Jamal Bentahar – författare

This book constitutes the refereed proceedings of the 17th International Conference on Mobile Web and Intelligent Information Systems, MobiWIS 2021, held as a virtual event, in August 2021.The 15 full papers presented in this book were carefully reviewed and selected from 40 submissions. The papers of MobiWIS 2021 deal focus on topics such as security and privacy; web and mobile applications; networking and communication; intelligent information systems; and IoT and ubiquitous computing.

Deep and machine learning is the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionise industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, etc. The ground-breaking technology of blockchain also enables decentralisation, immutability, and transparency of data and applications.This event aims to enable synergy between these areas and provide a leading forum for researchers, developers, practitioners, and professionals from public sectors and industries to meet and share the latest solutions and ideas in solving cutting-edge problems in the modern information society and the economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Some of the key topics of interest include (but are not limited to):Deep/Machine learning based modelsStatistical models and learningData analysis, insights and hidden patternData visualisationSecurity threat detectionData classification and clusteringBlockchain security and trustBlockchain data management

Deep and machine learning is the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionise industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, etc. The ground-breaking technology of blockchain also enables decentralisation, immutability, and transparency of data and applications.

This event aims to enable synergy between these areas and provide a leading forum for researchers, developers, practitioners, and professionals from public sectors and industries to meet and share the latest solutions and ideas in solving cutting-edge problems in the modern information society and the economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Some of the key topics of interest include (but are not limited to):

Deep/Machine learning based models

 Statistical models and learning

 Data analysis, insights and hidden pattern

 Data visualisation

 Security threat detection

 Data classification and clustering

 Blockchain security and trust

 Blockchain data management

This book is the 5th Joint International Conference on AI, Big Data and Blockchain (ABB 2024), 19–21 Aug 2024, Vienna, Austria. This book constitutes refereed articles which present research work on timely research themes such as novel AI methods and models, deep learning techniques, data analytics and hidden patterns, security, privacy and trust, blockchain data management, and fraud detection and prevention, among others. The intended readership of the book includes researchers, developers, and practitioners in the areas of AI, big data, blockchain techniques, technologies, and their applications.

In the multi-agent systems area, linking theory to practical applications is still a fertile research topic. The aim of the workshop on Declarative Agent Languages and Technologies (DALT 2009), in its seventh edition this year, is to achieve this goal, which needs developing and using advanced declarative technologies and languages, particularly agent programming, communication languages, and reasoning and decision-making mechanisms. Developing these technologies is a particularly challenging issue from many perspectives: formal foundations, pr- ticalfeasibility,degreeof?exibility,etc. Inthiscontext,thedeclarativeparadigm is arguably the most appropriate as unlike imperative approaches, the focus is onwhatthe solutionshouldaccomplishratherthanondescribing howto acc- plish it. This is because agentcomputing, as a paradigm,is about describing the logic of computation instead of describing how to accomplish it. DALT is about investigating,studying, andusing the declarativeparadigmaswell ascombining declarative and formal approaches with engineering and technology aspects of agents and multi-agent systems.This volume presents the latest developments in the area of declarative l- guagesandtechnologies,whichaimtoproviderigorousframeworksfordesigning, specifying, implementing and verifying autonomous interacting agents. These frameworksarebasedoncomputationallogicsand other formalmethods suchas mathematical models and game theoretical approaches. Using such models and approaches facilitates the development of agents that reason and act rationally while at the same time being able to verify the behavior of these agents against their speci?cation. The main theme of DALT 2009 was the further advan- ment of relevant speci?cation and veri?cation techniques, such as, for instance, modal and epistemic logics, model checking, constraint logic programming, and distributed constraint satisfaction.