Teaching

Teaching at KBSG

Teaching Overview

Submitted by stf on 27. November 2007 - 12:19

Our regular teaching activities include Introduction to Artificial Intelligence, Knowledge Representation, and Logic of Knowledge-Bases. Browse the categories to see what's up this semester.

Lectures | Seminars | Laboratories | Proseminars

Lecture - The Logic of Knowledge Bases SS 2018

Submitted by Jens Claßen on 15. February 2018 - 16:37

This course is about the logic of knowledge bases, in two distinct but related senses. On the one hand, a knowledge base is a collection of sentences in a representation language that entails a certain picture of the world represented. On the other hand, having a knowledge base entails being in a certain state of knowledge where a number of other epistemic properties hold. One of the principal aims of this course is to develop a detailed account of the relationship between symbolic representations of knowledge and abstract states of knowledge. Students wishing to attend the course should be familiar with first-order predicate logic.

Proseminar Artificial Intelligence SS 2018

Submitted by stf on 15. January 2018 - 12:02

The proseminar will be on different (sub-)topics from artificial intelligence. We largely follow the lines of the well known textbook by Stuart Russell and Peter Norvig "Artificial Intelligence - A Modern Approach".

We 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.

An L²P-Lernraum of the course contains more info and material (for participants only!).

Seminar "Reasoning, Planning, and Scheduling with Uncertainty"

Submitted by Till Hofmann on 13. January 2018 - 13:46

In this seminar, we will study uncertainty in the context of reasoning, planning, and scheduling. For reasoning about actions, we will look into stochastic extensions of the Situation Calculus, a well-known formalism for reasoning about dynamic domains. In the classical Situation Calculus, all actions are deterministic. In this seminar, we will learn about extensions that allow non-deterministic and probabilistic actions. For planning, we will investigate probabilistic extensions to classical planning frameworks such as the Planning Domain Definition Language (PDDL) and compare them to Markov Decision Processes (MDPs). For scheduling, we will learn about mechanisms for solving scheduling problems with probabilistic task durations.

Lecture - Introduction to Artificial Intelligence WS 2017/2018

Submitted by Jens Claßen on 26. September 2017 - 13:57
See Campus for announcements for Note:
  • To access the L2P room, you need to register for the course in Campus ("Zum klassischen Anmeldeverfahren"). There we publish slides, announcements, etc.
  • To take the exam, you need to do the modular registration process which closes 10 November.

Lecture - Introduction to Knowledge Representation SS 2017

Submitted by Jens Claßen on 3. February 2017 - 12:26
See Campus for announcements for Note:
  • To access the L2P room, you need to register for the course in Campus ("Zum klassischen Anmeldeverfahren"). There we publish slides, announcements, etc.
  • To take the exam, you need to do the modular registration process which closes 18 November.

Seminar "Selected Topics on Planning and Plan Execution for Robotic Systems" SS 2017

Submitted by Till Hofmann on 9. January 2017 - 18:41

In this seminar we will study plan generation and plan execution in robotic domains. While planning deals with the problem of finding suitable actions to accomplish a certain goal, plan execution and monitoring on robots come with additional problems: The agent's knowledge is no longer complete, the environment may change during plan execution, humans and other agents may interfere with the agent's actions, and resource and temporal constraints need to be honored. The plan executive needs to execute actions physically on a robot, adapt to changes during execution, and repair the current plan or replan if necessary. In this seminar, we will look at various methods to deal with those problems and we will investigate how these methods are applied on real-world robotic systems.