“Learning from Learners” (“Von Lernenden Lernen”, “VoLL-KI ” for short) is a is collaborative research project with the goal of creating a practical toolbox of instruments at different levels of abstraction to improve the learning experience and …

CLKR (Conditional Logic and Knowledge Representation) is an online repository of conditional logic resources for knowledge representation and reasoning. The question which entailments should follow from a conditional knowledge base consisting of a …

Path planning and motion control of mobile robots are highly dependent on the map representation. Planners and controllers can solve both simple 2D navigation indoors and complex navigation in rough outdoor terrain with multiple levels and varying …

This dissertation abstract summarizes results of the thesis “Comprehensible Knowledge Base Extraction for Learning Agents - Practical Challenges and Applications in Games” (accepted as dissertation at the Department of Computer Science of TU …

Failure mode and effects analysis (FMEA) is a systematic approach to identify and analyse potential failures and their effects in a system or process. The FMEA approach, however, requires domain experts to manually analyse the FMEA model to derive …

In recent years, agriculture has become a major field of application and transfer for AI. The paper gives an overview of the topic, focusing agricultural processes and technology in Central-European style arable farming. AI could also be part of …

KI: Trying to generalize that for the readership of the KI Journal, it is of course interesting which AI and robotics technologies are relevant for this area. Obviously, sensor data interpretation is. You said, for the phenotyping application …

Reinforcement learning (RL) is a powerful tool for teaching agents goal-directed behaviour in stochastic environments, and many proposed applications involve adopting societal roles which have ethical, legal, or social norms attached to them.

Interactions between logic and theoretical computer science are multiple and profound. In the last decades, they have been deeply investigated, but, surprisingly, the study of probabilistic computation was only marginally touched by such fruitful …

In this special issue we provide a collection of recent developments and applications of AI in current and future agriculture, which also serves as an entry point for further research. We start with an introductory overview and an interview with …

With this article, the two authors would like to pay tribute to the memory of their dear friend and colleague Steffen Hölldobler, who left us far too early in 2023. Ulrich (UF), in his time as a postdoc at the University of the Bundeswehr Munich …

This is a report on the project “Axiomatizing Conditional Normative Reasoning” (ANCoR, M 3240-N) funded by the Austrian Science Fund (FWF). The project aims to deepen our understanding of conditional normative reasoning by providing an axiomatic …

Today, the number of applications and tasks that use AI is rapidly growing. It is used where the task is too difficult to solve for a human or requires a lot of manual work. While AI algorithms are black boxes most of the time, the success of an …

Ulcerative Colitis (UC) is a chronic inflammatory bowel disease decreasing life quality through symptoms such as bloody diarrhoea and abdominal pain. Endoscopy is a cornerstone of diagnosis and monitoring of UC. The Mayo endoscopic subscore (MES) …

To date, there is no universal explanatory method for making decisions of an AI-based system transparent to human decision makers. This is because, depending on the application domain, data modality, and classification model, the requirements for …

Several researchers have focused in recent years on improving the efficiency of abdominal diagnostics by segmenting colonoscopy images with machine learning techniques. Previously, colonoscopy images were manually segmented by experts in this …

We report on recent successes in the application of computational methods and automated reasoning techniques to a foundational theory of metaphysics: in [ 13 ], we utilize and extend the method of shallow semantic embeddings (SSEs) in classical …

This paper summarises several contributions to the theory of belief change by the authors’ dissertation thesis. First, a relational characterization of belief revision for Tarskian logics is considered, encompassing first-order predicate logic …

Personalized medicine seeks to identify the right treatment for the right patient at the right time. Predicting the treatment effect for an individual patient has the potential to transform treatment of patients and drastically improve patients …