Being able to explain what Artificial Intelligence (AI) is and what its major subfields areKnow major approaches (theory and methods) in AI, in particular Logic-based AIBeing able to apply some approaches to concrete settings

Slides, workshops, exercises to prepare at home and present in class

In this course we present an overview of the field of artificial intelligence and provide a detailed account of some of its traditional areas. In particular, we will focus on knowledge representation and reasoning and give an introduction or reminder of logic. These techniques usually require full knowledge or complete observability of the domain of discourse. We will then move towards settings with uncertainty and identify different sources of uncertainty. We will then focus on one of these and expand on reasoning with incomplete knowledge.

There will be two online assessments and a mini-project.

Topics covered in the module, but in particular logic and incomplete knowledge.

Points obtained from assessments and project will form the final grade. Both assessments and the project should be delivered for passing.Each of the deliverables will be marked numerically out of 100 achievable grade points each. It will be necessary in principle to achieve at least half of the achievable grade points (150) and achieve at least half of the points (50) on each assessment. We reserve the right to reward a condoned pass also if one assessment had less than half of the achievable points, but this will be reviewed on a case-by-case basis.Constructive interaction in class can earn extra (bonus) points.Grade points (x) to grades:x < 150: Nicht Genügend (5)150 <= x < 187: Genügend (4)187 <= x < 224: Befriedigend (3)224 <= x < 262: Gut (2)262 <= x: Sehr Gut (1)