After successful completion of the course, students are able to

• explain the fundamental concepts of formal argumentation
• apply the methodology of formal argumentation to select reserach topics
• apply established methods from the field of knowledge representation to a new formalism
• contribute to scientific research within a team of experts

+ lecture part:
    - Dungs Abstract Argumentation Frameworks
    - Semantics for abstract argumentation
    - Properties and Complexity of argumentation
    - Algorithms and ASP / (Q)SAT Encodings
    - Recent developments in abstract argumentation

+ practical part:
    - Application of the concepts and techniques presented in the lecture

The course consists of both a lecture part, where the appropriate concepts will be presented, and a practical part.
In the latter, students (in cooperation with a lecturer) are supposed to work
out some theoretical results OR / AND  breaking down such results to practice by respective implementations.

Hybridmodus im WS 2021: 
The kick-off meeting will be held be online via zoom. Lectures are planed to  be on-site. If that is not possible/feasible we will ZOOM meetings for the lecture part. The meetings for the individual projects can be online or on-site (up to the student and project-supervisor).

ECTS breakdown: 4.5 ECTS = 112.5 Hours

0.5h Kick-Off meeting

18h Lectures incl. final discussions

19h Exercises

75h Project

Elaboration of the practical part & exam at the end of the course.

The course adresses advanced students in knowledge representation. There are no formal prerequisites for this course. However, students will profit from preknowledge in the following subjects.

1. Basic complexity theory: Knowledge of the fundamental concepts of complexity theory, e.g.: complexity classes; reductions; classes P and NP;
   
   If you successfully completed one of the following courses you probably have these skills.
   185.291 4.0 VU Formal Methods in Computer Science,
   181.142 2.0 VU Complexity Theory,
   184.215 2.0 VU Complexity Analysis
   
   
2. SAT-Solving OR Answer Set Programming (ASP): Ability to formalize a combinatorial problem in SAT or ASP and solve it with state-of-the-art systems.
   
   If you successfully completed one of the following courses you probably have these skills:
   184.090 2.0 VU SAT Solving,
   184.143 2.0 VL Logic-oriented Programming,
   184.176 1.0 LU Introduction to Knowledge-based Systems