1. Tripartite evolutionary game analysis of the adoption of AI delivery technologyS. Y. Lin, M. Y. Zheng, J. L. Chen, 2025, original scientific article Abstract: The decision of logistics enterprises to adopt AI delivery technology is influenced by multiple stakeholders, a fact that is largely ignored in existing research. A tripartite evolutionary game model incorporating the government, logistics enterprises, and consumers was established in this study. It analyzed the strategies adopted by the three actors in promoting AI delivery technology and examined the factors influencing their choices. Furthermore, the evolutionary equilibrium and stability of these strategies were explored and verified through simulation analysis. Results reveal several key insights: (1) Technology promotion is a collaborative process driven by multiple stakeholders. Government subsidies, enterprise costs and benefits, and consumer utility are the crucial variables determining system stability. (2) Government incentives not only reduce enterprises’ adoption costs but also increase consumer willingness to adopt through subsidies and publicity. These measures accelerate the system’s evolution toward the ideal stable state of “introduction, incentive, AI delivery”. (3) Enterprises’ investment decisions are highly sensitive to input costs and economic benefits. The threshold for technology adoption decreases when significant economic benefits are present or costs decline. (4) Consumers’ perceived utility and learning costs directly affect their usage intentions and subsequently influence the strategic choices of the government and enterprises through demand feedback. This study provides a novel perspective on the promotion of AI delivery and offers practical management insights for policy-making and user analysis in logistics enterprises.
Keywords: artificial intelligence, AI delivery, logistics delivery services, technology adoption, tripartite evolutionary game mode, government incentives, logistics enterprise decision-making, consumer behaviour
Published in DKUM: 23.01.2026; Views: 0; Downloads: 0
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2. Information modelling and knowledge bases XXXIIscientific monograph Abstract: Information modeling and knowledge bases are important technologies for academic and industrial research that goes beyond the traditional borders of information systems and computer science. The amount and complexity of information to be dealt with grows continually, as do the levels of abstraction and the size of databases.
This book presents the proceedings of the 30th International Conference on Information Modelling and Knowledge Bases (EJC2020), due to be held in Hamburg, Germany on 8 and 9 June 2020, but instead held as a virtual conference on the same dates due to the Corona-virus pandemic restrictions. The conference provides a research forum for the exchange of scientific results and experiences, and brings together experts from different areas of computer science and other disciplines with a common interest in information modeling and knowledge bases. The subject touches on many disciplines, with philosophy and logic, cognitive science, knowledge management, linguistics and management science, as well as the emerging fields of data science and machine learning, all being relevant areas. The 23 reviewed, selected, and upgraded contributions included here are the result of presentations, comments, and discussions from the conference, and reflect the themes of the conference sessions: learning and linguistics; systems and processes; data and knowledge representation; models and interfaces; formalizations and reasoning; models and modeling; machine learning; models and programming; environment and predictions; modeling emotion; and social networks.
The book provides an overview of current research and applications, and will be of interest to all those working in the field.
Keywords: information modelling, knowledge bases, knowledge management, expert systems, artificial intelligence, information systems, database
Published in DKUM: 20.01.2026; Views: 0; Downloads: 0
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3. Information modelling and knowledge bases XXXIIIscientific monograph Abstract: The technology of information modelling and knowledge bases addresses the complexities of modelling in digital transformation and digital innovation, reaching beyond the traditional borders of information systems and academic research in computer science.
This book presents 21 papers from the 31st International conference on Information Modeling and Knowledge Bases (EJC 2021), hosted by the Department Informatik of the University of Applied Sciences in Hamburg, Germany, and held as a virtual event from 7 to 9 September 2021 due to restrictions caused by the Corona virus. The conference provides a research forum for academics and practitioners dealing with information and knowledge to exchange scientific results and experiences, and EJC 2021 covered a wide range of themes extending knowledge discovery through conceptual modeling, knowledge and information modeling and discovery, linguistic modeling, cross-cultural communication and social computing, environmental modeling and engineering, and multimedia data modeling and systems. As always, the conference was open to new topics related to its main themes, meaning the content emphasis of the EJC conferences is always able to adapt to the changes taking place in the research field, and the 21 papers included here after rigorous review, selection and upgrading are the result of presentations, comments, and discussions during the conference.
