_tagpages/recruiting.md

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-layout: tagpage
-tag: recruiting
-title: Recruiting
----

_tagpages/release.md

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-layout: tagpage
-tag: release
-title: Release
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_tagpages/talk.md

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-layout: tagpage
-tag: talk
-class: event
-title: Talk
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_tagpages/workshop.md

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-layout: tagpage
-tag: workshop
-title: Workshop
-class: event
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contact.md

@@ -2,17 +2,18 @@
 layout: default
 title: KWARC Contact
 ---
- For general questions, contact the head of the group:
+For general questions, contact the head of the group:
+
 [Prof. Dr. Michael Kohlhase](/people/mkohlhase/)
 
 *Professur für Wissensrepräsentation und -verarbeitung*; Informatik, FAU Erlangen-Nürnberg
 
-**Office**: Martensstraße 3, 91058 Erlangen, Room11.139, tel/fax: (49) 9131-85-64052/55, <michael.kohlhase@fau.de>
+**Office**: Martensstraße 3, 91058 Erlangen, Room11.139, tel/fax: (49) 9131-85-64052/55, michael.kohlhase  [at] fau.de
 
-**Secretary**: Gabriele Schönberger, Room 11.158, tel/fax: (49) 9131-85-64052/55, <gabriele.schoenberger@fau.de>
+**Secretary**: Gabriele Schönberger, Room 11.158, tel/fax: (49) 9131-85-64052/55, gabriele.schoenberger [at] fau.de
 
 For specific questions, please contact the members of the KWARC group directly or use the mailing lists:
 
- * <core@kwarc.info> (the core group, i.e. PIs, postdocs, and Ph.D. students)
- * <group@kwarc.info> (all KWARCies, i.e. including students)
- * <admin@kwarc.info> (for systems, ...)
+ * core [at] kwarc.info (the core group, i.e. PIs, postdocs, and Ph.D. students)
+ * group [at] kwarc.info (all KWARCies, i.e. including students)
+ * admin [at] kwarc.info (for systems, ...)

courses/AIProj.md

+---
+layout: course
+
+title: AI Research Project
+instructors:
+    - mkohlhase
+    - frabe
+semesters: 
+    - SS16
+    - WS16/17
+    - SS17 
+    - WS17/18
+    - SS18 
+    - WS18/19
+    - SS19 
+    - WS19/20
+    - SS20 
+    - WS20/21
+    - SS21 
+    - WS21/22
+    - SS22 
+---
+The KWARC group offers guided research projects in Artificial Intelligence either at the Bachelor's level or the Master's level.
+The topics of these projects are individually tailored to the student's interest and the
+projects themselves will be supervised closely by senior KWARC members.
+
+Projects will consist of a research/development project commensurable in size with the
+ECTS points awarded, and end in a research report that documents it. 
+
+Even though administratively, AI Projects are tied to particular semesters, the research
+itself can be conducted at any time, and we are quite flexible in scheduling.  
+
+See the [KWARC research page](/research/) for a general introduction to the research
+conducted in the KWARC group and
+[the KWARC research topics list](http://gl.kwarc.info/kwarc/thesis-projects) for
+exemplary topics.

courses/GenICT1.md

+---
+layout: course
+
+title: General Information and Communication Technology I 
+instructors:
+    - mkohlhase
+    - Prof.  Jürgen Schönwälder
+    - Prof. Peter Baumann
+    - Prof. Herbert Jaeger
+    
+organization: Jacobs University
+semesters:
+    - Fall14
+    - Fall15
+---
+An Introduction to Computer Science for students of all subjects. 

courses/GenICT2.md

+---
+layout: course
+
+title: General Information and Communication Technology II 
+instructors:
+    - mkohlhase
+    - Prof.  Jürgen Schönwälder
+    - Prof. Peter Baumann
+    - Prof. Herbert Jaeger
+
+organization: Jacobs University
+semesters:
+    - Spring15
+---
+An Introduction to Computer Science for students of all subjects. 

