News
First Paper ExerciseWritten on 23.04.24 by Daniel Fišer Dear students, the first paper exercise is out, you can find it in CMS. You have until Tue April 30 14:15 to finish it. You can submit your solutions to CMS, or you can just bring it on paper to the tutorial next Tue April 30 where it will be discussed. If you submit your solution to CMS, please,… Read more Dear students, the first paper exercise is out, you can find it in CMS. You have until Tue April 30 14:15 to finish it. You can submit your solutions to CMS, or you can just bring it on paper to the tutorial next Tue April 30 where it will be discussed. If you submit your solution to CMS, please, include your name and matriculation number on the first page. Remember that these exercises are graded and you need to achieve at least 50% of all points to be admitted to the exam. Best, Dan Fiser |
AI Planning
AI Planning is one of the fundamental sub-areas of Artificial Intelligence, concerned with methods taking long-term action decisions in complex environments. The course builds directly upon the core course Artificial Intelligence to delve deeper into this topic. The course covers advanced methods for effective plan generation. A special emphasis lies on techniques supporting trust in learned action policies, through methods such as verification, testing, and explanation.
The students will gain a deep understanding of algorithms used in AI Planning, encompassing both symbolic methods, data-driven methods, and combinations thereof. Many of the algorithms and methodologies are generic and are relevant also in other CS sub-areas in which large transition systems need to be analyzed.
Prerequisites. Successful participation in the core course Artificial Intelligence is strongly recommended.