TY - RPRT A1 - Huber, Markus A1 - Klimczak, Peter T1 - Nix g'sagt is' g'lobt g'nua : Kybernetisches Lehren und Lernen mit Petri-Netzen N2 - In diesem Text wird das in „Maschinensemiotik“ [12] vorgestellte Verfahren zur Verknüpfung von Äußerungen mit deren Bedeutung weiterentwickelt und in Form von Algebraischen Petri-Netzen [20] modelliert. Gleichzeitig wird der Formalismus der Petri-Netze nebenbei eingeführt, wobei die Vorstellung nicht auf formale Vollständigkeit abzielt, sondern nur das für die Anwendung nötige Wissen Erwähnung findet. Die Modellierung umfasst dabei sowohl die Systemkomponente, die Verknüpfungen zwischen sprachlichen Äußerungen und Handlungen herstellt – das Lernermodell –, als auch die Komponente, die sprachliche Äußerungen tätigt, bis die gewünschte Verknüpfung hergestellt wurde – das Lehrermodell samt Lernzielkontrolle. Die Umsetzung des Modells per Software [19] erlaubt die weitere Diskussion anhand einer Simulation mit einigen Testdaten. Eine ausführliche mathematische Analyse zeigt beweisbare Eigenschaften des Modells auf. Knappe Vergleiche mit der kybernetischen Didaktik nach von Cube [26] sowie der Suggestopädie Lozanovs [16] ordnen das Modell darüber hinaus noch in einen pädagogischen Kontext ein. Y1 - 2020 U6 - https://doi.org/10.13140/RG.2.2.12056.83209 ER - TY - GEN A1 - Römer, Ronald A1 - beim Graben, Peter A1 - Huber-Liebl, Markus A1 - Wolff, Matthias T1 - Unifying Physical Interaction, Linguistic Communication, and Language Acquisition of Cognitive Agents by Minimalist Grammars T2 - Frontiers in Computer Science N2 - Cognitive agents that act independently and solve problems in their environment on behalf of a user are referred to as autonomous. In order to increase the degree of autonomy, advanced cognitive architectures also contain higher-level psychological modules with which needs and motives of the agent are also taken into account and with which the behavior of the agent can be controlled. Regardless of the level of autonomy, successful behavior is based on interacting with the environment and being able to communicate with other agents or users. The agent can use these skills to learn a truthful knowledge model of the environment and thus predict the consequences of its own actions. For this purpose, the symbolic information received during the interaction and communication must be converted into representational data structures so that they can be stored in the knowledge model, processed logically and retrieved from there. Here, we firstly outline a grammar-based transformation mechanism that unifies the description of physical interaction and linguistic communication and on which the language acquisition is based. Specifically, we use minimalist grammar (MG) for this aim, which is a recent computational implementation of generative linguistics. In order to develop proper cognitive information and communication technologies, we are using utterance meaning transducers (UMT) that are based on semantic parsers and a mental lexicon, comprising syntactic and semantic features of the language under consideration. This lexicon must be acquired by a cognitive agent during interaction with its users. To this aim we outline a reinforcement learning algorithm for the acquisition of syntax and semantics of English utterances. English declarative sentences are presented to the agent by a teacher in form of utterance meaning pairs (UMP) where the meanings are encoded as formulas of predicate logic. Since MG codifies universal linguistic competence through inference rules, thereby separating innate linguistic knowledge from the contingently acquired lexicon, our approach unifies generative grammar and reinforcement learning, hence potentially resolving the still pending Chomsky-Skinner controversy. btuktuminglear, btuktsptech, btuktcogsys Y1 - 2022 UR - https://www.frontiersin.org/article/10.3389/fcomp.2022.733596 U6 - https://doi.org/10.3389/fcomp.2022.733596 SN - 2624-9898 IS - 4 ER - TY - GEN A1 - Meyer, Werner A1 - Borislavov, Borislav A1 - Eckert, Friedrich A1 - Richter, Christian A1 - Römer, Ronald A1 - Beim Graben, Peter A1 - Huber, Markus A1 - Wolff, Matthias ED - Hillmann, Stefan ED - Weiss, Benjamin ED - Michael, Thilo ED - Möller, Sebastian T1 - Formalisierung und Implementierung einer adaptiven kognitiven Architektur unter Verwendung von Strukturdiagrammen T2 - Elektronische Sprachsignalverarbeitung 2021 : Tagungsband der 32. Konferenz Berlin, 3.