courses/KRMT.md

+---
+layout: course
+title: Logic-Based Representation of Mathematical/Technical Knowledge
+instructors:
+  - mkohlhase
+  - frabe
+semesters:
+    - SS17 
+    - SS18 
+    - SS19 
+    - SS20 
+    - SS21 
+    - SS22 
+    - SS23 
+    - SS25 
+---
+
+This course covers the foundations of mathematics, modular formalizations in theory graphs,
+narrative structures in informal mathematical/technical documents, and the formalization
+of logical languages in meta-logical frameworks. 
+
+This is (tradictionally) a small course, so we can make it very interactive and
+project-like. The contents are split between 
+* lectures, where we discuss the concepts and
+* labs, where we jointly formalize mathematical knowledge and representation languages in
+  [OMDoc/MMT](http://uniformal.github.io).
+
+Materials:
+
+* [KRMT on StudOn](https://www.studon.fau.de/crs4499012.html)
+* [Course on zoom](Https://fau.zoom.us/j/65839665250)
+* [Videos on FAU.tv](Https://www.fau.tv/course/id/3065)
+* [Course Notes, Resources](http://kwarc.info/teaching/KRMT)
+* [Formalization Tutorialz](https://gl.mathhub.info/Tutorials/Mathematicians/blob/master/tutorial/mmt-math-tutorial.pdf)
+* [Formalizations of the last years](https://gl.mathhub.info/Teaching/KRMT/tree/master/source)
+ 

courses/ai.md

+---
+layout: course
+
+title: Artificial Intelligence
+instructors:
+    - mkohlhase
+
+organization: Jacobs University
+semesters:
+    - Spring05
+---
+
+An intro course on AI following Russell/Norvig

courses/ai1.md

+---
+layout: course
+
+title: Artificial Intelligence I
+instructors:
+    - mkohlhase
+
+semesters:
+    - WS16/17
+    - WS17/18
+    - WS18/19
+    - WS19/20 
+    - WS20/21 
+    - WS21/22 
+    - WS22/23 
+    - WS23/24
+    - WS24/25 
+---
+
+This course is the first part of a two-semester introduction into the field of Artificial
+Intelligence (AI). It introduces the foundations of symbolic AI, in particular: 
+
+* Agent Models as foundation of AI
+* Logic Programming in Prolog
+* Heuristic Search as a methdod for problem solving
+* Adversarial Search (automating board games) via heuristic search
+* Constraint Propagation
+* Logical Languages for knowledge representation
+* Inference and automated theorem proving
+* Classical Planning
+* Planning and Acting in the real world. 
+
+The course follows the book
+[Artificial Intelligence: A Modern Approach](https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-3rd-Edition/PGM156683.html)
+by Stuart Russell und Peter Norvig. We use the third edition. 
+
+The course materials (e.g. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) or
+[Assignments](http://kwarc.info/teaching/AI/assignments.pdf), but also old exams and
+(some) solutions) are [here](http://kwarc.info/teaching/AI/). 
+
+The course forum on [StudOn](https://studon.fau.de) is an important source for advice and
+discussions. The instrutor and tutors try to be present to help. 
+
+### German Version (possibly out of date)
+
+Diese Vorlesung ist der erste Teil einer zwei-semestrigen Einführung in die Künstlichen
+Intelligenz (KI). Sie beschäftigt sich mit den Grundlagen der symbolischen KI,
+insbesondere
+
+* Agentenmodelle als  Grundlagen der KI
+* Logisches Programmieren in Prolog
+* Heuristische Suche als Methode zum Problemlösen
+* Adversarielle Suche (Strategiespiele)
+* Probleme unter Rand- oder Nebenbedingungen (Constraint Propagation)
+* Logische Sprachen zur Wissensrepräsentation,
+* Inferenz und Logisches Programmieren
+* Klassisches Planen
+* Planen und Agieren in der realen Welt
+
+Die Vorlesung folgt dem Buch
+[Artificial Intelligence: A Modern Approach](https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-3rd-Edition/PGM156683.html)
+von Stuart Russell und Peter Norvig. Wir verwenden die dritte Ausgabe.
+
+Die Kursmaterialien (z.B. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) oder
+[Aufgaben](http://kwarc.info/teaching/AI/assignments.pdf), aber auch alte Klausuren)
+finden sich in [hier](http://kwarc.info/teaching/AI/). 
+
+Diskussionen finden auf dem
+[StudOn](https://studon.fau.de) statt. Dies ist
+eine wichtige Quelle von Rat und Tat. Wir bemühen uns, auf dem Forum präsent zu sein, und
+schnell auf Fragen zu antworten. Also das Forum abonnieren! 

courses/ai2.md

+---
+layout: course
+
+title: Artificial Intelligence II
+instructors:
+    - mkohlhase
+
+semesters:
+    - SS17 
+    - SS18 
+    - SS19 
+    - SS20 
+    - SS21 
+    - SS22 
+    - SS23 
+    - SS24 
+---
+
+This course is the second part of a two-semester introduction into the field of Artificial
+Intelligence (AI). It introducers the foundations of inference under uncertainty, machine
+learning and language understanding. The course builds on and continues the course 
+[Artificial Intelligence I](/courses/ai1/) from the winter semester. In particular, the course 
+covers
+
+* Inference under Uncertainty
+* Bayesian Networks
+* Rational Decision Theory (MDPs and POMDPs)
+* Machine Learning and Neural Networks
+* Natural Language Processing
+
+The course follows the book
+[Artificial Intelligence: A Modern Approach](https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-3rd-Edition/PGM156683.html)
+by Stuart Russell und Peter Norvig. We use the third edition. 
+
+The course materials (e.g. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) or
+[Assignments](http://kwarc.info/teaching/AI/assignments.pdf), but also old exams and
+(some) solutions) are [here](http://kwarc.info/teaching/AI/). 
+
+The course forum on [StudOn](https://studon.fau.de) is an important source for advice and
+discussions. The instrutor and tutors try to be present to help. 
+
+### German Version (possibly out of date)
+
+Diese Vorlesung ist der zweite Teil einer zwei-semestrigen Einführung in die Künstlichen
+Intelligenz (KI). Sie beschäftigt sich mit den Grundlagen des Schliessens unter
+Unsicherheit, des maschinellen Lernens und des Sprachverstehens.  Der Kurs baut auf der
+[Vorlesung Künstliche Intelligenz I](/courses/ai1/) vom Wintersemester auf und führt diese
+weiter. Wir behandeln insbesondere
+
+* Schliessen unter Unsicherheit
+* Bayessche Netzwerke
+* Theorie der Rationalen Entscheidungen
+* Maschinelles Lernen
+* Sprachverstehen (wenn die Zeit reicht)
+
+Die Vorlesung folgt dem Buch
+[Artificial Intelligence: A Modern Approach](https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-3rd-Edition/PGM156683.html)
+von Stuart Russell und Peter Norvig. Wir verwenden die dritte Ausgabe.
+
+Die Kursmaterialien (z.B. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) oder
+[Aufgaben](http://kwarc.info/teaching/AI/assignments.pdf), aber auch alte Klausuren)
+finden sich in [hier](http://kwarc.info/teaching/AI/). 
+
+Diskussionen finden auf dem
+[FSI Forum KI-I](https://fsi.cs.fau.de/forum/149-Kuenstliche-Intelligenz-II) statt. Dies ist
+eine wichtige Quelle von Rat und Tat. Wir bemühen uns, auf dem Forum präsent zu sein, und
+schnell auf Fragen zu antworten. Also das Forum abonnieren! 

courses/aisysproj.md

+---
+layout: course
+
+title: AI 1/2 Systems Project
+instructors:
+    - mkohlhase
+    - jfschaefer
+semesters:
+    - WS21/22 
+    - WS22/23 
+    - WS23/24 
+    - WS24/25 
+    - SS22
+    - SS23
+    - SS24
+    - SS25
+    - SS26
+---
+
+
+##### AI-1 and AI-2 systems project
+The AI systems projects are designed to provide hands-on experience for the topics covered in the AI lectures.
+The AI-1 Systems Project focuses on the symbolic methods discussed in the [AI-1 lecture](https://kwarc.info/courses/ai1/) (search, SAT solving, semantic web, planning, ...)
+and the AI-2 Systems Project focuses on the subsymbolic methods covered by the [AI-2 lecture](https://kwarc.info/courses/ai2/) (Bayesian networks, (hidden) markov problems, machine learning, ...).
+Each AI systems project is worth 10 ECTS.
+Generally, you can pick whichever project sounds more interesting to you/is more relevant for your studies.
+If you need two projects, you can also take both, but you cannot start both at the same time.
+
+**Requirements:** There are no formal requirements, but we strongly recommend
+that you either have taken the AI lecture or will take it in parallel.
+Furthermore, you should have substantial programming experience (the programming language is not important) because you will have to program a lot.
+In particular, the AI systems project is not a programming course, i.e. we expect that you are already proficient.
+
+##### What happens in the project?
+The project will consist of several large problems (≈6), which you will work on individually or in small teams.
+Each problem will require a substantial amount of programming work - after all the project is worth 10 ECTS.
+You can take a look at the [problems from the previous iterations](https://kwarc.info/teaching/AISysProj/) to get a first impression.
+The first problem is a warm-up problem, which you have to solve alone, so that you can judge whether the project works for you.
+The remaining problems are intended to be solved in teams of size 2.
+Furthermore, you will have to write a report on one of the problems and have a small presentation (or rather, a section of a presentation together with other people).
+The details will be discussed in the admin meeting.
+
+
+##### Sign-up
+You can sign up for the AI systems project via [StudOn](https://www.studon.fau.de/crs6243066.html)
+(sign-up is independent of whether you are interested in the AI-1 or AI-2 systems project).
+You will probably be placed on a waiting list (this is normal; demand is high). We first accept people from the waiting list of the previous semester, so the course may already be fuller than indicated.
+However, we will regularly accept new people throughtout the semester,
+whenever students have finished or dropped out.
+The project is designed in a way that you can join at any point, including in the middle of the semester.
+In that case your project would simply continue for a while after the semester ends.
+
+**Important: Make sure to regularly check if you have been admitted (you should also get an email notification).
+If you miss some of the early deadlines, we assume that you are not interested in the project and will remove you to give other students a chance.**
+
+
+##### Timeline
+The project timeline is quite flexible:
+
+* You can request to join the project at any time, and at regular intervals we will admit new people (the capacity is limited, so you might have to wait).
+* Once we have admitted you, we will have an admin meeting, in which we will discuss more details about the project.
+    Check the StudOn forum for information on the time of the next admin meeting.
+    Afterwards, you should follow the onboarding guide (posted on StudOn).
+    You can still drop the project later on.
+* Then you can get started with the warm-up problem.
+    The warm-up problem has to be solved individually and is a requirement to take the project.
+    It is also an opportunity for you to see if the project works for you. You can still decide to drop the project after starting the warm-up problem.
+* Once you have solved the warm-up problem, you can sign up to solve the other ≈5 problems. These are intended to be solved in teams of size two,
+    but currently we also allow teams of size one (that might change at any point though).
+    Each problem is offered once a semester. It's up to you if you want to do all of them in one semester or e.g. spread it over two semesters.
+* You will have to give a presentation on one of the problems. We will use some sort of sign-up process for that as well.
+* You will have to write a report on one of the problems (can be the one you present). Furthermore, we will simulate double-blind peer review,
+    which means that you will have to write 3 anonymous reviews for other students' reports.
+
+**Important:**
+You will have to take initiative to finish the project.
+That means actively following the announcements (e.g. about new problems or available presentation slots), making sure that you sign up for problems and reach out if you need anything.
+Simply joining the StudOn course is not enough.
+**As the number of spaces in the project is limited, we will remove students from the project who do not finish the on-boarding procedure in time or who do not submit a preliminary solution to the warm-up problem on time.**
+If you have been removed, you can join the waiting list again.
+
+
+##### It's different from "Projekt zur Künstlichen Intelligenz"
+You might also find references to "Projekt zur Künstlichen Intelligenz (P KI)".
+Despite the similar names, they are very different:
+The systems project (as described on this page) is organized more like a course, parallel to the AI lecture,
+and every student will work on the same set of problems.
+"P KI", on the other hand, is an individual research project with the kwarc group.
+In the AI Master you need two projects, so you could even take both (then taking the systems project first is probably a good idea).
+
+
+##### Contact
+If you have any questions, feel free to send an email to `"jan frederik schaefer".replace(' ', '.') + "@fau.de"`.
+Note that sending an email will not get you accepted into the project faster.
+You can also join [our public AISysProj matrix room](https://matrix.to/#/#aisysproj-non-members:fau.de).
+Matrix is a communications platform that is supported by FAU. We will use it to communicate during the AI systems project.
+You can find instructions for joining Matrix at FAU [here](https://www.anleitungen.rrze.fau.de/serverdienste/matrix-an-der-fau/erste-schritte/) (only in German, unfortunately).
+

courses/complog.md

+---
+layout: course
+
+title: Computational Logic
+instructors:
+    - mkohlhase
+    - frabe
+    - dmueller
+    
+organization: Jacobs University
+semesters:
+    - Fall05
+    - Fall07
+    - Fall09
+    - Fall11
+    - Fall13
+    - Fall15
+---
+Theory and machine-oriented inference for propositional, first-order, higher-order, modal,
+and description logics. 
+
+The course resources (course notes, literature, assignments) can be found [here](http://kwarc.info/teaching/CompLog).

courses/comsem.md

+---
+layout: course
+
+title: Computational Natural Language Semantics
+instructors:
+    - mkohlhase
+    
+organization: Jacobs University
+semesters:
+    - Fall06
+    - Fall08
+    - Fall10
+    - Fall12
+    - Spring14
+    - Spring15
+---
+
+This course introduces logic-based methods for computing and representing for the semantics of natural language. We use Montague's "method of fragments" to create a series of language models of increasing coverage (of English).
+
+A **language model** is a triple of
+
+* a grammar *G* that defines a language fragment that can be translated,
+* a logical system *L* that acts as the meaning representation, and 
+* a translation from syntax trees induced by *G* to formulae in *L*.
+
+The course resources (course notes, literature, assignments) can be found [here](http://kwarc.info/teaching/ComSem).
+
+Having heard the course ["Computational Logic](http://kwarc.info/teaching/CompLog)" is very helpful, but not a prerequisite.
+ 

courses/dbwa.md

+---
+layout: course
+
+title: Data Bases and Web Applications
+instructors:
+    - mkohlhase
+
+organization: Jacobs University
+semesters:
+    - Spring05
+---
+
+An intro course on data bases and web applications.

courses/dynamics.md

+---
+layout: course
+
+title: Representing Dynamics and Dynamic Representation 
+instructors:
+    - mkohlhase
+    - Herber Jaeger, Jacobs University
+
+organization: Jacobs University
+semesters:
+    - Spring05
+---
+
+An intro course on AI following Russell/Norvig

courses/gencs.md

+---
+layout: course
+
+title: General Computer Science
+instructors:
+    - mkohlhase
+
+organization: Jacobs University
+semesters:
+    - Fall15 
+    - Fall16 
+---
+
+General Computer Science I is the first semester, introductory course taught at Jacobs University. Starting the Fall Semester 2015 (when GenCS II was dropped). It is really still the same as GenCS I. 

courses/gencs1.md

+---
+layout: course
+
+title: General Computer Science I
+instructors:
+    - mkohlhase
+
+organization: Jacobs University
+semesters:
+    - Fall03
+    - Fall04
+    - Fall05
+    - Fall06
+    - Fall07
+    - Fall08
+    - Fall09
+    - Fall10
+    - Fall11
+    - Fall12
+    - Fall13 
+    - Fall14 
+---
+
+General Computer Science I is the first semester, introductory course taught at Jacobs University. It focuses on representation issues for objects, and uses SML as an programming language to equalize over a diverse student body. 

courses/gencs2.md

+---
+layout: course
+
+title: General Computer Science II
+instructors:
+    - mkohlhase
+
+organization: Jacobs University
+semesters:
+    - Spring04
+    - Spring05
+    - Spring06
+    - Spring07
+    - Spring08
+    - Spring09
+    - Spring010
+    - Spring011
+    - Spring012
+    - Spring013 
+    - Spring014 
+---
+
+General Computer Science II is the second semester, introductory course taught at Jacobs University.  It focuses on abstract computation (machine models), search, and declarative programming. It still uses SML as a programming language.