@misc{DuckhornHuberMeyeretal., author = {Duckhorn, Frank and Huber, Markus and Meyer, Werner and Jokisch, Oliver and Tsch{\"o}pe, Constanze and Wolff, Matthias}, title = {Towards an Autarkic Embedded Cognitive User Interface}, series = {Proceedings Interspeech 2017, 20-24 August 2017, Stockholm}, journal = {Proceedings Interspeech 2017, 20-24 August 2017, Stockholm}, editor = {Lacerda, Francisco}, publisher = {ISCA}, doi = {10.21437/Interspeech.2017}, pages = {3435 -- 3436}, abstract = {ucuikt2015}, language = {en} } @misc{RoemerHuberLieblWolff, author = {R{\"o}mer, Ronald and Huber-Liebl, Markus and Wolff, Matthias}, title = {Quantum-inspired representation and querying of semiotic object properties by cognitive agents}, series = {2025 IEEE 16th International Conference on Cognitive Infocommunications (CogInfoCom)}, journal = {2025 IEEE 16th International Conference on Cognitive Infocommunications (CogInfoCom)}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {979-8-3503-5691-5}, doi = {10.1109/CogInfoCom66819.2025.11200567}, pages = {000129 -- 000134}, abstract = {Advanced intelligence often relies on the ability to build and use models. They allow the representation of knowledge, enable predictions, and serve to plan goal-directed actions. However, the successfull use of models requires a certain level of competence in interacting with models. This competence can be acquired by exploiting the separation of the cognitive agent from the objects represented in the model; because it allows the differentiation of individual semiotic levels. This includes the separation of self-sufficient and non self-sufficient object attributes. Non self-sufficient attributes that the agent assigned to potential target objects during the exploration phase form the starting point for the information requirement regarding the self-sufficient attributes of these objects. These attributes are required for target selection and the subsequent alignment of the model-based planning. This process is characterized by a series of queries to the environment model and thus shows a certain similarity to information retrieval (IR). Therefore, in this work we particularly investigate quantum-inspired IR-methods for representation and querying. We demonstrate that they are suitable for modelling cognitive effort and behavior, as they represent a realistic and universally applicable descriptive tool.}, language = {en} } @misc{HuberLieblRosenowRoemeretal., author = {Huber-Liebl, Markus and Rosenow, Tillmann and R{\"o}mer, Ronald and Wirsching, G{\"u}nther and Wolff, Matthias}, title = {Knowledge representation and querying with tensors for a class of practical test problems}, series = {Refereed Paper Proceedings - KM Conference 2025 - Siena, Italy}, journal = {Refereed Paper Proceedings - KM Conference 2025 - Siena, Italy}, publisher = {International Institute for Applied Knowledge Management}, pages = {111 -- 123}, abstract = {We further promote the idea of quantum inspiration and propose to equip cognitive systems not only with tensors for data representation but also for operation representation and querying. We discuss ideas from information retrieval and translate them into our method of behavioral control. We formalize the method with tensor algebra and discuss its extensions to learning. At the example of the problem of 𝑁-dimensional aiming, we visualize the transfer of our stated theoretical foundation to a class of practical test problems.}, language = {en} }