
|Working life cooperation