239 research outputs found
Multidisciplinary perspectives on Artificial Intelligence and the law
This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio
Development and evaluation of a behavior change support system targeting learning behavior: a technology-based approach to complement the education of future executives using persuasive systems in higher education
Learning is crucial in today's information societies, and the need for comprehensive and accessible support systems to enhance learning competencies is increasingly evident. In this context, this dissertation provides descriptive knowledge about the demands for such a system, aiming to train higher education students and equip them with learning competencies. Drawing on design science research, the dissertation addresses the identified demands, considers technical frameworks and psychological models to design technology-based artifacts. Against this background, the dissertation provides a pragmatic contribution through novel artifacts in form of Behavior Change Support Systems targeting self-regulated learning in higher education. The evaluation of these artifacts extends prior design knowledge through specific recommendations, including design principles, that can guide the implementation of Behavior Change Support Systems and further technology-based interventions in higher education. These recommendations aim to promote the development of necessary competencies within the higher education context
Konzeption und Realisierung eines Multiagentensystems zur Unterstützung von Entscheidungsträgern bei der Bewältigung von Erdbebenkatastrophen
Weltweit stellen Großschadensereignisse aufgrund von Naturkatastrophen Gesellschaften vor schwer zu bewältigende Probleme. Selbst in Industrienation, die landesweit über ausreichende Ressourcen verfügen, ist das Krisenmanagement in einer betroffenen Region oft eine Herausforderung, wie der Hurrikan Katrina 2005 in den USA oder das Oderhochwasser 1997 in Deutschland zeigten. Bei Erdbebenkatastrophen ist ein zeitnahes Krisenmanagement entscheidend für eine Minimierung der Schäden. Die Orte, die potenziell gefährdet sind, lassen sich meist gut eingrenzen. Es gibt allerdings aktuell keine Möglichkeit, Starkbeben mit einem entsprechenden Schadensumfang frühzeitig vorauszusehen. Die Optimierung der Koordination von Einsatzkräften hat das Potenzial, die Bewältigung solcher Großschadensereignisse deutlich zu verbessern.
Aufbauend auf den Ergebnissen vorangegangener Forschung zum Management von Erdbebenkatastrophen am Institut für Technologie und Management im Baubetrieb wurde in der vorliegenden Arbeit ein Entscheidungsunterstützungssystem für die Mitarbeiter einer Einsatzleitstelle geschaffen. In einem theoretischen Teil werden mögliche Hilfestellungen untersucht und bewertet, deren praktischer Nutzen durch die Umsetzung in einem Programm, dem Disaster Management Tool (DMT), evaluiert wird. Ein Modell des Entscheidungsprozesses von Personen aus dem Zivilschutz dient als Anhaltspunkt für mögliche Hilfestellungen sowie deren Präsentation in der Benutzungsoberfläche des Systems.
Die Entscheidungshilfen basieren auf der Auswertung einer Faktenbasis durch Algorithmen und Regeln, die in einer Wissensbasis abgelegt sind. Die Regeln beruhen auf Literaturrecherchen, aber insbesondere auf dem Expertenwissen von Zivilschutzmitarbeitern, welches in Befragungen erhoben wurde. Die im System genutzte Fakten- und Wissensbasis zeichnet sich vor allem durch ihre Fähigkeit zur Verarbeitung unscharfer Informationen aus. Die Implementierung der theoretischen Modelle zur Entscheidungsunterstützung im DMT basiert auf dem Konzept eines Multiagentensystems. Das System dient, aufgrund seiner auf Standards basierenden Plattform und der Nutzung offener Datenformate, auch als Machbarkeitsstudie für das Design einer flexiblen und interoperablen Systemarchitektur. Die gewonnenen Erkenntnisse beschränken sich dabei nicht auf das Katastrophenmanagement nach Starkbeben, sondern lassen sich auch auf Schadensereignisse aufgrund anderer Ursachen übertragen
Komponentenbasierte dynamische Modellierung von Energiesystemen und Energiemanagement-Strategien für ein intelligentes Stromnetz im Heimbereich
