The course provides theoretical and methodological knowledge and skills in classical AI (artificial intelligence) and robotics.
Heuristics for search. Search for games. Applied predicate logic. Classical planning: heuristics. Knowledge representation. Probability theory: axioms, conditional probability, Bayes' rule. Bayesian networks. Probabilistic reasoning over time, Hidden Markov Models. Decision trees and learning. Robotics: reinforcement learning, learning from demonstration, hybrid architectures, motion planning, odometry, metric and topological route planning, localization and map generation.
The course can be included in the Master's Program in Computational Science and Engineering
To be admitted you must have 60 ECTS-credits in Computing Science or 2 years of completed studies, in both cases including the courses Fundamentals of Artificial Intelligence (5DV121), Data Structures and Algorithms (5DV108/5DV127/5DV128), Fundations of Logic and Model Theory (5DV102) or equivalent. Proficiency in English equivalent to Swedish upper secondary course English A (IELTS (Academic) with a minimum overall score of 5.5 and no individual score below 5.0. TOEFL PBT (Paper-based Test) with a minimum total score of 530 and a minimum TWE score of 4. TOEFL iBT (Internet-based Test) with a minimum total score of 72 and a minimum score of 17 on the Writing Section).
Where the language of instruction is Swedish, applicants must prove proficiency in Swedish to the level required for basic eligibility for higher studies.
Applicants in some programs at Umeå University have guaranteed admission to this course. The number of places for a single course may therefore be limited.
Application and Tuition fees
As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.