-5. März 2021 N2 - Das Fachgebiet der Kognitiven Technischen Systeme zeichnet sich durch einen hohen Grad an Interdisziplinarität (z. B. Kenntnisse auf den Gebieten Biologie, Psychologie, Informatik und den Ingenieurwissenschaften) aus. Nach wie vor besteht Bedarf an einer methodischen Darstellung des Fachgebietes, bei der die theoretische Durchdringung von Zusammenhängen zwischen den verschiedenen Wissensgebieten zusätzlich durch Anschaulichkeit unterstützt wird. Die vorliegende Arbeit stellt einen Fortschrittsbericht zur Realisierung eines Forschungs- und Experimentiersystems dar, mit dem wir dieses Anliegen unterstützen und über das wir erstmals konzeptionell in [1] berichtet haben. In diesem Beitrag folgen wir einem integrativen Ansatz zur Entwicklung einer kognitiven Architektur, mit der unter Verwendung repräsentationaler Datenstrukturen adaptives Verhalten auf verschiedenen Zeitskalen sowie zwei wichtige Verhaltensprogramme für das Problemlösen (Objektfindung, Exploration) auf der gemeinsamen Grundlage von Markov-Entscheidungsprozessen umgesetzt werden. Mit einem Kurzbericht zum Entwicklungsstand der physikalischen Experimentierumgebung und einer Zusammenfassung der bislang erreichten Ergebnisse beschließen wir den diesjährigen Beitrag. Y1 - 2021 UR - https://www.essv.de/?year=2021 SN - 978-3-959082-27-3 SN - 0940-6832 SP - 67 EP - 76 PB - TUDpress CY - Dresden ER - TY - GEN A1 - Beim Graben, Peter A1 - Huber, Markus A1 - Meyer, Werner A1 - Römer, Ronald A1 - Wolff, Matthias T1 - Vector Symbolic Architectures for Context-Free Grammars T2 - Cognitive Computation N2 - Vector symbolic architectures (VSA) are a viable approach for the hyperdimensional representation of symbolic data, such as documents, syntactic structures, or semantic frames. We present a rigorous mathematical framework for the representation of phrase structure trees and parse trees of context-free grammars (CFG) in Fock space, i.e. infinite-dimensional Hilbert space as being used in quantum field theory. We define a novel normal form for CFG by means of term algebras. Using a recently developed software toolbox, called FockBox, we construct Fock space representations for the trees built up by a CFG left-corner (LC) parser. We prove a universal representation theorem for CFG term algebras in Fock space and illustrate our findings through a low-dimensional principal component projection of the LC parser state. Our approach could leverage the development of VSA for explainable artificial intelligence (XAI) by means of hyperdimensional deep neural computation. Y1 - 2021 U6 - https://doi.org/10.1007/s12559-021-09974-y SN - 1866-9964 VL - 14 IS - 2 SP - 733 EP - 748 ER - TY - GEN A1 - Huber-Liebl, Markus A1 - Römer, Ronald A1 - Wirsching, Günther A1 - Schmitt, Ingo A1 - beim Graben, Peter A1 - Wolff, Matthias T1 - Quantum-inspired Cognitive Agents T2 - Frontiers in Applied Mathematics and Statistics N2 - The concept of intelligent agents is—roughly speaking—based on an architecture and a set of behavioral programs that primarily serve to solve problems autonomously. Increasing the degree of autonomy and improving cognitive performance, which can be assessed using cognitive and behavioral tests, are two important research trends. The degree of autonomy can be increased using higher-level psychological modules with which needs and motives are taken into account. In our approach we integrate these modules in architecture for an embodied, enactive multi-agent system, such that distributed problem solutions can be achieved. Furthermore, after uncovering some weaknesses in the cognitive performance of traditionally designed agents, we focus on two major aspects. On the one hand, the knowledge processing of cognitive agents is based on logical formalisms, which have deficiencies in the representation and processing of incomplete or uncertain knowledge. On the other hand, in order to fully understand the performance of cognitive agents, explanations at the symbolic and subsymbolic levels are required. Both aspects can be addressed by quantum-inspired