Wolfgang Weber (1939–2019) Professor of Human Resource Management and Founding Editor of the German Journal of Human Resource Management - Festing, Marion; Iseke, Anja; Kabst, Rüdiger; Martin, Albert; Matiaske, Wenzel; Mayrhofer, Wolfgang; Nienhüser, Werner (German Journal of Human Resource Management: Zeitschrift für Personalforschung)

Intergenerational Value Similarity in Adulthood - Hoellger, Christian; Sommer, Sabrina; Albert, Isabelle; Buhl, Heike M. (Journal of Family Issues)
This investigation concentrates on value similarity between parents and their children during adulthood. The interplay between gender, age, relationship quality, and frequency of contact on value similarity was analyzed. A total of 600 adult German children (53.8% women) and their parents took part in a questionnaire study. Value orientation was measured with a short version of Schwartz’s Portrait Values Questionnaire, and relationship quality with the Network of Relationships Inventory (Furman & Buhrmeister, 1992).Value similarity was higher in mother–daughter dyads compared to mother–son dyads, but in the other dyads, no significant differences were found. Regarding relationship quality, verbal intimacy was not related to value similarity. Parental satisfaction was associated with value similarity in the father–child dyads. Satisfaction, as perceived by adult children, was linked to value similarity in mother–child and father–son dyads. Furthermore, the frequency of contact related to value similarity between mothers and sons.
Keywords: Social Sciences (miscellaneous)

Ecken, Systeme, Funktionsbereiche. Eine Medienkulturgeschichte des Filter(n)s im Kontext von Wohnräumen - Miggelbrink, Monique (Navigationen – Zeitschrift für Medien- und Kulturwissenschaften, Themenschwerpunkt: Filter(n) – Geschichte Ästhetik Praktiken)

Nash Smoothing on the Test Bench: H_alpha--Essential Equilibira - Duman, Papatya; Trockel, Walter

Mental body rotation with egocentric and object-based transformations in different postures: sitting vs. standing - Budde, Kirsten; Barela, José Angelo; Figueiredo, Gabriella Andreeta; Weigelt, Matthias (Brazilian Journal of Motor Behavior)
BACKGROUND: A detail of previous studies on mental rotation, which has not received any attention so far, relates to the testing situation of the participants. In nearly every study, participants were tested in a sitting posture (and not standing). However, when considering embodied cognition approaches on mental processes, participants may not be able to fully exploit these processes when performing mental rotation tasks in a sitting posture.
AIM: Therefore, the aim of the present study is to examine the potential influence of two different postures (sitting vs. standing), when solving mental body rotation tasks.
METHOD: Sixteen participants (6 females) were tested in two mental body-rotation tasks (MBRT), requiring either an object-based spatial transformation (based on a same-different judgment) or an egocentric transformation (based on a left-right judgment) in a sitting and in a standing posture. Reaction times and response errors were analysed in two three-way ANOVAs, with the factors orientation, task, and posture.
RESULTS: Results revealed an effect of orientation and task, indicating that participants performed better for egocentric than for object-based transformations. However, there was no effect of posture.
CONCLUSION: The different dynamics of postural control during sitting and standing do not induce different embodiment effects on mental rotation.

Hat die Körperposition (sitzen vs. stehen) einen Einfluss auf die Leistung in einer Mentalen Rotationsaufgabe? - Budde, Kirsten; Barela, José A; Weigelt, Matthias (Abstractband der 52. Jahrestagung der Arbeitsgemeinschaft für Sportpsychologie (asp))

Linguistik des Briefs - Schuster, Britt-Marie (Handbuch Brief. Von der Frühen Neuzeit bis zur Gegenwart (Bd. 1: Interdisziplinarität – Systematische Perspektiven – Briefgenres))
Keywords: Textsortengeschichte

The contribution of terminology research to the understanding of science communication - Schuster, Britt-Marie (Science Communication (Handbooks of Communication Science))
Keywords: Fachkommunikation

Was bedeutet Ehre? Diskursethische Überlegungen zu den BBC-Reden Thomas Manns - Schuster, Britt-Marie; Markewitz, Friedrich; Wilk, Nicole M. (Diskurs – ethisch.)
Keywords: Textsemantik

micro-Raman Investigations of Periodically-Poled X-Cut Thin-Film Lithium Niobate for Integrated Optics - Reitzig, Sven; Rüsing, Michael; Kirbus, Benjamin; Gossel, Joshua; Singh, Ekta; Eng, Lukas M.; Zhao, Jie; Mookherjea, Shayan (2020 Joint Conference of the IEEE International Frequency Control Symposium and International Symposium on Applications of Ferroelectrics (IFCS-ISAF))

Selbstreguliertes Lernen - Können die das überhaupt? Gestaltung von Lernprozessen in berufsvorbereitenden Bildungsgängen. - Sloane, Peter F. E.; Daniel, Desiree; Meier, Karin; Schwabl, Franziska; Volgmann, Simone

Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis - Prager, Raphael Patrick; Trautmann, Heike; Wang, Hao; Bäck, Thomas H. W.; Kerschke, Pascal (Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI))
In this paper, we rely on previous work proposing a modularized version of CMA-ES, which captures several alterations to the conventional CMA-ES developed in recent years. Each alteration provides significant advantages under certain problem properties, e.g., multi-modality, high conditioning. These distinct advancements are implemented as modules which result in 4608 unique versions of CMA-ES. Previous findings illustrate the competitive advantage of enabling and disabling the aforementioned modules for different optimization problems. Yet, this modular CMA-ES is lacking a method to automatically determine when the activation of specific modules is auspicious and when it is not. We propose a well-performing instance-specific algorithm configuration model which selects an (almost) optimal configuration of modules for a given problem instance. In addition, the structure of this configuration model is able to capture inter-dependencies between modules, e.g., two (or more) modules might only be advantageous in unison for some problem types, making the orchestration of modules a crucial task. This is accomplished by chaining multiple random forest classifiers together into a so-called Classifier Chain based on a set of numerical features extracted by means of Exploratory Landscape Analysis (ELA) to describe the given problem instances.

A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media - Assenmacher, D; Clever, L; Pohl, JS; Trautmann, Heike; Grimme, C (Proceedings of the International Conference on Human-Computer Interaction (HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis)
The identification of coordinated campaigns within Social Media is a complex task that is often hindered by missing labels and large amounts of data that have to be processed. We propose a new two-phase framework that uses unsupervised stream clustering for detecting suspicious trends over time in a first step. Afterwards, traditional offline analyses are applied to distinguish between normal trend evolution and malicious manipulation attempts. We demonstrate the applicability of our framework in the context of the final days of the Brexit in 2019/2020.

Towards Automated Configuration of Stream Clustering Algorithms - Carnein, Matthias; Trautmann, Heike; Bifet, Albert; Pfahringer, Bernhard (Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD ’19))
Clustering is an important technique in data analysis which can reveal hidden patterns and unknown relationships in the data. A common problem in clustering is the proper choice of parameter settings. To tackle this, automated algorithm configuration is available which can automatically find the best parameter settings. In practice, however, many of our today’s data sources are data streams due to the widespread deployment of sensors, the internet-of-things or (social) media. Stream clustering aims to tackle this challenge by identifying, tracking and updating clusters over time. Unfortunately, none of the existing approaches for automated algorithm configuration are directly applicable to the streaming scenario. In this paper, we explore the possibility of automated algorithm configuration for stream clustering algorithms using an ensemble of different configurations. In first experiments, we demonstrate that our approach is able to automatically find superior configurations and refine them over time.

