Knowledge Representation and Reasoning

Welcome to the group headed by Johannes (P.) Wallner, specializing on Knowledge Representation & Reasoning (KRR).

If you are interested in student topics (e.g., for a Bachelor's or Master's thesis) you can have look at the topics page. A Bachelor's or Master's thesis can be started anytime (contact).

Broadly construed, knowledge representation & reasoning in Artificial Intelligence is concerned with foundational research questions such as how to represent knowledge and how to reason based on knowledge. Our research and teaching focuses on

  • formal studies of prominent logic-based representations of knowledge, and
  • addressing challenging computational reasoning tasks arising in KRR.

Our research agenda is to further understanding of complex forms of reasoning in knowledge representation, and to bring promising approaches closer to application, by going from theory to practice.

One of our main current areas is computational argumentation. For a general introduction to the topic, you can have a look, e.g., at the Handbook of Formal Argumentation or this article

** News **: we are organizing the next ICCMA in 2025.

** New course **: Logic-based Knowledge Representation (winter term).

Below you find recent news (news archive).

Recent News


Habilitation Talk by Wallner

06.12.2024

During the 20 year celebration of the Faculty of Computer Science and Biomedical Engineering (CSBME), Wallner gave a presentation of his habilitation work ("HabilTalk"). The topic was on several computational aspects in the field of argumentation in Artificial Intelligence. We thank the faculty for organizing this pleasant event!


Paper accepted to SAC

6.12.2024

Our work on "Dynamic Programming Algorithms for Probabilistic Bipolar Argumentation Frameworks" was accepted to SAC (Symposium On Applied Computing) in the Track on Knowledge Representation and Reasoning (KRR). We extend our previous works on probabilistic argumentation frameworks to the case of having supporting relations, instead of only attack relations, between arguments. We develop dynamic programming algorithms utilizing tree decompositions for challenging computational tasks that arise in such frameworks.


International Competitions on Computational Models of Argumentation (ICCMA)

29.10.2024

Our group organizes the next edition of the International Competitions on Computational Models of Argumentation (ICCMA) in 2025. Call for solvers and benchmarks can be found here. The aim of the competition is to further development of solvers for (hard) reasoning tasks in computational argumentation.


Paper accepted to LPNMR

5.9.2024

Our work "A Semantical Approach to Abstraction in Answer Set Programming and Assumption-based Argumentation" was accepted to this year's edition of LPNMR. Following the theme of the conference, non-monotonic reasoning and logic programming, we investigate forms of abstractions on logic programs under the answer set semantics and on the related assumption-based argumentation formalism.


Invitation to Early Career Track at IJCAI 2024

15.07.2024

At IJCAI 2024, Wallner will present recent works on the topic of "Computational Argumentation: Reasoning, Dynamics, and Supporting Explainability" in the Early Career track of the conference, which is a by invitation only track. In this talk, an overview of recent advances of algorithmic approaches to argumentative reasoning including static and dynamic forms is given, and ways of supporting explainability are discussed.


Three papers accepted to KR 2024

11.07.2024

In this year's edition of the International Conference on Principles of Knowledge Representation and Reasoning (KR'24), three of our works got accepted:

  • Complexity Results and Algorithms for Preferential Argumentative Reasoning in ASPIC+
  • Abstraction in Assumption-based Argumentation
  • Advancing Algorithmic Approaches to Probabilistic Argumentation under the Constellation Approach

In the first work, we extend computational approaches to the prominent structured argumentation formalism of ASPIC+, in particular incorporating also preferential argumentative reasoning. In the second work we deal with abstracting information to attain a high-level view aimed at supporting explainability. In the third work we studied alorithmic approaches to the highly complex field of probabilistic reasoning in formal argumentation.