cognitive agents. To investigate this approach, we consider two tasks in the sphere of Shannon's famous mouse-maze problem: namely classifying target objects and ontology inference. First, the classification of an unknown target object in the mouse-maze, such as cheese, water, and bacon, is based on sensory data that measure characteristics such as odor, color, shape, or nature. For an intelligent agent, we need a classifier with good prediction accuracy and explanatory power on a symbolic level. Boolean logic classifiers do work on a symbolic level but are not adequate for dealing with continuous data. Therefore, we demonstrate and evaluate a quantum-logic-inspired classifier in comparison to Boolean-logic-based classifiers. Second, ontology inference is iteratively achieved by a quantum-inspired agent through maze exploration. This requires the agent to be able to manipulate its own state by performing actions and by collecting sensory data during perception. We suggest an algebraic approach where both kinds of behaviors are uniquely described by quantum operators. The agent's state space is then iteratively constructed by carrying out unitary action operators, while Hermitian perception operators act as observables on quantum eigenstates. As a result, an ontology emerges as the simultaneous solution of the respective eigenvalue equations. Tags: btuktqiai; btuktcogsys; btukttheseus; btuktqtheseus Y1 - 2022 UR - https://www.frontiersin.org/articles/10.3389/fams.2022.909873 U6 - https://doi.org/10.3389/fams.2022.909873 SN - 2297-4687 IS - 8 SP - 1 EP - 31 ER - TY - GEN A1 - Beim Graben, Peter A1 - Huber-Liebl, Markus A1 - Klimczak, Peter A1 - Wirsching, Günther T1 - Machine Semiotics T2 - arXiv N2 - Recognizing a basic difference between the semiotics of humans and machines presents a possibility to overcome the shortcomings of current speech assistive devices. For the machine, the meaning of a (human) utterance is defined by its own scope of actions. Machines, thus, do not need to understand the conventional meaning of an utterance. Rather, they draw conversational implicatures in the sense of (neo-)Gricean pragmatics. For speech assistive devices, the learning of machine-specific meanings of human utterances, i.e. the fossilization of conversational implicatures into conventionalized ones by trial and error through lexicalization appears to be sufficient. Using the quite trivial example of a cognitive heating | device, we show that — based on dynamic semantics — this process can be formalized as the reinforcement learning of utterance-meaning pairs (UMP). KW - Semiotics KW - machine learning KW - dynamic semantics KW - pragmatic implicatures KW - fossilization Y1 - 2023 UR - https://arxiv.org/abs/2008.10522v2 SP - 1 EP - 48 ER - TY - GEN A1 - Römer, Ronald A1 - beim Graben, Peter A1 - Huber-Liebl, Markus A1 - Wolff, Matthias T1 - (Pre-)linguistic Problem Solving based on Dynamic Semantics T2 - 14th IEEE International Conference on Cognitive Infocommunications – CogInfoCom 2023, September 22-23, Budapest, Hungary Y1 - 2023 SN - 979-8-3503-2565-2 SN - 979-8-3503-2566-9 U6 - https://doi.org/10.1109/CogInfoCom59411.2023.10397487 SN - 2473-5671 SN - 2380-7350 SP - 147 EP - 152 ER - TY - GEN A1 - Maier, Isidor Konrad A1 - Kuhn, Johannes A1 - Beisegel, Jesse A1 - Huber-Liebl, Markus A1 - Wolff, Matthias T1 - Minimalist Grammar: Construction without Overgeneration T2 - arXiv N2 - In this paper we give instructions on how to write a minimalist grammar (MG). In order to present the instructions as an algorithm, we use a variant of context free grammars (CFG) as an input format. We can exclude overgeneration, if the CFG has no recursion, i.e. no non-terminal can (indirectly) derive to a right-hand side containing itself. The constructed MGs utilize licensors/-ees as a special way of exception handling. A CFG format for a derivation A_eats_B↦∗peter_eats_apples, where A and B generate noun phrases, normally leads to overgeneration, e.