Sommersemester

Sommersemester

Lecture - The Logic of Knowledge Bases SS 2016

Note: This course starts on Monday, 18 April 2016.

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.

Submitted by Jens Claßen on 7. April 2016 - 12:54 categories [ ]

Proseminar Artificial Intelligence SS 2016

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 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.

Submitted by stf on 8. January 2016 - 16:05 categories [ ]

Seminar Forgetting and Relevance SS 2016

In this seminar we will study concepts of forgetting and relevance developed in the field of Knowledge Representation. Humans not only forget unintentionally but also intentionally, for example, when they obtain new information and delete previous contradicting and apparently false information. In fact, humans usually do not forget irrevocably; we can bring back memories and reconstruct forgotten knowledge. In formal languages as studied in KR, however, even supposedly simple forgetting often turns out very difficult. In this seminar, we will study techniques for forgetting in KR languages such as predicate logic, description logics, or answer set programs. Related to forgetting is the concept of relevance among different facts. For example, when some fact is to be forgotten, this may also affect other facts relevant to the forgotten fact. Relevance is useful to develop tractable reasoning and handling inconsistencies in a knowledge base.

Submitted by Christoph Schwering on 30. December 2015 - 20:59 categories [ ]

Lecture - Introduction to Knowledge Representation SS 2015

An announcement of the course can also be found in the course information system CAMPUS.

Submitted by Jens Claßen on 12. January 2015 - 11:57 categories [ ]

Proseminar Artificial Intelligence SS 2015

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 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.

Submitted by stf on 8. January 2015 - 16:59 categories [ ]

Lecture - The Logic of Knowledge Bases SS 2014

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.

Submitted by Jens Claßen on 1. April 2014 - 18:07 categories [ ]

Proseminar Artificial Intelligence SS 2014

The SS 2014 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 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.

Submitted by stf on 6. January 2014 - 3:05 categories [ ]

Seminar Dynamics of Knowledge and Belief SS 2014

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.

Submitted by Christoph Schwering on 6. January 2014 - 0:08 categories [ ]

Lecture - Introduction to Knowledge Representation SS 2013

An announcement of the course can also be found in the course information system CAMPUS.

Submitted by Jens Claßen on 1. February 2013 - 16:05 categories [ ]

Seminar Plan and Activity Recognition SS 2013

In this seminar we will study several different approaches to and aspects of plan and activity recognition. Recognizing what other agents are doing is an important aspect of intelligent systems. For example, a domestic service robot needs to understand what the human is doing in order to interact with him in a reasonable way. And a self-driving car should know what the other traffic participants are doing right now and infer what they are going to do in the next moments. Different domains bring along different problems and needs for levels of expressiveness like partial observability, incomplete knowledge, non-deterministic actions, adversarial agents, potentially hazardous situations. We will study some of the latest research on these problems and work out the particular strengths and weaknesses.

The topics include recent papers on plan and activity recognition.

Submitted by Christoph Schwering on 11. January 2013 - 15:14 categories [ ]