Inside the tool set of automation: Free social bot code revisited - Assenmacher, Dennis; Frischlich , Lena; Trautmann, Heike; Grimme, Christian; Adam, Lena (Disinformation in open online media)
Social bots have recently gained attention in the context of public opinion manipulation on social media platforms. While a lot of research effort has been put into the classification and detection of such automated programs, it is still unclear how technically sophisticated those bots are, which platforms they target, and where they originate from. To answer these questions, we gathered repository data from open source collaboration platforms to identify the status-quo of social bot development as well as first insights into the overall skills of publicly available bot code.

confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms - Carnein, Matthias; Trautmann, Heike; Bifet, Albert; Pfahringer, Bernhard (Proceedings of the 14$^th$ Learning and Intelligent Optimization Conference (LION 2020))
Machine learning has become one of the most important tools in data analysis. However, selecting the most appropriate machine learning algorithm and tuning its hyperparameters to their optimal values remains a difficult task. This is even more difficult for streaming applications where automated approaches are often not available to help during algorithm selection and configuration. This paper proposes the first approach for automated algorithm selection and configuration of stream clustering algorithms. We train an ensemble of different stream clustering algorithms and configurations in parallel and use the best performing configuration to obtain a clustering solution. By drawing new configurations from better performing ones, we are able to improve the ensemble performance over time. In large experiments on real and artificial data we show how our ensemble approach can improve upon default configurations and can also compete with a-posteriori algorithm configuration. Our approach is considerably faster than a-posteriori approaches and applicable in real-time. In addition, it is not limited to stream clustering and can be generalised to all streaming applications, including stream classification and regression.

Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection - Bossek, Jakob; Kerschke, Pascal; Trautmann, Heike (Proceedings of the IEEE Congress on Evolutionary Computation (CEC))
The Traveling-Salesperson-Problem (TSP) is arguably one of the best-known NP-hard combinatorial optimization problems. The two sophisticated heuristic solvers LKH and EAX and respective (restart) variants manage to calculate close-to optimal or even optimal solutions, also for large instances with several thousand nodes in reasonable time. In this work we extend existing benchmarking studies by addressing anytime behaviour of inexact TSP solvers based on empirical runtime distributions leading to an increased understanding of solver behaviour and the respective relation to problem hardness. It turns out that performance ranking of solvers is highly dependent on the focused approximation quality. Insights on intersection points of performances offer huge potential for the construction of hybridized solvers depending on instance features. Moreover, instance features tailored to anytime performance and corresponding performance indicators will highly improve automated algorithm selection models by including comprehensive information on solver quality.

Towards Decision Support in Dynamic Bi-Objective Vehicle Routing - Bossek, Jakob; Grimme, Christian; Rudolph, Günter; Trautmann, Heike (Proceedings of the IEEE Congress on Evolutionary Computation (CEC))
We consider a dynamic bi-objective vehicle routing problem, where a subset of customers ask for service over time. Therein, the distance traveled by a single vehicle and the number of unserved dynamic requests is minimized by a dynamic evolutionary multi-objective algorithm (DEMOA), which operates on discrete time windows (eras). A decision is made at each era by a decision-maker, thus any decision depends on irreversible decisions made in foregoing eras. To understand effects of sequences of decision-making and interactions/dependencies between decisions made, we conduct a series of experiments. More precisely, we fix a set of decision-maker preferences D and the number of eras n t and analyze all |D| nt combinations of decision-maker options. We find that for random uniform instances (a) the final selected solutions mainly depend on the final decision and not on the decision history, (b) solutions are quite robust with respect to the number of unvisited dynamic customers, and (c) solutions of the dynamic approach can even dominate solutions obtained by a clairvoyant EMOA. In contrast, for instances with clustered customers, we observe a strong dependency on decision-making history as well as more variance in solution diversity.

Dynamic Bi-Objective Routing of Multiple Vehicles - Bossek, Jakob; Grimme, Christian; Trautmann, Heike (Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’20))
In practice, e.g. in delivery and service scenarios, Vehicle-Routing-Problems (VRPs) often imply repeated decision making on dynamic customer requests. As in classical VRPs, tours have to be planned short while the number of serviced customers has to be maximized at the same time resulting in a multi-objective problem. Beyond that, however, dynamic requests lead to the need for re-planning of not yet realized tour parts, while already realized tour parts are irreversible. In this paper we study this type of bi-objective dynamic VRP including sequential decision making and concurrent realization of decisions. We adopt a recently proposed Dynamic Evolutionary Multi-Objective Algorithm (DEMOA) for a related VRP problem and extend it to the more realistic (here considered) scenario of multiple vehicles. We empirically show that our DEMOA is competitive with a multi-vehicle offline and clairvoyant variant of the proposed DEMOA as well as with the dynamic single-vehicle approach proposed earlier.

Automated detection of nostalgic text in the context of societal pessimism - Lena, Clever; Frischlich, Lena; Trautmann, Heike; Grimme, Christian (Disinformation in open online media)
In online media environments, nostalgia can be used as important ingredient of propaganda strategies, specifically, by creating societal pessimism. This work addresses the automated detection of nostalgic text as a first step towards automatically identifying nostalgia-based manipulation strategies. We compare the performance of standard machine learning approaches on this challenge and demonstrate the successful transfer of the best performing approach to real-world nostalgia detection in a case study.

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem - Seiler, Moritz V; Pohl, Janina; Bossek, Jakob; Kerschke, Pascal; Trautmann, Heike (Proceedings of the 16$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XVI))
In this work we focus on the well-known Euclidean Traveling Salesperson Problem (TSP) and two highly competitive inexact heuristic TSP solvers, EAX and LKH, in the context of per-instance algorithm selection (AS). We evolve instances with 1000 nodes where the solvers show strongly different performance profiles. These instances serve as a basis for an exploratory study on the identification of well-discriminating problem characteristics (features). Our results in a nutshell: we show that even though (1) promising features exist, (2) these are in line with previous results from the literature, and (3) models trained with these features are more accurate than models adopting sophisticated feature selection methods, the advantage is not close to the virtual best solver in terms of penalized average runtime and so is the performance gain over the single best solver. However, we show that a feature-free deep neural network based approach solely based on visual representation of the instances already matches classical AS model results and thus shows huge potential for future studies.

Building an Integrated Comment Moderation System – Towards a Semi-automatic Moderation Tool - Riehle, Dennis M.; Niemann, Marco; Brunk, Jens; Assenmacher, Dennis; Trautmann, Heike; Becker, Jörg (Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social Computing)
The past decade has been characterized by a strong increase in the use of social media and a continuous growth of public online discussion. With the failure of purely manual moderation, platform operators started searching for semi-automated solutions, where the application of Natural Language Processing (NLP) and Machine Learning (ML) techniques is promising. However, this requires huge financial investments for algorithmic implementations, data collection, and model training, which only big players can afford. To support smaller or medium-sized media enterprises (SME), we developed an integrated comment moderation system as an IT platform. This platform acts as a service provider and offers Analytics as a Service (AaaS) to SMEs. Operating such a platform, however, requires a robust technology stack, integrated workflows and well-defined interfaces between all parties. In this paper, we develop and discuss a suitable IT architecture and present a prototypical implementation.

Demystifying Social Bots: On the Intelligence of Automated Social Media Actors - Assenmacher, Dennis; Clever, Lena; Frischlich, Lena; Quandt, Thorsten; Trautmann, Heike; Grimme, Christian (Social Media + Society)
Recently, social bots, (semi-) automatized accounts in social media, gained global attention in the context of public opinion manipulation. Dystopian scenarios like the malicious amplification of topics, the spreading of disinformation, and the manipulation of elections through “opinion machines” created headlines around the globe. As a consequence, much research effort has been put into the classification and detection of social bots. Yet, it is still unclear how easy an average online media user can purchase social bots, which platforms they target, where they originate from, and how sophisticated these bots are. This work provides a much needed new perspective on these questions. By providing insights into the markets of social bots in the clearnet and darknet as well as an exhaustive analysis of freely available software tools for automation during the last decade, we shed light on the availability and capabilities of automated profiles in social media platforms. Our results confirm the increasing importance of social bot technology but also uncover an as yet unknown discrepancy of theoretical and practically achieved artificial intelligence in social bots: while literature reports on a high degree of intelligence for chat bots and assumes the same for social bots, the observed degree of intelligence in social bot implementations is limited. In fact, the overwhelming majority of available services and software are of supportive nature and merely provide modules of automation instead of fully fledged “intelligent” social bots.

A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms - Bossek, Jakob; Kerschke, Pascal; Trautmann, Heike (Applied Soft Computing)
We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs – both to be minimized – is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers.
Keywords: Algorithm selection; Multi-objective optimization; Performance measurement; Combinatorial optimization; Traveling Salesperson Problem

Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries - Seiler, Moritz Vinzent; Trautmann, Heike; Kerschke, Pascal (Proceedings of the International Joint Conference on Neural Networks (IJCNN))
Artificial neural networks in general and deep learning networks in particular established themselves as popular and powerful machine learning algorithms. While the often tremendous sizes of these networks are beneficial when solving complex tasks, the tremendous number of parameters also causes such networks to be vulnerable to malicious behavior such as adversarial perturbations. These perturbations can change a model's classification decision. Moreover, while single-step adversaries can easily be transferred from network to network, the transfer of more powerful multi-step adversaries has - usually - been rather difficult.In this work, we introduce a method for generating strong adversaries that can easily (and frequently) be transferred between different models. This method is then used to generate a large set of adversaries, based on which the effects of selected defense methods are experimentally assessed. At last, we introduce a novel, simple, yet effective approach to enhance the resilience of neural networks against adversaries and benchmark it against established defense methods. In contrast to the already existing methods, our proposed defense approach is much more efficient as it only requires a single additional forward-pass to achieve comparable performance results.

Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent - Steinhoff, Vera; Kerschke, Pascal; Aspar, Pelin; Trautmann, Heike; Grimme, Christian (Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI))
Multimodality is one of the biggest difficulties for optimization as local optima are often preventing algorithms from making progress. This does not only challenge local strategies that can get stuck. It also hinders meta-heuristics like evolutionary algorithms in convergence to the global optimum. In this paper we present a new concept of gradient descent, which is able to escape local traps. It relies on multiobjectivization of the original problem and applies the recently proposed and here slightly modified multi-objective local search mechanism MOGSA. We use a sophisticated visualization technique for multi-objective problems to prove the working principle of our idea. As such, this work highlights the transfer of new insights from the multi-objective to the single-objective domain and provides first visual evidence that multiobjectivization can link single-objective local optima in multimodal landscapes.

Why do you think that? Exploring Faithful Sentence-Level Rationales Without Supervision - Glockner, Max; Habernal, Ivan; Gurevych, Iryna (Findings of the Association for Computational Linguistics: EMNLP 2020)

1-MW Full-Bridge MMC for High-Current Low-Voltage (100V-400V) DC-Applications - Unruh, Roland; Schafmeister, Frank; Fröhleke, Norbert; Böcker, Joachim (PCIM Europe digital days 2020; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management)
A full-bridge modular multilevel converter (MMC) is compared to a half-bridge-based MMC for high-current low-voltage DC-applications such as electrolysis, arc welding or datacenters with DC-power distribution. Usually, modular multilevel converters are used in high-voltage DC-applications (HVDC) in the multiple kV-range, but to meet the needs of a high-current demand at low output voltage levels, the modular converter concept requires adaptations. In the proposed concept, the MMC is used to step-down the three-phase medium-voltage of 10 kV. Therefore, each module is extended by an LLC resonant converter to adapt to the specific electrolyzers DC-voltage range of 142-220V and to provide galvanic isolation. The proposed MMC converter with full-bridge modules uses half the number of modules compared to a half-bridge-based MMC while reducing the voltage ripple by 78% and capacitor losses by 64% by rearranging the same components to ensure identical costs and volume. For additional reliability, a new robust algorithm for balancing conduction losses during the bypass phase is presented.
Keywords: Cascaded H-Bridge; Solid-State Transformer; Capacitor voltage ripple; Zero sequence voltage; Full-Bridge

Dual Study Programmes as a Design Challenge: Identifying Areas for Improvement as a Starting Point for Interventions - Mordhorst, Lisa; Gössling, Bernd (EDeR. Educational Design Research)
The proportion of freshmen enrolled in dual study programmes has steadily increased in recent years. From the perspective of potential students, these programmes are highly attractive because they combine types of learning that used to be largely separate at an institutional level: vocational and academic learning. In training-integrated dual study programmes, different institutional contexts, governance regimes, teaching styles and learning environments make bridging these two worlds of learning a challenge for both educators and learners. However, these programmes also allow leeway for didactic innovation, through the cooperation of different types of educational institutions and through new ways of using available didactic methods, and for establishing a new relationship between higher education (HE) and vocational education and training (VET). This paper positions training-integrated dual study programmes as an object of design-based research (DBR). By developing and using an extended model for the pedagogic development of HEIs, “pädagogische Hochschulentwicklung” (Brahm, Jenert, & Euler, 2016a, p. 19; Euler, 2013, p. 360), the paper systematically identifies generic educational problems in these hybrids. Based on a literature review, this paper classifies and explains the design challenges at the level of the learning environment, the study programme and the organisation. The challenges revolve mainly around the cooperation and integration of HE and VET. The paper concludes with an outlook on future DBR projects designing dual studies.
Keywords: Dual study programmes; Design challenges; Pedagogic development of HEIs; Literature review; Study programme development; DBR cycle

Heat dissipation strategies for silicon carbide power SMDs and their use in different applications - Strothmann, Benjamin; Piepenbrock, Till; Schafmeister, Frank; Böcker, Joachim (PCIM Europe digital days 2020; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management)
Heat dissipation is a limiting factor in the performance of many power electronic components. Especially in the TO-263-7 package, which is used for several SiC-MOSFETs, the heat transfer must take place through the cross section of the printed circuit board (PCB) to the heatsink at the bottom side. Most commonly, thermal vias are used to form this path in a perpendicular direction through all PCB-layers. In a given soft- and hard switched example applications with the use of C3M0065090J SiC-MOSFETs, this conventional approach limited the component’s maximum heat dissipation to approx. 13 W. A recent alternative approach are massive copper blocks (”pedestals”) being integrated in PCBs and reaching from their top- to the bottom-side in relevant footprint areas under SMD-housed power semiconductors. Pedestals allowing to increase the heat dissipation in the given case to even 36 W. This step is achieved due to the clearly superior heat spreading capability of that massive thermal connection between SiC-MOSFET and heatsink. For the hard switched example application the number of switch-elements can be halved to one, by using the pedestal instead of thermal vias. Independently of optimizing the heat transfer path, the up-front avoidance of losses helps to stay within existing heat dissipation limits, of course. The dominant conduction losses of the mentioned soft-switched example application could be halved by changing to SiC-MOSFET types with significant lowered RDSon. By using pedestals and changing to SiC-MOSFETs with lowered RDSon, the number of switch-elements can also be halved for the soft switched application.

Behavioral Economics for Human-in-the-loop Control Systems Design: Overconfidence and the hot hand fallacy - Protte, Marius; Fahr, René; Quevedo, Daniel E. (IEEE Control Systems Magazine)
Successful design of human-in-the-loop control sys- tems requires appropriate models for human decision makers. Whilst most paradigms adopted in the control systems literature hide the (limited) decision capability of humans, in behavioral economics individual decision making and optimization processes are well-known to be affected by perceptual and behavioral biases. Our goal is to enrich control engineering with some insights from behavioral economics research through exposing such biases in control-relevant settings. This paper addresses the following two key questions: 1) How do behavioral biases affect decision making? 2) What is the role played by feedback in human-in-the-loop control systems? Our experimental framework shows how individuals behave when faced with the task of piloting an UAV under risk and uncertainty, paralleling a real-world decision-making scenario. Our findings support the notion of humans in Cyberphysical Systems underlying behavioral biases regardless of – or even because of – receiving immediate outcome feedback. We observe substantial shares of drone controllers to act inefficiently through either flying excessively (overconfident) or overly conservatively (underconfident). Furthermore, we observe human-controllers to self-servingly misinterpret random sequences through being subject to a “hot hand fallacy”. We advise control engineers to mind the human component in order not to compromise technological accomplishments through human issues.

Birth Without a Woman: Mary Shelley's Frankenstein in the Context of Eighteenth-Century Ideas on Birth, Motherhood and Midwifery - Schneider, Julia Christina (Transient Bodies in Anglophone Literature and Culture)

Reformation und Regierungskunst: Wahrheit als Grundlage normalisierender Macht bei Nietzsche und Foucault - Corall, Niklas (Nietzsche und die Reformation)

Verstehensgrundlagen diagnostizieren - Welche Wissenselemente fokussieren Lehrkräfte? - Dröse, Jennifer (Beiträge zum Mathematikunterricht 2020)

Textaufgaben lesen lernen – eine digital gestützte Einheit mit App - Dröse, Jennifer; Eisen, V.; Prediger, Susanne; Altieri, M.; Schellenbach, M.; Menning, R. (Mathematik lehren 223)

Übersetzung und Validierung einer deutschsprachigen Version des Sport Emotion Questionnaire (SEQ) - Wetzel, Änne; Weigelt, Matthias; Klingsieck, Katrin Birte (Diagnostica)
Zusammenfassung. Die vorliegende Studie befasst sich mit der Übersetzung und Validierung des englischsprachigen Sport Emotion Questionnaire (SEQ; Jones et al., 2005 ), der vorwettbewerblichen Emotionen von Sporttreibenden misst. In einer ersten Teilstudie wurde mittels einer Hin-Rück-Übersetzung und des Bilingual-Retest-Verfahrens ( n = 32) eine deutsche Version des SEQ (SEQ-d) erzeugt. In Studie 2 (Tennisspieler/innen, n = 116) zeigte sich jedoch eine vom Original abweichende Faktorstruktur, woraufhin der SEQ-d als dreidimensionale Kurzskala entwickelt wurde. Diese wurde in Studie 3 (Läufern/innen, n = 271) validiert. Die Kurzskala besitzt einen akzeptablen Fit (CFI = .950, RMSEA = .069, SRMR = .063) und eine interne Konsistenz von α = .84 (negative Emotionen), α = .86 (positive Emotionen), α = .87 (Anspannung). Durch Korrelationen mit anderen Emotionsmerkmalen konnte die konvergente Validität bestätigt werden. Die Kriteriumsvalidität wurde anhand wettkampf- und personenbezogener Zusatzparameter untersucht (bspw. Alter, Wettkampferfahrung…). Mit der deutschsprachigen Version des SEQ liegt ein ökonomisches und validiertes Messinstrument zur Erfassung vorwettbewerblicher Emotionen vor.
Keywords: Clinical Psychology

Übersetzung und Validierung einer deutschsprachigen Version des Sport Emotion Questionnaire (SEQ) - Wetzel, Änne; Weigelt, Matthias; Klingsieck, Katrin B. (Diagnostica)
Zusammenfassung. Die vorliegende Studie befasst sich mit der Übersetzung und Validierung des englischsprachigen Sport Emotion Questionnaire (SEQ; Jones et al., 2005 ), der vorwettbewerblichen Emotionen von Sporttreibenden misst. In einer ersten Teilstudie wurde mittels einer Hin-Rück-Übersetzung und des Bilingual-Retest-Verfahrens ( n = 32) eine deutsche Version des SEQ (SEQ-d) erzeugt. In Studie 2 (Tennisspieler/innen, n = 116) zeigte sich jedoch eine vom Original abweichende Faktorstruktur, woraufhin der SEQ-d als dreidimensionale Kurzskala entwickelt wurde. Diese wurde in Studie 3 (Läufern/innen, n = 271) validiert. Die Kurzskala besitzt einen akzeptablen Fit (CFI = .950, RMSEA = .069, SRMR = .063) und eine interne Konsistenz von α = .84 (negative Emotionen), α = .86 (positive Emotionen), α = .87 (Anspannung). Durch Korrelationen mit anderen Emotionsmerkmalen konnte die konvergente Validität bestätigt werden. Die Kriteriumsvalidität wurde anhand wettkampf- und personenbezogener Zusatzparameter untersucht (bspw. Alter, Wettkampferfahrung…). Mit der deutschsprachigen Version des SEQ liegt ein ökonomisches und validiertes Messinstrument zur Erfassung vorwettbewerblicher Emotionen vor.

Schreibherausforderungen: Ins Schreiben kommen und im Schreiben bleiben –die Selbstregulation beim Schreiben wissenschaftlicher Texte in den Qualifizierungsphasen. - Klingsieck, Katrin B.; Golombek, Christiane (HLZ – Herausforderung Lehrer*innenbildung)
Das Schreiben von wissenschaftlichen Texten ist mit einer Vielzahl von Herausforderungen verbunden, die die Bewältigung einer Schreibaufgabe häufig mühselig erscheinen lassen. Dieser Beitrag führt das wissenschaftliche Schreiben als eine Form des komplexen Problemlösens ein. Er betrachtet das wissenschaftliche Schreiben als ein rhetorisches Problem und zeigt auf, welche Ressourcen und Strategien im Rahmen des Schreibprozesses eingesetzt werden, um dieses Problem zu lösen. Der Fokus liegt dabei auf der Rolle der Selbstregulation beim wissenschaftlichen Schreiben. Aus prominenten Kompetenz- und Phasenmodellen des Schreibens abgeleitet, stellt der Beitrag grundlegende Strategien einer erfolgreichen Selbstregulation beim wissenschaftlichen Schreiben vor, die individuell eingesetzt werden können, um ins Schreiben zu kommen und im Schreiben zu bleiben.

Psychologie als Unterrichtsfach: Konzeption des Curriculums an der Universität Paderborn - Buhl, Heike M.; Scharlau, Ingrid; Patrzek, Justine; Hiller, Sara; Klingsieck, Katrin B. (Psychologiedidaktik und Evaluation XIII)
Keywords: Unterrichtsfach Psychologie

Measuring implemental delay in procrastination: Separating onset and sustained goal striving - Svartdal, Frode; Klingsieck, Katrin B.; Steel, Piers; Gamst-Klaussen, Thor (Personality and Individual Differences)

How Study Environments Foster Academic Procrastination: Overview and Recommendations - Svartdal, Frode; Dahl, Tove I.; Gamst-Klaussen, Thor; Koppenborg, Markus; Klingsieck, Katrin B. (Frontiers in Psychology)

Die angebliche Frage nach dem ‘Sein des Seienden’: An Unknown Husserlian Response to Heidegger’s ‘Question of Being’ - Luft, Sebastian; Janes, Jered (Transcending Reason. Heidegger on Rationality,)

Geschlecht als pädagogische Herausforderung?! - Daniel-Söltenfuß, Desiree

Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation - Kinoshita, Keisuke; von Neumann, Thilo; Delcroix, Marc; Nakatani, Tomohiro; Haeb-Umbach, Reinhold (Proc. Interspeech 2020)
Recently, the source separation performance was greatly improved by time-domain audio source separation based on dual-path recurrent neural network (DPRNN). DPRNN is a simple but effective model for a long sequential data. While DPRNN is quite efficient in modeling a sequential data of the length of an utterance, i.e., about 5 to 10 second data, it is harder to apply it to longer sequences such as whole conversations consisting of multiple utterances. It is simply because, in such a case, the number of time steps consumed by its internal module called inter-chunk RNN becomes extremely large. To mitigate this problem, this paper proposes a multi-path RNN (MPRNN), a generalized version of DPRNN, that models the input data in a hierarchical manner. In the MPRNN framework, the input data is represented at several (>_ 3) time-resolutions, each of which is modeled by a specific RNN sub-module. For example, the RNN sub-module that deals with the finest resolution may model temporal relationship only within a phoneme, while the RNN sub-module handling the most coarse resolution may capture only the relationship between utterances such as speaker information. We perform experiments using simulated dialogue-like mixtures and show that MPRNN has greater model capacity, and it outperforms the current state-of-the-art DPRNN framework especially in online processing scenarios.

Traceable learning effects by use of digital adaptive assistance in production - Gräßler, Iris; Roesmann, Daniel; Pottebaum, Jens (Procedia Manufacturing - Proceedings of the 10th Conference on Learning Factories, CLF2020, Band 45; 16. - 17. Apr. 2020)

Innovation management and strategic planning of innovative self-preparednes and self-Protection services - Gräßler, Iris; Pottebaum, Jens; Scholle, Philipp; Thiele, Henrik (ISPIM Conference Proceedings; 7. - 10. Jun. 2020)

Diskriminierung begegnen – Vielfalt gestalten : Veranstaltungsreihe von und für Studierende und Interessierte - Treder, Alexandra

Security-Oriented Fault-Tolerance in Systems Engineering: A Conceptual Threat Modelling Approach for Cyber-Physical Production Systems - Gräßler, Iris; Bodden, Eric; Pottebaum, Jens; Geismann, Johannes; Roesmann, Daniel (Advanced, Contemporary Control, Advances in Intelligent Systems and Computing)
Faults in the realization and usage of cyber-physical systems can cause significant security issues. Attackers might exploit vulnerabilities in the physical configurations, control systems, or accessibility through internet connections. For CPS, two challenges are combined: Firstly, discipline-specific security measures should be applied. Secondly, new measures have to be created to cover interdisciplinary impacts. For instance, faulty software configurations in cyber-physical production systems (CPPS) might allow attackers to manipulate the correct control of production processes impacting the quality of end products. From liability and publicity perspective, a worst-case scenario is that such a corrupted product is delivered to a customer. In this context, security-oriented fault-tolerance in Systems Engineering (SE) requires measures to evaluate interdisciplinary system designs with regard to potential scenarios of attacks. The paper at hand contributes a conceptual threat modelling approach to cover potential attack scenarios. The approach can be used to derive both system-level and discipline-specific security solutions. As an application case, issues are focused on which attackers intend to exploit vulnerabilities in a CPPS. The goal is to support systems engineers in verification and validation tasks regarding security-oriented fault-tolerance.

Immersive Abstraction: A new Morphology of Intuitive Interaction with System Models - Gräßler, Iris; Pottebaum, Jens (Proceedings of the Design Society: DESIGN Conference; 26. - 29. Okt. 2020)
Abstract The value of models is well recognised in product and systems engineering. Modelling languages and diagrams are used to capture mental models and to handle model complexity. Literature research indicates that there are only very few approaches to utilise the potential of virtual and augmented reality for supporting tasks in model based (systems) engineering. The paper at hand contributes a new morphology of intuitive interaction for Immersive Abstraction as a holistic approach to extend that coverage. It presents a holistic framework to categorise solutions and future research directions.

Entwicklung eines Prüfstands für die Bewertung von kompetenzbildenden Assistenzsystemen in Cyber-physischen Produktionssystemen - Gräßler, Iris; Roesmann, Daniel; Pottebaum, Jens (Frühjahrskongress 2020 - Digitaler Wandel, digitale Arbeit, digitaler Mensch?; 16. - 18. Mrz. 2020)

Produktdatenbasiertes, arbeitsgebundenes Lernen für und mit Augmented Reality in der Instandhaltung - Gräßler, Iris; Pottebaum, Jens; Taplick, Patrick; Roesmann, Daniel; Kamann, Markus (Frühjahrskongress 2020 - Digitaler Wandel, digitale Arbeit, digitaler Mensch?; 16. - 18. Mrz. 2020)

Informationsqualität in der Produktentwicklung: Modellbasiertes Systems Engineering mit expliziter Berücksichtigung von Unsicherheit - Pottebaum, Jens; Gräßler, Iris (Konstruktion)

Mit Methoden der Drama- und Erzählpädagogik Fremdsprachen lernen - Meyberg, Sora; Treder, Alexandra

Hunger (Eduardo Chillida) und Swingcolor - Schulze, Max (Provinz Editionen 2011-2020)
Keywords: Editionen; Kunst; Fotografie; Siebdruck; Farbattentat

Der Wunsch zu verschwinden - Schulze, Max (Salon #15)

Museen und Geschichtsunterricht - Hartung, Olaf

Mehr Barock wagen. Neuordnungen des Fürstbistums Paderborn aus dem Dreißigjährigen Krieg - Moritz, Tilman (Peter Paul Rubens und der Barock im Norden. Katalog zur Ausstellung im Erzbischöflichen Diözesanmuseum Paderborn)

P. O. Adiele: The Popes, the Catholic Church and the Transatlantic Enslavement of Black Africans 1418–1839. Hildesheim u. a. 2017 - Moritz, Tilman (Rottenburger Jahrbuch für Kirchengeschichte)

The Approximation of Invariant Sets in Infinite Dimensional Dynamical Systems - Gerlach, Raphael; Ziessler, Adrian (Advances in Dynamics, Optimization and Computation)
In this work we review the novel framework for the computation of finite dimensional invariant sets of infinite dimensional dynamical systems developed in [6] and [36]. By utilizing results on embedding techniques for infinite dimensional systems we extend a classical subdivision scheme [8] as well as a continuation algorithm [7] for the computation of attractors and invariant manifolds of finite dimensional systems to the infinite dimensional case. We show how to implement this approach for the analysis of delay differential equations and partial differential equations and illustrate the feasibility of our implementation by computing the attractor of the Mackey-Glass equation and the unstable manifold of the one-dimensional Kuramoto-Sivashinsky equation.

On the equivariance properties of self-adjoint matrices - Dellnitz, Michael; Gebken, Bennet; Gerlach, Raphael; Klus, Stefan (Dynamical Systems)
We investigate self-adjoint matrices A∈Rn,n with respect to their equivariance properties. We show in particular that a matrix is self-adjoint if and only if it is equivariant with respect to the action of a group Γ2(A)⊂O(n) which is isomorphic to ⊗nk=1Z2. If the self-adjoint matrix possesses multiple eigenvalues – this may, for instance, be induced by symmetry properties of an underlying dynamical system – then A is even equivariant with respect to the action of a group Γ(A)≃∏ki=1O(mi) where m1,…,mk are the multiplicities of the eigenvalues λ1,…,λk of A. We discuss implications of this result for equivariant bifurcation problems, and we briefly address further applications for the Procrustes problem, graph symmetries and Taylor expansions.

Vandalene - Schulze, Max

Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-Supervised Sound Event Detection - Ebbers, Janek; Haeb-Umbach, Reinhold (Proceedings of the Detection and Classification of Acoustic Scenes and Events 2020 Workshop (DCASE2020))
In this paper we present our system for the detection and classification of acoustic scenes and events (DCASE) 2020 Challenge Task 4: Sound event detection and separation in domestic environments. We introduce two new models: the forward-backward convolutional recurrent neural network (FBCRNN) and the tag-conditioned convolutional neural network (CNN). The FBCRNN employs two recurrent neural network (RNN) classifiers sharing the same CNN for preprocessing. With one RNN processing a recording in forward direction and the other in backward direction, the two networks are trained to jointly predict audio tags, i.e., weak labels, at each time step within a recording, given that at each time step they have jointly processed the whole recording. The proposed training encourages the classifiers to tag events as soon as possible. Therefore, after training, the networks can be applied to shorter audio segments of, e.g., 200ms, allowing sound event detection (SED). Further, we propose a tag-conditioned CNN to complement SED. It is trained to predict strong labels while using (predicted) tags, i.e., weak labels, as additional input. For training pseudo strong labels from a FBCRNN ensemble are used. The presented system scored the fourth and third place in the systems and teams rankings, respectively. Subsequent improvements allow our system to even outperform the challenge baseline and winner systems in average by, respectively, 18.0% and 2.2% event-based F1-score on the validation set. Source code is publicly available at https://github.com/fgnt/pb_sed.

Personalökonomie und Personalpolitik: Grundlagen einer evidenzbasierten Praxis - Schneider, Martin; Sadowski, Dieter; Frick, Bernd; Warning, Susanne

Gier und andere Tugenden: Widersprüchliche Bewertungen der Marktwirtschaft ain Oliver Stones "Wall Street" - Schneider, Martin (Erzähltes Geld: Finanzmärkte und Krisen in Literatur, Film und Medien)

Der Einfluss von gesundheitsförderlichen Maßnahmen auf die Kommunikationsstrukturen: Nutzen für die Arbeitsproduktivität? - Meier, Heiko; Auer, Thorsten Fabian; Sennefelder, Lisa (Journal Gesundheitsförderung für Akteurinnen und Akteure aus Politik, Wissenschaft und Praxis)

Zwischen romantischem Fragment und Skizze/n der Moderne. Zum medialen Realismus von Wilhelm Raabes Wer kann es wenden? - Gretz, Daniela (JbRG)

Intergenerationelle Beziehungen in der Familie - Buhl, Heike M.; Sommer, Sabrina (Psychotherapie im Alter)
Beziehungen zwischen Erwachsenen und ihren Eltern sind durch Interdependenzen und Dependenzen gekennzeichnet. Während das Zusammenleben von Familien mit Kindern im mittleren Erwachsenenalter dabei ganz überwiegend durch Interdependenz geprägt ist, nehmen im Alter Dependenzen durch gesundheitliche Beeinträchtigungen der Eltern zu. Mit Blick darauf werden im Artikel behaviorale, kognitive und emotionale Merkmale von Eltern-Kind-Beziehungen erläutert und theoretisch in zentrale Konzepte eingebettet. Das Verhalten ist durch Solidarität zwischen den Generationen, aber auch durch Aspekte des Einflusses innerhalb der Beziehung und aufeinander, gekennzeichnet. Um Familienkognitionen zu beschreiben, werden die verwandten Konzepte der Individuation und der filialen Reife herangezogen. Verhalten, wie auch Kognitionen, sind eng mit dem dritten Beziehungsmerkmal, der Affektivität verknüpft, das neben positiven auch negative Gefühle sowie Ambivalenzen umfasst.
Keywords: General Earth and Planetary Sciences; General Environmental Science

Das Leichte Lexikon des Glaubens

Material Specific Predicting of the Optimal Joining Parameters for the Screw Blind Rivet Joining Process - Moritzer, Elmar; Hillemeyer, Johannes (73rd Annual Assembly of International Institute of Welding (IIW) and International Conference)

Differenz - Kammeyer, Katharina (Inklusive Religionspädagogik der Vielfalt. Konzeptionelle Grundlagen und didaktische Konkretionen)

Synthesizing and Integrating Research on IT-Based Value Co-Creation: A Meta-Analysis - Mandrella, M.; Trang, S.; Kolbe, L. M. (Journal of the Association for Information Systems)

Replication of the Unified Model of Information Security Policy Compliance - Masuch, K.; Hengstler, S.; Trang, S.; Brendel, A. (AIS Transactions on Replication Research)

Towards a Greater Diversity of Replication Studies - Brendel, B.; Greulich, S.; Trang, S.; Niederman, F. (AIS Transactions on Replication Research)

One app to trace them all? Examining app specifications for mass acceptance of contact-tracing apps - Trang, S.; Trenz, M.; Weiger, W.; Tarafdar, M.; Cheung, C. (European Journal of Information Systems)

Die Eigenen täuschen: Szenen eines Kriegsausbruchs nach wahrer Geschichte - Halding, Ole; Hartung, Olaf

Development Framework for Context-Aware Augmented Reality Applications - Krings, Sarah Claudia; Yigitbas, Enes; Jovanovikj, Ivan; Sauer, Stefan; Engels, Gregor (Proceedings of the 12th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2020))

"[...] eine Sammelstelle für Tierseelenkunde". Wie eine Wissenschaftszeitschrift um 1900 die Mensch/Tier-Grenze neu zu ordnen versucht - Hagemann, Philipp; Kreißl, Steffen; Reinke, Paul; Wagner, Alexander (Tierstudien)

Peer Mentoring an der Fakultät für Wirtschaftswissenschaften - Einblicke in ein Schulungskonzept für Peer Mentor*innen - Sloane, Hannah; Kremer, H.-Hugo (Mentoring in Hochschuldidaktik und -praxis - Eine Reflexion wissenschaftlicher Erkenntnisse und praktischer Erfahrungen)

Gotteswort und Menschenwort. - Meyer zu Hörste-Bührer, Raphaela (Schriftbindung evangelischer Theologie, Forum Theologische Literaturzeitung 37)

Autorität der Schrift im Verhältnis zu Rezeptionsprozessen. - Meyer zu Hörste-Bührer, Raphaela (Schriftbindung evangelischer Theologie, Forum Theologische Literaturzeitung 37)

Schrift und Schriftauslegung in relationaler Perspektive. - Meyer zu Hörste-Bührer, Raphaela (Schriftbindung evangelischer Theologie, Forum Theologische Literaturzeitung 37)

Pluralität und Einheit der Schrift. - Meyer zu Hörste-Bührer, Raphaela (Schriftbindung evangelischer Theologie, Forum Theologische Literaturzeitung 37)

Schriftbindung evangelischer Theologie. Theorieelemente aus interdisziplinären Gesprächen.

Die Gewalt der Ethik? Überlegungen zu Ausübung und Legitimation struktureller Gewalt durch die theologische Ethik. - Meyer zu Hörste-Bührer, Raphaela (ides quaerens intellectum. Festschrift für Walter Dietz.)

Digitale antike Ethik – Gründung des „Journals of Ethics in Antiquity and Christianity (JEAC)“ - Meyer zu Hörste-Bührer, Raphaela (Zeitschrift für Evangelische Ethik 64/1)

More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization - Bossek, Jakob; Neumann, Frank; Peng, Pan; Sudholt, Dirk (Proceedings of the Genetic and Evolutionary Computation Conference)
Dynamic optimization problems have gained significant attention in evolutionary computation as evolutionary algorithms (EAs) can easily adapt to changing environments. We show that EAs can solve the graph coloring problem for bipartite graphs more efficiently by using dynamic optimization. In our approach the graph instance is given incrementally such that the EA can reoptimize its coloring when a new edge introduces a conflict. We show that, when edges are inserted in a way that preserves graph connectivity, Randomized Local Search (RLS) efficiently finds a proper 2-coloring for all bipartite graphs. This includes graphs for which RLS and other EAs need exponential expected time in a static optimization scenario. We investigate different ways of building up the graph by popular graph traversals such as breadth-first-search and depth-first-search and analyse the resulting runtime behavior. We further show that offspring populations (e. g. a (1 + {$λ$}) RLS) lead to an exponential speedup in {$λ$}. Finally, an island model using 3 islands succeeds in an optimal time of {$Θ$}(m) on every m-edge bipartite graph, outperforming offspring populations. This is the first example where an island model guarantees a speedup that is not bounded in the number of islands.
Keywords: dynamic optimization; evolutionary algorithms; running time analysis; theory

Evolving Sampling Strategies for One-Shot Optimization Tasks - Bossek, Jakob; Doerr, Carola; Kerschke, Pascal; Neumann, Aneta; Neumann, Frank (Parallel Problem Solving from Nature (PPSN XVI))
One-shot optimization tasks require to determine the set of solution candidates prior to their evaluation, i.e., without possibility for adaptive sampling. We consider two variants, classic one-shot optimization (where our aim is to find at least one solution of high quality) and one-shot regression (where the goal is to fit a model that resembles the true problem as well as possible). For both tasks it seems intuitive that well-distributed samples should perform better than uniform or grid-based samples, since they show a better coverage of the decision space. In practice, quasi-random designs such as Latin Hypercube Samples and low-discrepancy point sets are indeed very commonly used designs for one-shot optimization tasks. We study in this work how well low star discrepancy correlates with performance in one-shot optimization. Our results confirm an advantage of low-discrepancy designs, but also indicate the correlation between discrepancy values and overall performance is rather weak. We then demonstrate that commonly used designs may be far from optimal. More precisely, we evolve 24 very specific designs that each achieve good performance on one of our benchmark problems. Interestingly, we find that these specifically designed samples yield surprisingly good performance across the whole benchmark set. Our results therefore give strong indication that significant performance gains over state-of-the-art one-shot sampling techniques are possible, and that evolutionary algorithms can be an efficient means to evolve these.
Keywords: Continuous optimization; Fully parallel search; One-shot optimization; Regression; Surrogate-assisted optimization

The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics - Bossek, Jakob; Casel, Katrin; Kerschke, Pascal; Neumann, Frank (Proceedings of the Genetic and Evolutionary Computation Conference)
Several important optimization problems in the area of vehicle routing can be seen as variants of the classical Traveling Salesperson Problem (TSP). In the area of evolutionary computation, the Traveling Thief Problem (TTP) has gained increasing interest over the last 5 years. In this paper, we investigate the effect of weights on such problems, in the sense that the cost of traveling increases with respect to the weights of nodes already visited during a tour. This provides abstractions of important TSP variants such as the Traveling Thief Problem and time dependent TSP variants, and allows to study precisely the increase in difficulty caused by weight dependence. We provide a 3.59-approximation for this weight dependent version of TSP with metric distances and bounded positive weights. Furthermore, we conduct experimental investigations for simple randomized local search with classical mutation operators and two variants of the state-of-the-art evolutionary algorithm EAX adapted to the weighted TSP. Our results show the impact of the node weights on the position of the nodes in the resulting tour.
Keywords: dynamic optimization; evolutionary algorithms; running time analysis; theory

Dynamic Bi-Objective Routing of Multiple Vehicles - Bossek, Jakob; Grimme, Christian; Trautmann, Heike (Proceedings of the Genetic and Evolutionary Computation Conference)
In practice, e.g. in delivery and service scenarios, Vehicle-Routing-Problems (VRPs) often imply repeated decision making on dynamic customer requests. As in classical VRPs, tours have to be planned short while the number of serviced customers has to be maximized at the same time resulting in a multi-objective problem. Beyond that, however, dynamic requests lead to the need for re-planning of not yet realized tour parts, while already realized tour parts are irreversible. In this paper we study this type of bi-objective dynamic VRP including sequential decision making and concurrent realization of decisions. We adopt a recently proposed Dynamic Evolutionary Multi-Objective Algorithm (DEMOA) for a related VRP problem and extend it to the more realistic (here considered) scenario of multiple vehicles. We empirically show that our DEMOA is competitive with a multi-vehicle offline and clairvoyant variant of the proposed DEMOA as well as with the dynamic single-vehicle approach proposed earlier.
Keywords: decision making; dynamic optimization; evolutionary algorithms; multi-objective optimization; vehicle routing

Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection - Bossek, Jakob; Kerschke, Pascal; Trautmann, Heike (2020 IEEE Congress on Evolutionary Computation (CEC))
The Traveling-Salesperson-Problem (TSP) is arguably one of the best-known NP-hard combinatorial optimization problems. The two sophisticated heuristic solvers LKH and EAX and respective (restart) variants manage to calculate close-to optimal or even optimal solutions, also for large instances with several thousand nodes in reasonable time. In this work we extend existing benchmarking studies by addressing anytime behaviour of inexact TSP solvers based on empirical runtime distributions leading to an increased understanding of solver behaviour and the respective relation to problem hardness. It turns out that performance ranking of solvers is highly dependent on the focused approximation quality. Insights on intersection points of performances offer huge potential for the construction of hybridized solvers depending on instance features. Moreover, instance features tailored to anytime performance and corresponding performance indicators will highly improve automated algorithm selection models by including comprehensive information on solver quality.

