In this seminar we will study several modeling and reasoning techniques for knowledge and belief in dynamic systems. Knowledge is an important aspect of intelligent programs: while most of today's systems assume a closed world, i.e., everything they don't know to be true is assumed to be false, an intelligent system needs to consider possible that there are truths not known to the system. In a dynamic environment, i.e., an environment where one or multiple agents (inter)act, the system will usually have to acquire new knowledge through sensing. Potentially it may even revise its beliefs when it realizes some beliefs were wrong. In this seminar we will study various aspects of action, knowledge, and belief.
We plan to implement a peer review process for this seminar. That is, every student will read some other students' term paper and provide feedback in form of a written review. This shall not only deepen your understanding of the other topics, but it also introduces you to the academic review process.