\,g., i_eats_apples. In order to avoid overgeneration, a CFG would need many non-terminal symbols and rules, that mainly produce the same word, just to handle exceptions. In our MGs however, we can summarize CFG rules that produce the same word in one item and handle exceptions by a proper distribution of licensees/-ors. The difficulty with this technique is that in most generations the majority of licensees/-ors is not needed, but still has to be triggered somehow. We solve this problem with ϵ-items called \emph{adapters}. Y1 - 2023 UR - https://arxiv.org/abs/2311.01820 U6 - https://doi.org/10.48550/arXiv.2311.01820 ER - TY - GEN A1 - Huber-Liebl, Markus A1 - Wirsching, Günther T1 - Ein quantenlogisch motivierter Ansatz zur Verarbeitung von Äußerungs-Bedeutungspaaren T2 - Elektronische Sprachsignalverarbeitung, Tagungsband der 35. Konferenz, 06.-08.03.2024, Regensburg N2 - Wir repräsentieren eine Bedeutung als Liste von Mustersignalen, und unser Ziel ist es, ein weiteres ankommendes Signal damit zu vergleichen. Die Quantenlogik motiviert die Verwendung von Orthogonalprojektoren, um die gesuchte Ähnlichkeit als Projektionswahrscheinlichkeit darzustellen. Die Ergebnisse des quantenlogischen Verfahrens hängen davon ab, in welcher Weise die Signale vorverarbeitet werden. In diesem Aufsatz untersuchen und diskutieren wir vier verschiedene Möglichkeiten der Vorverarbeitung. Y1 - 2024 UR - https://www.essv.de/pdf/2024_94_101.pdf?id=1210 SN - 978-3-95908-325-6 SN - 0940-6832 SP - 94 EP - 101 PB - TUDpress CY - Dresden ER - TY - GEN A1 - Huber-Liebl, Markus A1 - Rosenow, Tillmann A1 - Römer, Ronald A1 - Wirsching, Günther A1 - Wolff, Matthias ED - Grawunder, Sven T1 - It all starts with a little difference : tensors as data and code. T2 - Elektronische Sprachsignalverarbeitung 2025 : Tagungsband der 36. Konferenz Halle/Saale, 5.–7. März 2025 N2 - 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. We argue that these are two sides of the same coin. For experimental symbolic algorithms we introduce a suitable testbed and give its proper specification. We formalize our method of behavioural control with tensor algebra and discuss its implementation for our physical testbed realization. Y1 - 2025 UR - https://www.essv.de/pdf/2025_170_179.pdf?id=1250 SN - 978-3-95908-803-9 SN - 0940-6832 SP - 170 EP - 179 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Duckhorn, Frank A1 - Huber, Markus A1 - Meyer, Werner A1 - Wolff, Matthias ED - Karpov, Alexey ED - Jokisch, Oliver ED - Potapova, Rodmonga T1 - A Cognitive User Interface for a Multi-Modal Human-Machine Interaction T2 - Speech and computer : 20th International Conference, SPECOM 2018, Leipzig, Germany, September 18-22, 2018, proceedings Y1 - 2018 UR - https://link.springer.com/chapter/10.1007/978-3-319-99579-3_72 SN - 978-3-319-99578-6 U6 - https://doi.org/10.1007/978-3-319-99579-3 SP - 707 EP - 717 PB - Springer International Publishing CY - Cham ER - TY - GEN A1 - Duckhorn, Frank A1 - Huber, Markus A1 - Meyer, Werner A1 - Jokisch, Oliver A1 - Tschöpe, Constanze A1 - Wolff, Matthias ED - Lacerda, Francisco T1 - Towards an Autarkic Embedded Cognitive User Interface T2 - Proceedings Interspeech 2017, 20-24 August 2017, Stockholm N2 - ucuikt2015 Y1 - 2017 UR - http://www.isca-speech.org/archive/Interspeech_2017/ U6 - https://doi.org/10.21437/Interspeech.2017 SP - 3435 EP - 3436 PB - ISCA ER - TY - GEN A1 - Römer, Ronald A1 - Huber-Liebl, Markus A1 - Wolff, Matthias T1 - Quantum-inspired representation and querying of semiotic object properties by cognitive agents T2 - 2025 IEEE 16th International Conference on Cognitive Infocommunications (CogInfoCom) N2 - 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. KW - Information retrieval KW - Semiotics KW - Planning Y1 - 2025 SN - 979-8-3503-5691-5 U6 - https://doi.org/10.1109/CogInfoCom66819.2025.11200567 SP - 000129 EP - 000134 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Huber-Liebl, Markus A1 - Rosenow, Tillmann A1 - Römer, Ronald A1 - Wirsching, Günther A1 - Wolff, Matthias T1 - Knowledge representation and querying with tensors for a class of practical test problems T2 - Refereed Paper Proceedings - KM Conference 2025 – Siena, Italy N2 - 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. KW - Knowledge representation KW - Cognitive agents KW - Tensor algebra KW - Quantum inspiration Y1 - 2025 UR - https://www.iiakm.org/conference/proceedings/KM2025_RefereedProceedingsPapers.pdf SP - 111 EP - 123 PB - International Institute for Applied Knowledge Management ER -