Providing an up to the minute overview of the technology of information modeling and knowledge bases, the book will be of interest to all those working in the field.
Keywords: information modelling, knowledge bases, knowledge management, expert systems, artificial intelligence, information systems, database
Published in DKUM: 20.01.2026; Views: 0; Downloads: 0
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4. Information modelling and knowledge bases XXXIVscientific monograph Abstract: The amount and complexity of information is continually growing, and information modeling and knowledge bases have become important contributors to technology and to academic and industrial research in the 21st century. They address the complexities of modeling in digital transformation and digital innovation, reaching beyond the traditional borders of information systems and academic computer-science research.
This book presents the proceedings of EJC 2022, the 32nd International conference on Information Modeling and Knowledge Bases, held as a hybrid event due to restrictions related to the Corona virus pandemic in Hamburg, Germany, from 30 May to 3 June 2022. The aim of the conference is to bring together experts from different areas of computer science and other disciplines with a common interest in understanding and solving the problems of information modeling and knowledge bases and applying the results of research to practice. The conference has always been open to new topics related to its main themes, and the content emphasis of the conferences have changed through the years according to developments in the research field, so philosophy and logic, cognitive science, knowledge management, linguistics, and management science, as well as machine learning and AI, are also relevant areas. This book presents 19 reviewed and selected papers covering a wide range of topics, upgraded as a result of comments and discussions during the conference.
Providing a current overview of recent developments, the book will be of interest to all those using information modeling and knowledge bases as part of their work.
Keywords: information modelling, knowledge bases, knowledge management, expert systems, artificial intelligence, information systems, database
Published in DKUM: 20.01.2026; Views: 0; Downloads: 0
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5. Towards a definition of a responsible artificial intelligenceSabrina Göllner, Marina Tropmann-Frick, Boštjan Brumen, 2024, independent scientific component part or a chapter in a monograph Abstract: Our investigation seeks to enhance the understanding of responsible artificial intelligence. The EU is deeply engaged in discussions concerning AI trustworthiness and has released several relevant documents. It’s crucial to remember that while AI offers immense benefits, it also poses risks, necessitating global oversight. Moreover, there’s a need for a framework that helps enterprises align their AI development with these international standards. This research will aid both policymakers and AI developers in anticipating future challenges and prioritizing their efforts. In our study, we delve into the essence of responsible AI and, to our understanding, introduce a comprehensive definition of the term. Through a thorough literature review, we pinpoint the prevailing trends surrounding responsible AI. Using insights from our analysis, we’ve also deliberated on a prospective framework for responsible AI. Our findings emphasize that human-centeredness should prioritized. This entails adopting AI techniques that prioritize ethical considerations, explainability of models, and aspects like privacy, security, and trustworthiness.
Keywords: structured literature review, artificial intelligence, responsible AI, privacy-preserving AI, explainable AI, ethical AI, rustworthy AI
Published in DKUM: 20.01.2026; Views: 0; Downloads: 0
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6. Information modelling and knowledge bases XXXVscientific monograph Abstract: The volume and complexity of information, together with the number of abstraction levels and the size of data and knowledge bases, grow continually. Data originating from diverse sources involves a combination of data from traditional legacy sources and unstructured data requiring backwards modeling, meanwhile, information modeling and knowledge bases have become important contributors to 21st-century academic and industrial research.
This book presents the proceedings of EJC 2023, the 33rd International Conference on Information Modeling and Knowledge Bases, held from 5 to 9 June 2023 in Maribor, Slovenia. The aim of the EJC conferences is to bring together experts from different areas of computer science and from other disciplines that share the common interest of understanding and solving the problems of information modeling and knowledge bases and applying the results of research to practice. The conference constitutes a research forum for the exchange of results and experiences by academics and practitioners dealing with information and knowledge bases. The topics covered at EJC 2023 encompass a wide range of themes including conceptual modeling; knowledge and information modeling and discovery; linguistic modeling; cross-cultural communication and social computing; environmental modeling and engineering; and multimedia data modeling and systems. In the spirit of adapting to the changes taking place in these areas of research, the conference was also open to new topics related to its main themes.
Providing a current overview of progress in the field, this book will be of interest to all those whose work involves the use of information modeling and knowledge bases.
