XLoKR 2024
The Fifth Workshop on Explainable Logic-Based Knowledge Representation
Sponsored by the Argumentation-based Deep Interactive EXplanations project under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 101020934) and the Transregional Collaborative Research Centre 248 “Foundations of Perspicuous Software Systems” (CPEC – TRR 248).
About
XLoKR 2024 is the fifth workshop in the XLoKR series. It will be co-located with the 21st International Conference on Principles of Knowledge Representation and Reasoning, which will take place in Hanoi, Vietnam. Previous editions of XLoKR took place in
2020 co-located with the 17th International Conference on Principles of Knowledge Representation and Reasoning,
2021 co-located with the 18th International Conference on Principles of Knowledge Representation and Reasoning,
2022 co-located with the 19th International Conference on Principles of Knowledge Representation and Reasoning and
2023 co-located with the 20th International Conference on Principles of Knowledge Representation and Reasoning.
Motivation and Topic
Embedded or cyber-physical systems that interact autonomously with the real world, or with users they are supposed to support, must continuously make decisions based on sensor data, user input, knowledge they have acquired during runtime as well as knowledge provided during design-time. To make the behavior of such systems comprehensible, they need to be able to explain their decisions to the user or, after something has gone wrong, to an accident investigator.
While systems that use Machine Learning (ML) to interpret sensor data are very fast and usually quite accurate, their decisions are notoriously hard to explain, though huge efforts are currently being made to overcome this problem. In contrast, decisions made by reasoning about symbolically represented knowledge are in principle easy to explain. For example, if the knowledge is represented in (some fragment of) first-order logic, and a decision is made based on the result of a first-order reasoning process, then one can in principle use a formal proof in an appropriate calculus to explain a positive reasoning result, and a counter-model to explain a negative one. In practice, however, things are not so easy also in the symbolic KR setting. For example, proofs and counter-models may be very large, and thus it may be hard to comprehend why they demonstrate a positive or negative reasoning result, in particular for users that are not experts in logic. Thus, to leverage explainability as an advantage of symbolic KR over ML-based approaches, one needs to ensure that explanations can really be given in a way that is comprehensible to different classes of users (from knowledge engineers to laypersons).
The problem of explaining why a consequence does or does not follow from a given set of axioms has been considered for full first-order theorem proving since at least 40 years, but there usually with mathematicians as users in mind. In knowledge representation and reasoning, efforts in this direction are more recent, and were usually restricted to sub-areas of KR such as AI planning and description logics. The purpose of this workshop is to bring together researchers from different sub-areas of KR and automated deduction that are working on explainability in their respective fields, with the goal of exchanging experiences and approaches. A non-exhaustive list of areas to be covered by the workshop are the following:
AI planning
Answer set programming
Argumentation frameworks
Automated reasoning
Description logics
Non-monotonic reasoning
Probabilistic representation and reasoning
Important Dates
Paper Submission: July 17 July 28 (Extended Deadline), 2024
Notification: August 21, 2024
Camera-ready papers: October 1, 2024
November 2-4 (exact date TBA), 2024
Submission Guidelines
We invite extended abstracts of 2-5 pages (excluding references) on topics related to explanation in logic-based KR. The papers should be formatted in Springer LNCS Style and must be submitted via
Since the workshop will only have informal proceedings and the main purpose is to exchange results, we welcome not only papers covering unpublished results, but also previous publications that fall within the scope of the workshop. To avoid conflicts with previous/future publications, we will not have formal proceedings, but will make the papers available on the website.
Organization
Organization Committee
Franz Baader, TU Dresden
Bart Bogaerts, Vrije Universiteit Brussel
Jörg Hoffmann, Saarland University
Thomas Lukasiewicz, University of Oxford
Nico Potyka, Cardiff University
Francesca Toni, Imperial College London
Program Committee
Hamed Ayoobi, Imperial College London
Franz Baader, TU Dresden
Sander Beckers, University of Tübingen
Bart Bogaerts, Vrije Universiteit Brussel (VUB)
Alex Borgida, Rutgers University
Stefan Borgwardt, TU Dresden
Gerhard Brewka, Leipzig University
Roberta Calegari, Università di Bologna
Ruth Hoffmann, University of St Andrews
Joerg Hoffmann, Saarland University
Francesco Leofante, Imperial College London
Thomas Lukasiewicz, University of Oxford
Pierre Marquis, CRIL, U. Artois & CNRS
Cristian Molinaro, Università della Calabria
Guilherme Paulino-Passos, Imperial College London
Rafael Peñaloza, University of Milano-Bicocca
Nico Potyka, Cardiff University
Antonio Rago, Imperial College London
Francesco Ricca, University of Calabria
Tjitze Rienstra, Maastricht University
Stefan Schlobach, Vrije Universiteit Amsterdam
Matthias Thimm, FernUniversität in Hagen
Francesca Toni, Imperial College London
Contact
For organizational questions, please contact Nico Potyka.