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Qualitative Simulation abstracts from numerical details and captures the behavior of a system in terms of broad intervals or relations. The underlying symbolic models such as Qualitative Differential Equations or Qualitative Causal Models double as a representation for why a certain simulation outcome occurred. A long standing issue in common sense reasoning in AI is […]
Inductive Logic Programming (ILP) is a form of symbolic machine learning, where logic programs (e.g., Prolog or ASP) are synthesized from input/output examples. These synthesis tasks are notorious for their large search space. Modern approaches use a conflict-driven search to constrain this search iteratively. This procedure is usually implemented using constraint programming solvers operating on […]
A Master’s thesis is to be implemented within the context of the Open KI IoT Hub project. The project focuses on an open platform for utilizing Schleswig-Holstein’s unique, state-wide LoRaWAN network. The platform aims to enable users to integrate LoRaWAN-capable sensors, connect them to the state-wide network, and collect, visualize, and perform AI-supported analyses on […]
In der Vorlesung Robotik wird der Open-Source-Roboterarm “LeRobot” von HuggingFace verwendet – mit recht gutem Erfolg. Ein paar Probleme hat dieser Roboter aber leider noch: er verfügt nur über 5 Gelenke + einen Greifer. Dadurch sind die räumlichen Freiheiten des Roboters nicht vollständig, die letzte rotatorische Freiheit fehlt. Zudem ist die Implementierung der Gelenkbewegung nicht […]
Future Internet architectures such as Named Data Networking (NDN) rely heavily on in-network caching to improve performance and reduce latency, an especially valuable feature for resource-constrained IoT environments. However, current IoT-NDN deployments lack mechanisms to securely control how caches are manipulated. Unauthorized insertions, evictions, or modifications of cached data can lead to cache poisoning, cache […]