Explainable, Transparent Autonomous Agents and Multi-Agent Systems


Book Description

This book constitutes the proceedings of the Second International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, EXTRAAMAS 2020, which was due to be held in Auckland, New Zealand, in May 2020. The conference was held virtually due to the COVID-19 pandemic. The 8 revised and extended papers were carefully selected from 20 submissions and are presented here with one demo paper. The papers are organized in the following topical sections: explainable agents; cross disciplinary XAI; explainable machine learning; demos.




Explainable, Transparent Autonomous Agents and Multi-Agent Systems


Book Description

This book constitutes the proceedings of the First International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, EXTRAAMAS 2019, held in Montreal, Canada, in May 2019. The 12 revised and extended papers presented were carefully selected from 23 submissions. They are organized in topical sections on explanation and transparency; explainable robots; opening the black box; explainable agent simulations; planning and argumentation; explainable AI and cognitive science.







Explainable and Transparent AI and Multi-Agent Systems


Book Description

This book constitutes the proceedings of the Third International Workshop on Explainable, Transparent AI and Multi-Agent Systems, EXTRAAMAS 2021, which was held virtually due to the COVID-19 pandemic. The 19 long revised papers and 1 short contribution were carefully selected from 32 submissions. The papers are organized in the following topical sections: XAI & machine learning; XAI vision, understanding, deployment and evaluation; XAI applications; XAI logic and argumentation; decentralized and heterogeneous XAI.







Human-Automation Interaction


Book Description

This book provides practical guidance and awareness for a growing body of knowledge developing across a variety of disciplines. This initiative is a celebration of the Gavriel Salvendy International Symposium (GSIS) and provides a survey of topics and emerging areas of interest in human–automation interaction. This set of articles for the GSIS emphasizes a main thematic areas: mobile computing. Main areas of coverage include Section A: Health, Care and Assistive Technologies; Section B: Usability, User Experience and Design; Section C: Virtual Learning, Training and Collaboration; Section D: Ergonomics in Work, Automation and Production. In total, there are more than 600 pages emphasizing contributions from especially early career researchers that were featured as part of this (virtual) symposium and celebration. Gavriel Salvendy initiated the conferences that run annually as Human–Computer Interaction within LNCS of Springer and Applied Human Factors and Ergonomics International (AHFE). The book is inclusive of human–computer interaction and human factors and ergonomics principles, yet is intended to serve a much wider audience that has interest in automation and human modeling. The emerging need for human–automation interaction expertise has developed from an ever-growing availability and presence of automation in our everyday lives. This initiative is intended to provide practical guidance and awareness for a growing body of knowledge developing across a variety of disciplines and many countries.




Distributed Artificial Intelligence


Book Description

Distributed Artificial Intelligence (DAI) came to existence as an approach for solving complex learning, planning, and decision-making problems. When we talk about decision making, there may be some meta-heuristic methods where the problem solving may resemble like operation research. But exactly, it is not related completely to management research. The text examines representing and using organizational knowledge in DAI systems, dynamics of computational ecosystems, and communication-free interactions among rational agents. This publication takes a look at conflict-resolution strategies for nonhierarchical distributed agents, constraint-directed negotiation of resource allocations, and plans for multiple agents. Topics included plan verification, generation, and execution, negotiation operators, representation, network management problem, and conflict-resolution paradigms. The manuscript elaborates on negotiating task decomposition and allocation using partial global planning and mechanisms for assessing nonlocal impact of local decisions in distributed planning. The book will attract researchers and practitioners who are working in management and computer science, and industry persons in need of a beginner to advanced understanding of the basic and advanced concepts.




The Next Generation Innovation in IoT and Cloud Computing with Applications


Book Description

The Next Generation Innovation in IoT and Cloud Computing with Applications is a thought-provoking edited book that explores the cutting-edge advancements and transformative potential of the Internet of Things (IoT) and cloud computing. This comprehensive volume brings together leading experts and researchers to delve into the latest developments, emerging trends, and practical applications that define the next era of technological innovation. Readers will gain valuable insights into how IoT and cloud computing synergize to create a dynamic ecosystem, fostering unprecedented connectivity and efficiency across various industries. The book covers a wide spectrum of topics, including state-of-the-art technologies, security and privacy considerations, and real-world applications in fields such as healthcare, smart cities, agriculture, and more. With a focus on the future landscape of technology, this edited collection serves as a pivotal resource for academics, professionals, and enthusiasts eager to stay at the forefront of the rapidly evolving IoT and cloud computing domains. By offering a blend of theoretical perspectives and hands-on experiences, The Next Generation Innovation in IoT and Cloud Computing with Applications serves as a guide to the forefront of technological progress, providing a roadmap for the exciting possibilities that lie ahead in this era of connectivity and digital transformation.




Handbook on Artificial Intelligence-Empowered Applied Software Engineering


Book Description

This book provides a structured overview of artificial intelligence-empowered applied software engineering. Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions lead current research towards the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence. This book at hand, devoted to Novel Methodologies to Engineering Smart Software Systems Novel Methodologies to Engineering Smart Software Systems, constitutes the first volume of a two-volume Handbook on Artificial Intelligence-empowered Applied Software Engineering. Topics include very significant advances in (i) Artificial Intelligence-Assisted Software Development and (ii) Software Engineering Tools to develop Artificial Intelligence Applications, as well as a detailed Survey of Recent Relevant Literature. Professors, researchers, scientists, engineers and students in artificial intelligence, software engineering and computer science-related disciplines are expected to benefit from it, along with interested readers from other disciplines.




Explainable AI: Foundations, Methodologies and Applications


Book Description

This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas. The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.