The motivation of this work is to present an energy cost reduction concept in a home area power network (HAPN) with intelligent generation and flexible load demands. This study endeavors to address the energy management system (EMS) and layout-design challenges faced by HAPN through a systematic design approach. The growing demand for electricity has become a significant burden on traditional power networks, prompting power engineers to seek ways to improve their efficiency. One such solution is to integrate dispersed generation sources, such as photovoltaic (PV) and storage systems, with an appropriate control mechanism at the distribution level. In recent years, there has been a significant increase in interest in the installation of PV-Battery systems, due to their potential to reduce carbon emissions and lower energy costs. This research proposes an optimal economic power dispatch strategy using Model Predictive Control (MPC) to enhance the overall performance of HAPN. A hybrid AC/DC microgrid concept is proposed to address the control choices made by the appliance scheduling and hybrid switching approaches based on a linear programming optimization framework. The suggested optimization criteria improve consumer satisfaction, minimize grid disconnections, and lower overall energy costs by deploying inexpensive clean energy generation and control. Various examples from actual case study demonstrate the use of the established EMS and design methodology.Die Motivation dieser Arbeit besteht darin, ein Konzept zur Senkung der Energiekosten in einem Heimnetzwerk (HAPN) mit intelligenter Erzeugung und exiblen Lastanforderungen vorzustellen. Im Rahmen dieser Forschungsarbeit wird ein Entwurf für ein HAPN entwickelt, indem das Energiemanagementsystem (EMS) und der Entwurf des Layouts auf der Grundlage des Systemmodells und der betrieblichen Anforderungen gelöst werden. Die steigende Nachfrage nach Elektrizität ist für traditionelle Stromnetze kostspielig und infrastrukturintensiv. Daher konzentrieren sich Energietechniker darauf, die Effizienz der derzeitigen Netze zu erhöhen. Dies kann durch die Integration verteilter Erzeugungsanlagen (z. B. Photovoltaik (PV), Speicher) mit einem geeigneten Kontrollmechanismus für das Energiemanagement auf der Verteilungsseite erreicht werden. Darüber hinaus hat das Interesse an der Installation von PV-Batterie-basierten Systemen aufgrund der Reduzierung der CO2-Emissionen und der Senkung der Energiekosten erheblich zugenommen. Es wird eine optimale wirtschaftliche Strategie für den Energieeinsatz unter Verwendung einer modellprädiktiven Steuerung (MPC) entwickelt. Es wird zudem ein hybrides AC/DC-Microgrid-Konzept vorgeschlagen, um die Steuerungsentscheidungen, die von den Ansätzen der Geräteplanung und der hybriden Umschaltung getroffen werden, auf der Grundlage eines linearen Programmierungsoptimierungsrahmens zu berücksichtigen. Die vorgeschlagenen Optimierungskriterien verbessern die Zufriedenheit der Verbraucher, minimieren Netzabschaltungen und senken die Gesamtenergiekosten durch den Einsatz von kostengünstiger und sauberer Energieerzeugung. Verschiedene Beispiele aus einer Fallstudie demonstrieren den Einsatz des entwickelten EMS und der Entwurfsmethodik
Blockchain and distributed ledger technologies for supply chain traceability: industry considerations and consumer preferences
Several businesses and academic circles were quick to proclaim blockchain, the distributed ledger technology behind digital currencies, as the solution to a plethora of industry challenges. That was especially true for supply chain management and traceability applications for coffee products, where the technology's features were viewed as a potential solution to longstanding issues of communication inefficiencies, production monitoring, and communicating provenance information to the end consumer. However, despite the excessive amount of investment, research, and experimentation, blockchain growth and adoption have stagnated. This thesis suggests that a plausible reason for the current gridlock the technology finds itself in lies in the absence of primary research that goes beyond its technical implementations and provides clear insights on both how industry professionals understand blockchain and structure their decision-making process to adopt it, as well as on how consumers perceive coffee products that utilise the technology for traceability and provenance purposes.
In attempting to fill that knowledge gap, add to the overall understanding of consumer perception of provenance and traceability information and, ultimately, provide companies and organisations with actionable suggestions and insights, this PhD answers two critical questions. One addresses how industry decision-makers perceive fundamental characteristics of blockchain and identify the determining factors for deciding whether they need to adopt and implement the technology in their supply chains. The second examines using blockchain as a traceability certification solution in the coffee industry, how consumers will perceive products that utilise it, and how it compares with existing traceability certifications in the market.
