Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19) PDF Download
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Author: Sarit Kraus
Publisher:
ISBN: 9780999241141
Category :
Languages : en
Pages :
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Book Description
Author: Sarit Kraus
Publisher:
ISBN: 9780999241141
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: Alexander Ivrii
Publisher: TU Wien Academic Press
ISBN: 3854480423
Category : Technology & Engineering
Languages : en
Pages : 284
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Book Description
Formal Methods in Computer-Aided Design (FMCAD) is a conference series on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing ground-breaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing.
Author: Subarna Shakya
Publisher: Springer Nature
ISBN: 9811676577
Category : Technology & Engineering
Languages : en
Pages : 911
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Book Description
This book features high-quality research papers presented at the 2nd International Conference on Sustainable Expert Systems (ICSES 2021), held in Nepal during September 17–18, 2021. The book focusses on the research information related to artificial intelligence, sustainability, and expert systems applied in almost all the areas of industries, government sectors, and educational institutions worldwide. The main thrust of the book is to publish the conference papers that deal with the design, implementation, development, testing, and management of intelligent and sustainable expert systems and also to provide both theoretical and practical guidelines for the deployment of these systems.
Author: Lu Fang
Publisher: Springer Nature
ISBN: 3030930467
Category : Computers
Languages : en
Pages : 815
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Book Description
This two-volume set LNCS 13069-13070 constitutes selected papers presented at the First CAAI International Conference on Artificial Intelligence, held in Hangzhou, China, in June 2021. Due to the COVID-19 pandemic the conference was partially held online. The 105 papers were thoroughly reviewed and selected from 307 qualified submissions. The papers are organized in topical sections on applications of AI; computer vision; data mining; explainability, understandability, and verifiability of AI; machine learning; natural language processing; robotics; and other AI related topics.
Author: John Fitzgerald
Publisher: Springer Nature
ISBN: 3031667190
Category : Cooperating objects (Computer systems)
Languages : en
Pages : 403
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Book Description
This book is about the engineering of Digital Twins (DTs) of cyber-physical systems (CPSs). It goes behind the glossy image of DTs to help researchers and advanced professionals to ask and answer the fundamental questions underpinning the development of a DT. What are the foundational concepts of the DT? How do different engineering disciplines interact in creating a DT? How should the physical and digital worlds be connected, and how do the imperfections and faults inherent in both worlds affect the DT's qualities? How can we use a DT to support decisions, and how do we maintain it through life? To this end, the book is structured in five parts: "Foundations" introduces the DT concept, the potential benefits of DTs seen from a business perspective, and foundations for DT engineering. "Models and Data" presents the range of models and data that form the core assets of DTs for CPSs. It covers ways in which models can be produced and calibrated, and considers how data is derived from a CPS and communicated to its DT. Next, "Services for Digital Twins" details some of the main services that a DT provides by building on the assets of models and data, including visualisation, fault detection and diagnosis and support for decision-making. "Realising Digital Twins" then covers the realisation of DTs, including a platform allowing engineers to construct DTs from reusable components. Case studies in food production, robotics and marine engineering are presented using a systematic framework that aligns with the DT engineering concepts introduced in the earlier parts of the book. Eventually, "Advanced Topics in Digital Twins" introduces advanced topics in delivering dependable DT-enabled systems, focusing on security and privacy, the capacity for autonomy, and a range of open research topics. This book aims at researchers in DT technology and design, including advanced (master and doctoral) students, as well as engineering practitioners aiming to develop DTs. The most common techniques described in the main text will be accessible via open-source projects, including further DT examples, exercises and solutions, as well as pointers to emerging standards, frameworks and platforms. Classroom materials, exercises and solutions are available to lecturers through a dedicated Web site.
