Seminar Knowledge Representation and Computational Tractability SS 2011

Submitted by vaishakbelle on 4. January 2011 - 18:11

Knowledge Representation (KR) is a vibrant and exciting field in artificial intelligence. The endeavor rests on two fundamental ideas. First, to reason about the problem domain one must formalize it, perhaps in some logical formalism such as propositional logic or first-order logic. Second, for the representation to be useful one must be able to obtain reasonable and intuitive inferences in a timely fashion.
Unfortunately, propositional reasoning is intractable (Boolean reasoning is NP-COMPLETE) and first-order logic is undecidable. Thus, an important goal in the KR enterprise is to find a tradeoff be- tween the expressiveness of the representational language and the computational behavior of associated reasoning tasks. A main objective of this seminar is to discuss approaches bordering this tradeoff.

Seminar Foundations of AI SS 2009

Submitted by stf on 29. December 2008 - 14:18


The foundations of Artificial Intelligence, and the scope of the discipline has benefited from significant insights for the last 50 years: from symbolic representation and reasoning to theoretical assertiveness for learning programs. In this seminar, we cover a few ideas on the foundations of the aforementioned approaches, such as the situation calculus and the Frame Problem in logical formalisms for action and effects, non-monotonic reasoning, and graphical representations for decision-making and learning.
Recently, Artificial Intelligence has also benefited from the use of important results in the field of game theory. To this extent, we also include topics in non-cooperative game theory and the impact of game theory on Artificial Intelligence.