@phdthesis{Schneider2019, author = {Schneider, Jan Niklas}, title = {Computational approaches for emotion research}, doi = {10.25932/publishup-45927}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-459275}, school = {Universit{\"a}t Potsdam}, pages = {xv, 145}, year = {2019}, abstract = {Emotionen sind ein zentrales Element menschlichen Erlebens und spielen eine wichtige Rolle bei der Entscheidungsfindung. Diese Dissertation identifiziert drei methodische Probleme der aktuellen Emotionsforschung und zeigt auf, wie diese mittels computergest{\"u}tzter Methoden gel{\"o}st werden k{\"o}nnen. Dieser Ansatz wird in drei Forschungsprojekten demonstriert, die die Entwicklung solcher Methoden sowie deren Anwendung auf konkrete Forschungsfragen beschreiben. Das erste Projekt beschreibt ein Paradigma welches es erm{\"o}glicht, die subjektive und objektive Schwierigkeit der Emotionswahrnehmung zu messen. Dar{\"u}ber hinaus erm{\"o}glicht es die Verwendung einer beliebigen Anzahl von Emotionskategorien im Vergleich zu den {\"u}blichen sechs Kategorien der Basisemotionen. Die Ergebnisse deuten auf eine Zunahme der Schwierigkeiten bei der Wahrnehmung von Emotionen mit zunehmendem Alter der Darsteller hin und liefern Hinweise darauf, dass junge Erwachsene, {\"a}ltere Menschen und M{\"a}nner ihre Schwierigkeit bei der Wahrnehmung von Emotionen untersch{\"a}tzen. Weitere Analysen zeigten eine geringe Relevanz personenbezogener Variablen und deuteten darauf hin, dass die Schwierigkeit der Emotionswahrnehmung vornehmlich durch die Auspr{\"a}gung der Wertigkeit des Ausdrucks bestimmt wird. Das zweite Projekt zeigt am Beispiel von Arousal, einem etablierten, aber vagen Konstrukt der Emotionsforschung, wie Face-Tracking-Daten dazu genutzt werden k{\"o}nnen solche Konstrukte zu sch{\"a}rfen. Es beschreibt, wie aus Face-Tracking-Daten Maße f{\"u}r die Entfernung, Geschwindigkeit und Beschleunigung von Gesichtsausdr{\"u}cken berechnet werden k{\"o}nnen. Das Projekt untersuchte wie diesen Maße mit der Arousal-Wahrnehmung in Menschen mit und ohne Autismus zusammenh{\"a}ngen. Der Abstand zum Neutralgesicht war pr{\"a}diktiv f{\"u}r die Arousal-Bewertungen in beiden Gruppen. Die Ergebnisse deuten auf eine qualitativ {\"a}hnliche Wahrnehmung von Arousal f{\"u}r Menschen mit und ohne Autismus hin. Im dritten Projekt stellen wir die Partial-Least-Squares-Analyse als allgemeine Methode vor, um eine optimale Repr{\"a}sentation zur Verkn{\"u}pfung zweier hochdimensionale Datens{\"a}tze zu finden. Das Projekt demonstriert die Anwendbarkeit dieser Methode in der Emotionsforschung anhand der Frage nach Unterschieden in der Emotionswahrnehmung zwischen M{\"a}nnern und Frauen. Wir konnten zeigen, dass die emotionale Wahrnehmung von Frauen systematisch mehr Varianz der Gesichtsausdr{\"u}cke erfasst und dass signifikante Unterschiede in der Art und Weise bestehen, wie Frauen und M{\"a}nner einige Gesichtsausdr{\"u}cke wahrnehmen. Diese konnten wir als dynamische Gesichtsausdr{\"u}cke visualisieren. Um die Anwendung der entwickelten Methode f{\"u}r die Forschungsgemeinschaft zu erleichtern, wurde ein Software-Paket f{\"u}r die Statistikumgebung R geschrieben. Zudem wurde eine Website entwickelt (thisemotiondoesnotexist.com), die es Besuchern erlaubt, ein Partial-Least-Squares-Modell von Emotionsbewertungen und Face-Tracking-Daten interaktiv zu erkunden, um die entwickelte Methode zu verbreiten und ihren Nutzen f{\"u}r die Emotionsforschung zu illustrieren.}, language = {en} } @phdthesis{Boehne2019, author = {B{\"o}hne, Sebastian}, title = {Different degrees of formality}, doi = {10.25932/publishup-42379}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423795}, school = {Universit{\"a}t Potsdam}, pages = {VI, 167}, year = {2019}, abstract = {In this thesis we introduce the concept of the degree of formality. It is directed against a dualistic point of view, which only distinguishes between formal and informal proofs. This dualistic attitude does not respect the differences between the argumentations classified as informal and it is unproductive because the individual potential of the respective argumentation styles cannot be appreciated and remains untapped. This thesis has two parts. In the first of them we analyse the concept of the degree of formality (including a discussion about the respective benefits for each degree) while in the second we demonstrate its usefulness in three case studies. In the first case study we will repair Haskell B. Curry's view of mathematics, which incidentally is of great importance in the first part of this thesis, in light of the different degrees of formality. In the second case study we delineate how awareness of the different degrees of formality can be used to help students to learn how to prove. Third, we will show how the advantages of proofs of different degrees of formality can be combined by the development of so called tactics having a medium degree of formality. Together the three case studies show that the degrees of formality provide a convincing solution to the problem of untapped potential.