The online survey used to explore the views of industry professionals revealed that despite the overall positive attitudes around blockchain and the importance the technology plays in their future business plans, issues around regulatory compliance, operational frameworks and concerns around the role and nature of system participation are hindering broader adoption and implementation. Inevitably, the proposed decision- making flowchart revealed that blockchain was a suitable business solution for less than half of them. At the same time, a questionnaire based on an extended version of the Theory of Planned Behaviour combined with an online experimental study on multiple coffee certifications revealed that consumers positively value the features offered by a blockchain traceability system and found it easy to comprehend the proposed phone app format of presenting provenance information. However, a possible equation effect emerged when blockchain was compared with multiple traceability certifications in a market-like environment, highlighting the importance of consumer awareness around provenance information and the importance of product differentiation. The multifaceted insights provided in this thesis can significantly contribute to helping businesses and organisations formulate their strategies for implementing blockchain in their supply chains while also adopting a user-centred approach of considering consumer preferences and attitudes around the technology
Exploring leaders\u27 sensemaking of emergent global norms for open science: a mixed methods discourse analysis of UNESCO’s multistakeholder initiative
In November 2021, all 193 United Nations Member States adopted the United Nations Educational, Scientific, and Cultural Organization’s (UNESCO) Recommendation on Open Science (UNESCO, 2021a), which signaled a shared commitment to globally recognized standards for open science. However, as with other normative instruments established by intergovernmental organizations (IGOs) such as UNESCO, the ways in which local, national, and regional leaders will implement the recommendation can and will vary (Finnemore, 1993). Top-down and bottom-up coordination across international stakeholders in the research system is critical for the framework to be effective in driving global policy implementation and enabling sustained research culture change. Such international coordination necessitates an understanding of the complex economic, socio-political, and cultural dimensions that exist among these stakeholders and may influence local implementation efforts and norm-setting (Martinsson, 2011; Nilsson, 2017). This mixed methods study explores leaders’ sensemaking of emergent global norms for open science through public discourse during the development of UNESCO’s recommendation. The central research question is: How did institutional leaders make sense of emergent global norms for open science during UNESCO’s multistakeholder initiative? The study is situated at the intersection of systems thinking, global norms, and sensemaking, using a social constructionist lens. A synthesis of study findings draws two conclusions: That there is evidence in the discourse of accelerating self-organization toward open science among Member States who responded to UNESCO’s call for commentary on the draft recommendation; and that there is also evidence in the discourse of a degree of instability around prospective norm diffusion and internalization of the Recommendation on Open Science (2021a) related directly to matters of implementation. The tension between emergence and instability is well documented throughout the literature across complex systems, global norms, and sensemaking. Therefore, the study supports the ongoing exploration of global norms development and, specifically, the critical progression from norm emergence to norm diffusion. Given the theoretical coherence of complex systems, global norms, and sensemaking as evidenced throughout the findings, the novel integrative analytic frame that was developed during the design of this study may support other global norms development studies
Computational Intelligence for Cooperative Swarm Control
Over the last few decades, swarm intelligence (SI) has shown significant benefits in many practical applications. Real-world applications of swarm intelligence include disaster response and wildlife conservation. Swarm robots can collaborate to search for survivors, locate victims, and assess damage in hazardous environments during an earthquake or natural disaster. They can coordinate their movements and share data in real-time to increase their efficiency and effectiveness while guiding the survivors. In addition to tracking animal movements and behaviour, robots can guide animals to or away from specific areas. Sheep herding is a significant source of income in Australia that could be significantly enhanced if the human shepherd could be supported by single or multiple robots.
Although the shepherding framework has become a popular SI mechanism, where a leading agent (sheepdog) controls a swarm of agents (sheep) to complete a task, controlling a swarm of agents is still not a trivial task, especially in the presence of some practical constraints. For example, most of the existing shepherding literature assumes that each swarm member has an unlimited sensing range to recognise all other members’ locations. However, this is not practical for physical systems. In addition, current approaches do not consider shepherding as a distributed system where an agent, namely a central unit, may observe the environment and commu- nicate with the shepherd to guide the swarm. However, this brings another hurdle when noisy communication channels between the central unit and the shepherd af- fect the success of the mission. Also, the literature lacks shepherding models that can cope with dynamic communication systems. Therefore, this thesis aims to design a multi-agent learning system for effective shepherding control systems in a partially observable environment under communication constraints.
To achieve this goal, the thesis first introduces a new methodology to guide agents whose sensing range is limited. In this thesis, the sheep are modelled as an induced network to represent the sheep’s sensing range and propose a geometric method for finding a shepherd-impacted subset of sheep. The proposed swarm optimal herding point uses a particle swarm optimiser and a clustering mechanism to find the sheepdog’s near-optimal herding location while considering flock cohesion. Then, an improved version of the algorithm (named swarm optimal modified centroid push) is proposed to estimate the sheepdog’s intermediate waypoints to the herding point considering the sheep cohesion. The approaches outperform existing shepherding methods in reducing task time and increasing the success rate for herding.
Next, to improve shepherding in noisy communication channels, this thesis pro- poses a collaborative learning-based method to enhance communication between the central unit and the herding agent. The proposed independent pre-training collab- orative learning technique decreases the transmission mean square error by half in 10% of the training time compared to existing approaches. The algorithm is then ex- tended so that the sheepdog can read the modulated herding points from the central unit. The results demonstrate the efficiency of the new technique in time-varying noisy channels.
Finally, the central unit is modelled as a mobile agent to lower the time-varying noise caused by the sheepdog’s motion during the task. So, I propose a Q-learning- based incremental search to increase transmission success between the shepherd and the central unit. In addition, two unique reward functions are presented to ensure swarm guidance success with minimal energy consumption. The results demonstrate an increase in the success rate for shepherding
LIPIcs, Volume 277, GIScience 2023, Complete Volume
LIPIcs, Volume 277, GIScience 2023, Complete Volum
12th International Conference on Geographic Information Science: GIScience 2023, September 12–15, 2023, Leeds, UK
No abstract available
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