[ INBIPVOAINT ] VL Artificial Intelligence

(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS B3 - Bachelor's programme 3. year Computer Science Gerhard Widmer 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Computer Science 2021S
Objectives Students know the basic concepts underlying and defining the field of Artificial Intelligence (AI), including its history, fundamental goals and assumptions, general approach to problem modeling, and selected algorithms; they will have a broad overview of the field that permits them to pursue more in-depth studies, via more advanced classes or self-study, and to critically evaluate the potential benefits and dangers of AI.
Subject Definitions of AI. Problem solving as a search process: search algorithms (uninformed and heuristic), heuristic search in games. Knowledge representation and logical reasoning: inference in propositional logic. Reasoning with uncertain knowledge: knowledge representation and inference in Bayesian nets. Machine learning: inductive concept learning, reinforcement learning, learning about probabilities. Basics of computer perception.
Criteria for evaluation Written exam at the end of the semester
Methods Standard lectures with study materials (slides) provided.
Language English
Study material Pdf versions of the presentation slides used in the lecture are made available via KUSSS or Moodle (weekly).

Recommended reading (will not be needed if the lectures are attended on a regular basis): Russell, S.J. and Norvig, P. (2004). Artificial Intelligence: A Modern Approach (3rd Edition). Englewood Cliffs, NJ: Prentice-Hall.

Changing subject? No
Corresponding lecture (*)ist gemeinsam mit INBIPUEAINT: UE Artificial Intelligence (1,5 ECTS)
äquivalent zu

INMWAKVKINT: KV Künstliche Intelligenz (3 ECTS)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment