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Attentive cognitive agents for real-time virtual environments
No full textVirtuelle Umgebungen sind ein effizientes Trainingswerkzeug, besonders wenn Trainingsszenarien durch die Simulation von intelligenten virtuellen Agenten (IVA) unterstützt werden. Dafür muss das Agentenverhalten plausibel und steuerbar sein, um die Immersion nicht zu mindern und das Trainingsziel zu unterstützen. Methoden, mit denen diese Anforderungen erfüllt werden, können jedoch nicht beliebig komplex sein, da oft mehrere Agenten in Echtzeit simuliert werden müssen. Im Rahmen dieser Arbeit stellt sich somit die Aufgabe eine Lösung zu entwickeln, welche die Anforderungen an Plausibilität, Kontrollierbarkeit und Skalierbarkeit zusammen adressiert. Die Plausibilität wird dabei durch das Simulieren kognitiver Prozesse erreicht. Ein Kernelement der entwickelten leichtgewichtigen kognitiven Agentenarchitektur ist ein Persönlichkeitsprofil, das sich auf alle anderen kognitiven Prozesse auswirkt. Somit kann konsistentes, individualisiertes Verhalten erzeugt werden, welches zusätzlich mit Hilfe eines entwickelten, formalen Abbildungsprozesses aus psychologischen Persönlichkeitsstudien abgeleitet werden kann. Durch die Kopplung des Profils mit Emotionen kann das Verhalten dynamisch an die Gegebenheiten eines Agenten angepasst werden. Welche Aktion ein Agent in einer Situation auswählt, beeinflusst ebenfalls die Glaubwürdigkeit. Ein wichtiger Bestandteil dieses Auswahlprozesses ist das Wissen, das ein Agent über seine Umgebung besitzt. Um eine plausible Wissensbasis bereit zu stellen, wurde ein Perzeptionsmodul konzipiert und integriert, das eine einheitliche Sensorschnittstelle definiert und Informationen in einem hierarchischen Gedächtnis durch einen Aufmerksamkeitsprozess verwaltet. Die realisierte Architektur erlaubt erstmalig die Simulation kognitiver Agenten, die gleichzeitig kontrollierbar und in Echtzeit berechenbar sind. Demonstriert wird dies u. a. durch die Umsetzung als Software-Architektur (CAARVE) und eine damit entwickelte agentenbasierte Verkehrssimulation. Die entwickelten Ideen und deren Realisierung wurden im Rahmen der Arbeit anhand verschiedener Strategien evaluiert. Es wird gezeigt wie CAARVE-Agenten, anhand ihrer Persönlichkeiten und Emotionen, verschiedene Verkehrssituationen glaubwürdig auflösen. Die Kontrollierbarkeit und Anpassungsfähigkeit wird ebenfalls in Evaluationsszenarien demonstriert. Die Skalierbarkeit wird durch die Simulation von 200 Agenten in Echtzeit (50 FPS) nachgewiesen. Die Ergebnisse zeigen, dass eine Architektur für das Generieren von plausiblem, kontrollierbarem und echtzeitfähigem Agentenverhalten erfolgreich realisiert wurde. Damit stellt diese Arbeit fundamentale Grundlagen für diejenigen bereit, die kognitive IVA in Echtzeitanwendungen einsetzen wollen.Intelligent virtual agents provide a framework for simulating more life-like behavior and increasing plausibility in virtual training environments. They can improve the learning process if they portray believable behavior that can also be controlled to support the training objectives. In the context of this thesis, cognitive agents are considered a subset of intelligent virtual agents (IVA) with the focus on emulating cognitive processes to achieve believable behavior. The complexity of employed algorithms, however, is often limited since multiple agents need to be simulated in real-time. Available solutions focus on a subset of the indicated aspects: plausibility, controllability, or real-time capability (scalability). Within this thesis project, an agent architecture for attentive cognitive agents is developed that considers all three aspects at once. The result is a lightweight cognitive agent architecture that is customizable to application-specific requirements. A generic trait-based personality model influences all cognitive processes, facilitating the generation of consistent and individual behavior. An additional mapping process provides a formalized mechanism to transfer results of psychological studies to the architecture. Personality profiles are combined with an emotion model to achieve situational behavior adaptation. Which action an agent selects in a situation also influences plausibility. An integral element of this selection process is an agent's knowledge about its world. Therefore, synthetic perception is modeled and integrated into the architecture to provide a credible knowledge base. The developed perception module includes a unified sensor interface, a memory hierarchy, and an attention process. With the presented realization of the architecture (CAARVE), it is possible for the first time to simulate cognitive agents, whose behaviors are simultaneously computable in real-time and controllable. The architecture's applicability is demonstrated by integrating an agent-based traffic simulation built with CAARVE into a bicycle simulator for road-safety education. The developed ideas and their realization are evaluated within this work using different strategies and scenarios. For example, it is shown how CAARVE agents utilize personality profiles and emotions to plausibly resolve deadlocks in traffic simulations. Controllability and adaptability are demonstrated in additional scenarios. Using the realization, 200 agents can be simulated in real-time (50 FPS), illustrating scalability. The achieved results verify that the developed architecture can generate plausible and controllable agent behavior in real-time. The presented concepts and realizations provide sound fundamentals to everyone interested in simulating IVA in real-time environments
Direct detection of atomic oxygen on the dayside and nightside of Venus
No full textAtomic oxygen is a key species in the mesosphere and thermosphere of Venus. It peaks in the transition region between the two dominant atmospheric circulation patterns, the retrograde super-rotating zonal flow below 70 km and the subsolar to antisolar flow above 120 km altitude. However, past and current detection methods are indirect and based on measurements of other molecules in combination with photochemical models. Here, we show direct detection of atomic oxygen on the dayside as well as on the nightside of Venus by measuring its ground-state transition at 4.74 THz (63.2 µm). The atomic oxygen is concentrated at altitudes around 100 km with a maximum column density on the dayside where it is generated by photolysis of carbon dioxide and carbon monoxide. This method enables detailed investigations of the Venusian atmosphere in the region between the two atmospheric circulation patterns in support of future space missions to Venus
How Do Female Entrepreneurs Differ From Male Entrepreneurs? Distinguishing Personality Traits Throughout the Entrepreneurial Journey
Get PDFThis study addresses the underrepresentation of women and the so-far neglected process perspective in empirical entrepreneurial research. It aims to identify the personality traits that differentiate successful female entrepreneurs from their less successful peers and to determine which traits are crucial for pre-launch, launch, and post-launch success. Independent t-tests on 305 female entrepreneurs (and 476 male entrepreneurs) from the DACH region highlight the role of self-efficacy, proactivity, locus of control, and need for achievement for female entrepreneurs. Multiple regression analyses further reveal the importance of self-efficacy for every phase of women’s entrepreneurial journey. While the need for autonomy was critical during pre-launch and launch, locus of control significantly predicted female entrepreneurial success in the pre-launch and post-launch phases. Contrary to previous research, risk-taking was not a crucial trait for female entrepreneurs when compared to their male counterparts, while both showed similar levels of need for autonomy, proactivity, need for achievement, perseverance, self-control, and locus of control. The study offers valuable insights into successful entrepreneurship and highlights the need for female- and phase-specific support programs to enhance self-efficacy among female entrepreneurs
Lentiviral Micro-dystrophin Gene Treatment into Late-stage mdx Mice for Duchenne Muscular Dystrophy Disease
No full textZur Entschädigung der Opfer sexuellen Kindesmissbrauchs im System der sozialen Sicherung
No full textBiopolymerModell: Neuer Zugang zur Analyse von Biopolymeren - Kombination experimenteller Methoden mit chemometrischer Modellierung: Sachbericht zum Verwendungsnachweis : Zuordnung F&E Programm: FHprofUnt 2018 : Laufzeit des Vorhabens: ursprünglich bewilligt vom 01.07.2019 bis 30.06.2022; verlängert bis 30.04.2023
No full textForesee - recognising signs, devising solutions, shaping the future
No full textForesee means developing visions for the future and helping to shape them responsibly in close exchange between applied science, society and business. This is an important concern for the Hochschule Bonn-Rhein-Sieg. The H-BRS has broken new ground in teaching, research and transfer and set new trends - for example in the fields of sustainability, energy transition or cybersecurity. The Annual Report 2022/23 provides an overview of the most important topics in the areas of research, teaching, studies and cooperation
Pump Up Password Security! Evaluating and Enhancing Risk-Based Authentication on a Real-World Large-Scale Online Service
Get PDFRisk-based authentication (RBA) aims to protect users against attacks involving stolen passwords. RBA monitors features during login, and requests re-authentication when feature values widely differ from those previously observed. It is recommended by various national security organizations, and users perceive it more usable than and equally secure to equivalent two-factor authentication. Despite that, RBA is still used by very few online services. Reasons for this include a lack of validated open resources on RBA properties, implementation, and configuration. This effectively hinders the RBA research, development, and adoption progress.
To close this gap, we provide the first long-term RBA analysis on a real-world large-scale online service. We collected feature data of 3.3 million users and 31.3 million login attempts over more than 1 year. Based on the data, we provide (i) studies on RBA’s real-world characteristics plus its configurations and enhancements to balance usability, security, and privacy; (ii) a machine learning–based RBA parameter optimization method to support administrators finding an optimal configuration for their own use case scenario; (iii) an evaluation of the round-trip time feature’s potential to replace the IP address for enhanced user privacy; and (iv) a synthesized RBA dataset to reproduce this research and to foster future RBA research. Our results provide insights on selecting an optimized RBA configuration so that users profit from RBA after just a few logins. The open dataset enables researchers to study, test, and improve RBA for widespread deployment in the wild
How AI Learns the Bundeswehr’s “Innere Führung”: Value-Based Engineering with IEEE7000(TM)-2021
No full textThe increasing ubiquity of Artificial Intelligence (AI) poses significant political consequences. The rapid proliferation of AI over the past decade has prompted legislators and regulators to attempt to contain AI’s technological consequences. For Germany, relevant design requirements have been expressed by the European Commission’s High-Level Expert Group on Artificial Intelligence (HLEG AI), and, at the national level, by the German government’s Data Ethics Commission (DEK) as well as the German Bundestag’s Commission of Inquiry on Artificial Intelligence (EKKI)