Keywords: information modelling, knowledge bases, knowledge management, expert systems, artificial intelligence, information systems, database
Published in DKUM: 20.01.2026; Views: 0; Downloads: 0
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7. Information modelling and knowledge bases XXXVIscientific monograph Abstract: Information modeling and knowledge bases have become increasingly important for academic communities working with information systems, computer science, and artificial intelligence, and the volume and complexity and levels of abstraction, together with the size of databases and knowledge bases, continue to grow in parallel with the rising complexity of computational processes.
This book presents the proceedings of EJC 2024, the 34th international conference on Information Modelling and Knowledge Bases, held in Tokyo, Japan, from 10 to 14 June 2024. The EJC conference series aims to explore the progress in research communities with a common interest in understanding and solving problems on information modeling and knowledge bases and applying the results of research to practice by means of sharing scientific results and experiences achieved using innovative methods and systems in computer science and other disciplines. The selected papers published here cover many areas of information modeling and knowledge bases, including the theory of concepts, semantic computing, data mining, machine learning, context-based information retrieval, ontological technology, image databases, temporal and spatial databases, natural language processing, software engineering, cross-cultural computing, environmental analysis, social computing, and many others. This latest edition of the conference also addressed the question of global & environmental AI for nature and society and asked whether System 2 can do everything that AI cannot do yet.
Offering a comprehensive overview of current developments, the book will be of interest to all those working in the field.
Keywords: information modelling, knowledge bases, knowledge management, expert systems, artificial intelligence, information systems, database
Published in DKUM: 20.01.2026; Views: 0; Downloads: 1
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8. Comparison of artificial neural network, fuzzy logic and genetic algorithm for cutting temperature and surface roughness prediction during the face milling processBorislav Savković, Pavel Kovač, D. Rodic, Branko Strbac, Simon Klančnik, 2020, original scientific article Abstract: This paper shows the possibility of applying artificial intelligence methods in milling, as one of the most common machining operations. The main goal of the research is to obtain reliable intelligent models for selected output characteristics of the milling process, depending on the input parameters of the process: depth of cut, cutting speed and feed to the tooth. One of the problems is certainly determining the value of input parameters of the processing process depending on the objective function, i.e. the output characteristics of the milling process. The selected objective functions in this paper are the temperature in the cutting zone and arithmetic mean roughness of the machined surface. The paper examines the accuracy of three models based on artificial intelligence, obtained through artificial neural networks, fuzzy logic, and genetic algorithms. Based on the mean percentage error of deviation, conclusions were drawn as to which of the three models is most adequately applied and implemented in appropriate process systems, which are based on artificial intelligence.
Keywords: artificial intelligence, artificial neural networks (ANN), fuzzy logic, genetic algorithms (GA), face milling, modelling, surface roughness, cutting temperature
Published in DKUM: 15.01.2026; Views: 0; Downloads: 1
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10. Rebus sic stantibus in the age of artificial intelligence : the vital role of judicial discretion in contractual justiceKlemen Drnovšek, Nataša Samec Berghaus, 2025, original scientific article Abstract: This article investigates how the principle of contractual justice - an unwritten yet fundamental source of private law - continues to operate in an era shaped by artificial intelligence (AI). Although pacta sunt servanda remains the cornerstone of contractual certainty, the doctrine of rebus sic stantibus functions as a corrective when radically changed circumstances would make strict performance inequitable. Recognised across all developed legal orders and recently codified in many, the authors analyse the doctrine in more than twenty European jurisdictions, with attention to convergences and doctrinal divergences. The study then turns to smart-contract technology and AI-driven automation, asking whether code-based execution can accommodate contractual justice or instead amplifies contractual rigidity. The authors conclude that automated decision-making can handle only quantifiable adjustments, whereas genuine fairness still requires case-sensitive judicial discretion grounded in unwritten principles. Even - and especially - in the age of AI, therefore, courts - and the normative resources of good faith, fairness and equity - remain indispensable safeguards of contractual balance.
Keywords: changed circumstances, rebus sic stantibus, unwritten law, principle of contractual justice, intelligent contracts, artificial intelligence, judicial discretion, contract law
Published in DKUM: 07.01.2026; Views: 0; Downloads: 2
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