Initial Design Strategies and Their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB - Bossek, Jakob; Doerr, Carola; Kerschke, Pascal (Proceedings of the Genetic and Evolutionary Computation Conference)
Sequential model-based optimization (SMBO) approaches are algorithms for solving problems that require computationally or otherwise expensive function evaluations. The key design principle of SMBO is a substitution of the true objective function by a surrogate, which is used to propose the point(s) to be evaluated next. SMBO algorithms are intrinsically modular, leaving the user with many important design choices. Significant research efforts go into understanding which settings perform best for which type of problems. Most works, however, focus on the choice of the model, the acquisition function, and the strategy used to optimize the latter. The choice of the initial sampling strategy, however, receives much less attention. Not surprisingly, quite diverging recommendations can be found in the literature. We analyze in this work how the size and the distribution of the initial sample influences the overall quality of the efficient global optimization (EGO) algorithm, a well-known SMBO approach. While, overall, small initial budgets using Halton sampling seem preferable, we also observe that the performance landscape is rather unstructured. We furthermore identify several situations in which EGO performs unfavorably against random sampling. Both observations indicate that an adaptive SMBO design could be beneficial, making SMBO an interesting test-bed for automated algorithm design.
Keywords: continuous black-box optimization; design of experiments; initial design; sequential model-based optimization

Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions - Bossek, Jakob; Neumann, Aneta; Neumann, Frank (Parallel Problem Solving from Nature (PPSN XVI))
The Traveling Salesperson Problem (TSP) is one of the best-known combinatorial optimisation problems. However, many real-world problems are composed of several interacting components. The Traveling Thief Problem (TTP) addresses such interactions by combining two combinatorial optimisation problems, namely the TSP and the Knapsack Problem (KP). Recently, a new problem called the node weight dependent Traveling Salesperson Problem (W-TSP) has been introduced where nodes have weights that influence the cost of the tour. In this paper, we compare W-TSP and TTP. We investigate the structure of the optimised tours for W-TSP and TTP and the impact of using each others fitness function. Our experimental results suggest (1) that the W-TSP often can be solved better using the TTP fitness function and (2) final W-TSP and TTP solutions show different distributions when compared with optimal TSP or weighted greedy solutions.
Keywords: Evolutionary algorithms; Node weight dependent TSP; Traveling Thief Problem

Towards Decision Support in Dynamic Bi-Objective Vehicle Routing - Bossek, Jakob; Grimme, Christian; Rudolph, Günter; Trautmann, Heike (2020 IEEE Congress on Evolutionary Computation (CEC))
We consider a dynamic bi-objective vehicle routing problem, where a subset of customers ask for service over time. Therein, the distance traveled by a single vehicle and the number of unserved dynamic requests is minimized by a dynamic evolutionary multi-objective algorithm (DEMOA), which operates on discrete time windows (eras). A decision is made at each era by a decision-maker, thus any decision depends on irreversible decisions made in foregoing eras. To understand effects of sequences of decision-making and interactions/dependencies between decisions made, we conduct a series of experiments. More precisely, we fix a set of decision-maker preferences D and the number of eras n{$<$}inf{$>$}t{$<$}/inf{$>$} and analyze all $|D|\^{n_t}$ combinations of decision-maker options. We find that for random uniform instances (a) the final selected solutions mainly depend on the final decision and not on the decision history, (b) solutions are quite robust with respect to the number of unvisited dynamic customers, and (c) solutions of the dynamic approach can even dominate solutions obtained by a clairvoyant EMOA. In contrast, for instances with clustered customers, we observe a strong dependency on decision-making history as well as more variance in solution diversity.

Evolving Diverse Sets of Tours for the Travelling Salesperson Problem - Do, Anh Viet; Bossek, Jakob; Neumann, Aneta; Neumann, Frank (Proceedings of the Genetic and Evolutionary Computation Conference)
Evolving diverse sets of high quality solutions has gained increasing interest in the evolutionary computation literature in recent years. With this paper, we contribute to this area of research by examining evolutionary diversity optimisation approaches for the classical Traveling Salesperson Problem (TSP). We study the impact of using different diversity measures for a given set of tours and the ability of evolutionary algorithms to obtain a diverse set of high quality solutions when adopting these measures. Our studies show that a large variety of diverse high quality tours can be achieved by using our approaches. Furthermore, we compare our approaches in terms of theoretical properties and the final set of tours obtained by the evolutionary diversity optimisation algorithm.
Keywords: diversity maximisation; evolutionary algorithms; travelling salesperson problem

Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem - Roostapour, Vahid; Bossek, Jakob; Neumann, Frank (Proceedings of the 2020 Genetic and Evolutionary Computation Conference)
Evolutionary algorithms (EAs) are general-purpose problem solvers that usually perform an unbiased search. This is reasonable and desirable in a black-box scenario. For combinatorial optimization problems, often more knowledge about the structure of optimal solutions is given, which can be leveraged by means of biased search operators. We consider the Minimum Spanning Tree (MST) problem in a single- and multi-objective version, and introduce a biased mutation, which puts more emphasis on the selection of edges of low rank in terms of low domination number. We present example graphs where the biased mutation can significantly speed up the expected runtime until (Pareto-)optimal solutions are found. On the other hand, we demonstrate that bias can lead to exponential runtime if "heavy" edges are necessarily part of an optimal solution. However, on general graphs in the single-objective setting, we show that a combined mutation operator which decides for unbiased or biased edge selection in each step with equal probability exhibits a polynomial upper bound - as unbiased mutation - in the worst case and benefits from bias if the circumstances are favorable.
Keywords: biased mutation; evolutionary algorithms; minimum spanning tree problem; runtime analysis

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem - Seiler, Moritz; Pohl, Janina; Bossek, Jakob; Kerschke, Pascal; Trautmann, Heike (Parallel Problem Solving from Nature (PPSN XVI))
In this work we focus on the well-known Euclidean Traveling Salesperson Problem (TSP) and two highly competitive inexact heuristic TSP solvers, EAX and LKH, in the context of per-instance algorithm selection (AS). We evolve instances with nodes where the solvers show strongly different performance profiles. These instances serve as a basis for an exploratory study on the identification of well-discriminating problem characteristics (features). Our results in a nutshell: we show that even though (1) promising features exist, (2) these are in line with previous results from the literature, and (3) models trained with these features are more accurate than models adopting sophisticated feature selection methods, the advantage is not close to the virtual best solver in terms of penalized average runtime and so is the performance gain over the single best solver. However, we show that a feature-free deep neural network based approach solely based on visual representation of the instances already matches classical AS model results and thus shows huge potential for future studies.
Keywords: Automated algorithm selection; Deep learning; Feature-based approaches; Traveling Salesperson Problem

A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms - Bossek, Jakob; Kerschke, Pascal; Trautmann, Heike (Applied Soft Computing)
We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs – both to be minimized – is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers. \textbullet The multi-objective perspective is naturally generalizable to multiple objectives. \textbullet Proof of relationship between HV and the PAR in the considered bi-objective space. \textbullet New insights into complementary behavior of stochastic optimization algorithms.
Keywords: Algorithm selection; Combinatorial optimization; Multi-objective optimization; Performance measurement; Traveling Salesperson Problem

Benchmarking in Optimization: Best Practice and Open Issues - Bartz-Beielstein, Thomas; Doerr, Carola; van den Berg, Daan; Bossek, Jakob; Chandrasekaran, Sowmya; Eftimov, Tome; Fischbach, Andreas; Kerschke, Pascal; Cava, William La; Lopez-Ibanez, Manuel; Malan, Katherine M.; Moore, Jason H.; et al. (Corr)

Geschichte(n) der deutschen Migrationsgesellschaft. Jugendliche erzählen begründete historische Geschichten Eine Unterrichtsreihe für das Portal Zwischentöne.info - Fastlabend-Vargas, Daniel

Erinnerung und Identität: Literarische Konstruktionen in Doeschka Meijsings Prosa - Lammer, Christina