Author: Hong Qu
Publisher: Elsevier
ISBN: 0443328218
Category : Computers
Languages : en
Pages : 222
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Book Description
Towards Neuromorphic Machine Intelligence: Spike-Based Representation, Learning, and Applications provides readers with in-depth understanding of Spiking Neural Networks (SNNs), which is a burgeoning research branch of Artificial Neural Networks (ANNs), AI, and Machine Learning that sits at the heart of the integration between Computer Science and Neural Engineering. In recent years, neural networks have re-emerged in relation to AI, representing a well-grounded paradigm rooted in disciplines from physics and psychology to information science and engineering.This book represents one of the established cross-over areas where neurophysiology, cognition, and neural engineering coincide with the development of new Machine Learning and AI paradigms. There are many excellent theoretical achievements in neuron models, learning algorithms, network architecture, and so on. But these achievements are numerous and scattered, with a lack of straightforward systematic integration, making it difficult for researchers to assimilate and apply. As the third generation of Artificial Neural Networks (ANNs), Spiking Neural Networks (SNNs) simulate the neuron dynamics and information transmission in a biological neural system in more detail, which is a cross-product of computer science and neuroscience. The primary target audience of this book is divided into two categories: artificial intelligence researchers who know nothing about SNNs, and researchers who know a lot about SNNs. The former needs to acquire fundamental knowledge of SNNs, but the challenge is that much of the existing literature on SNNs only slightly mentions the basic knowledge of SNNs, or is too superficial, and this book gives a systematic explanation from scratch. The latter needs learning about some novel research achievements in the field of SNNs, and this book introduces the latest research results on different aspects of SNNs and provides detailed simulation processes to facilitate readers' replication. In addition, the book introduces neuromorphic hardware architecture as a further extension of the SNN system.The book starts with the birth and development of SNNs, and then introduces the main research hotspots, including spiking neuron models, learning algorithms, network architectures, and neuromorphic hardware. Therefore, the book provides readers with easy access to both the foundational concepts and recent research findings in SNNs. - Introduces Spiking Neural Networks (SNNs), a new generation of biologically inspired artificial intelligence. - Systematically presents basic concepts of SNNs, neuron and network models, learning algorithms, and neuromorphic hardware. - Introduces the latest research results on various aspects of SNNs and provides detailed simulation processes to facilitate readers' replication.
Author: Lingfei Wu
Publisher: Springer Nature
ISBN: 9811660549
Category : Computers
Languages : en
Pages : 701
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Book Description
Deep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data, such as images or sequence data, and not immediately applicable to graph-structured data such as text. This gap has driven a wave of research for deep learning on graphs, including graph representation learning, graph generation, and graph classification. The new neural network architectures on graph-structured data (graph neural networks, GNNs in short) have performed remarkably on these tasks, demonstrated by applications in social networks, bioinformatics, and medical informatics. Despite these successes, GNNs still face many challenges ranging from the foundational methodologies to the theoretical understandings of the power of the graph representation learning. This book provides a comprehensive introduction of GNNs. It first discusses the goals of graph representation learning and then reviews the history, current developments, and future directions of GNNs. The second part presents and reviews fundamental methods and theories concerning GNNs while the third part describes various frontiers that are built on the GNNs. The book concludes with an overview of recent developments in a number of applications using GNNs. This book is suitable for a wide audience including undergraduate and graduate students, postdoctoral researchers, professors and lecturers, as well as industrial and government practitioners who are new to this area or who already have some basic background but want to learn more about advanced and promising techniques and applications.
Author: Angelo Geraci
Publisher: Springer Nature
ISBN: 3030624765
Category : Technology & Engineering
Languages : en
Pages : 150
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Book Description
This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2019-20 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists.
Author: Marius George Linguraru
Publisher: Springer Nature
ISBN: 3031723902
Category :
Languages : en
Pages : 831
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Book Description
Author: M. Tropmann-Frick
Publisher: IOS Press
ISBN: 1643682431
Category : Computers
Languages : en
Pages : 348
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Book Description
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.