}, language = {en} } @misc{Fandinno2019, author = {Fandinno, Jorge}, title = {Founded (auto)epistemic equilibrium logic satisfies epistemic splitting}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1060}, issn = {1866-8372}, doi = {10.25932/publishup-46968}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-469685}, pages = {671 -- 687}, year = {2019}, abstract = {In a recent line of research, two familiar concepts from logic programming semantics (unfounded sets and splitting) were extrapolated to the case of epistemic logic programs. The property of epistemic splitting provides a natural and modular way to understand programs without epistemic cycles but, surprisingly, was only fulfilled by Gelfond's original semantics (G91), among the many proposals in the literature. On the other hand, G91 may suffer from a kind of self-supported, unfounded derivations when epistemic cycles come into play. Recently, the absence of these derivations was also formalised as a property of epistemic semantics called foundedness. Moreover, a first semantics proved to satisfy foundedness was also proposed, the so-called Founded Autoepistemic Equilibrium Logic (FAEEL). In this paper, we prove that FAEEL also satisfies the epistemic splitting property something that, together with foundedness, was not fulfilled by any other approach up to date. To prove this result, we provide an alternative characterisation of FAEEL as a combination of G91 with a simpler logic we called Founded Epistemic Equilibrium Logic (FEEL), which is somehow an extrapolation of the stable model semantics to the modal logic S5.}, language = {en} } @misc{Strickroth2019, author = {Strickroth, Sven}, title = {PLATON}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {804}, issn = {1866-8372}, doi = {10.25932/publishup-44188}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-441887}, pages = {28}, year = {2019}, abstract = {Lesson planning is both an important and demanding task—especially as part of teacher training. This paper presents the requirements for a lesson planning system and evaluates existing systems regarding these requirements. One major drawback of existing software tools is that most are limited to a text- or form-based representation of the lesson designs. In this article, a new approach with a graphical, time-based representation with (automatic) analyses methods is proposed and the system architecture and domain model are described in detail. The approach is implemented in an interactive, web-based prototype called PLATON, which additionally supports the management of lessons in units as well as the modelling of teacher and student-generated resources. The prototype was evaluated in a study with 61 prospective teachers (bachelor's and master's preservice teachers as well as teacher trainees in post-university teacher training) in Berlin, Germany, with a focus on usability. The results show that this approach proofed usable for lesson planning and offers positive effects for the perception of time and self-reflection.}, language = {en} } @phdthesis{AbdelwahabHusseinAbdelwahabElsayed2019, author = {Abdelwahab Hussein Abdelwahab Elsayed, Ahmed}, title = {Probabilistic, deep, and metric learning for biometric identification from eye movements}, doi = {10.25932/publishup-46798}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-467980}, school = {Universit{\"a}t Potsdam}, pages = {vi, 65}, year = {2019}, abstract = {A central insight from psychological studies on human eye movements is that eye movement patterns are highly individually characteristic. They can, therefore, be used as a biometric feature, that is, subjects can be identified based on their eye movements. This thesis introduces new machine learning methods to identify subjects based on their eye movements while viewing arbitrary content. The thesis focuses on probabilistic modeling of the problem, which has yielded the best results in the most recent literature. The thesis studies the problem in three phases by proposing a purely probabilistic, probabilistic