Reasoning with uncertainty is important in many fields in artificial intelligence, such as expert systems, robotics, neural networks, etc. The course will give a representative selection from the various formal models for dealing with uncertain knowledge, e.g., possibilistic logic for multi-agent systems, Bayesian probability theory, and elements of game theory. The aim of the course is to provide the logical ground on which the various formalisms can be understood, studied, and compared.
In the fall of 2015 the lectures take place on Mondays (room B0.209) and Tuesdays (room B0.207) at 3PM till 5PM.
For more information about the course see the Course Contents page.