deep learning, and probabilistic deep metric learning approach. In the first phase, the thesis studies models that rely on psychological concepts about eye movements. Recent literature illustrates that individual-specific distributions of gaze patterns can be used to accurately identify individuals. In these studies, models were based on a simple parametric family of distributions. Such simple parametric models can be robustly estimated from sparse data, but have limited flexibility to capture the differences between individuals. Therefore, this thesis proposes a semiparametric model of gaze patterns that is flexible yet robust for individual identification. These patterns can be understood as domain knowledge derived from psychological literature. Fixations and saccades are examples of simple gaze patterns. The proposed semiparametric densities are drawn under a Gaussian process prior centered at a simple parametric distribution. Thus, the model will stay close to the parametric class of densities if little data is available, but it can also deviate from this class if enough data is available, increasing the flexibility of the model. The proposed method is evaluated on a large-scale dataset, showing significant improvements over the state-of-the-art. Later, the thesis replaces the model based on gaze patterns derived from psychological concepts with a deep neural network that can learn more informative and complex patterns from raw eye movement data. As previous work has shown that the distribution of these patterns across a sequence is informative, a novel statistical aggregation layer called the quantile layer is introduced. It explicitly fits the distribution of deep patterns learned directly from the raw eye movement data. The proposed deep learning approach is end-to-end learnable, such that the deep model learns to extract informative, short local patterns while the quantile layer learns to approximate the distributions of these patterns. Quantile layers are a generic approach that can converge to standard pooling layers or have a more detailed description of the features being pooled, depending on the problem. The proposed model is evaluated in a large-scale study using the eye movements of subjects viewing arbitrary visual input. The model improves upon the standard pooling layers and other statistical aggregation layers proposed in the literature. It also improves upon the state-of-the-art eye movement biometrics by a wide margin. Finally, for the model to identify any subject — not just the set of subjects it is trained on — a metric learning approach is developed. Metric learning learns a distance function over instances. The metric learning model maps the instances into a metric space, where sequences of the same individual are close, and sequences of different individuals are further apart. This thesis introduces a deep metric learning approach with distributional embeddings. The approach represents sequences as a set of continuous distributions in a metric space; to achieve this, a new loss function based on Wasserstein distances is introduced. The proposed method is evaluated on multiple domains besides eye movement biometrics. This approach outperforms the state of the art in deep metric learning in several domains while also outperforming the state of the art in eye movement biometrics.}, language = {en} } @misc{AguadoCabalarFandinnoetal.2019, author = {Aguado, Felicidad and Cabalar, Pedro and Fandinno, Jorge and Pearce, David and Perez, Gilberto and Vidal, Concepcion}, title = {Revisiting explicit negation in answer set programming}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1104}, issn = {1866-8372}, doi = {10.25932/publishup-46969}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-469697}, pages = {908 -- 924}, year = {2019}, abstract = {A common feature in Answer Set Programming is the use of a second negation, stronger than default negation and sometimes called explicit, strong or classical negation. This explicit negation is normally used in front of atoms, rather than allowing its use as a regular operator. In this paper we consider the arbitrary combination of explicit negation with nested expressions, as those defined by Lifschitz, Tang and Turner. We extend the concept of reduct for this new syntax and then prove that it can be captured by an extension of Equilibrium Logic with this second negation. We study some properties of this variant and compare to the already known combination of Equilibrium Logic with Nelson's strong negation.}, language = {en} }