Faithful communication is a necessary precondition for large-scale quantum information processing and networking, irrespective of the physical platform. Thus, the problems of quantum-state transfer and quantum-network engineering have attracted enormous interest over the last years, and constitute one of the most active areas of research in quantum information processing. The present volume introduces the reader to fundamental concepts and various aspects of this exciting research area, including links to other related areas and problems. The implementation of state-transfer schemes and the engineering of quantum networks are discussed in the framework of various quantum optical and condensed matter systems, emphasizing the interdisciplinary character of the research area. Each chapter is a review of theoretical or experimental achievements on a particular topic, written by leading scientists in the field. The volume aims at both newcomers as well as experienced researchers.

I am indebted to my thesis advisor, Michael Genesereth, for his guidance, inspiration, and support which has made this research possible. As a teacher and a sounding board for new ideas, Mike was extremely helpful in pointing out Haws, and suggesting new directions to explore. I would also like to thank Harold Brown for introducing me to the application of artificial intelligence to reasoning about designs, and his many valuable comments as a reader of this thesis. Significant contribu tions by the other members of my reading committee, Mark Horowitz, and Allen Peterson have greatly improved the content and organization of this thesis by forcing me to communicate my ideas more clearly. I am extremely grateful to the other members of the Logic Group at the Heuristic Programming Project for being a sounding board for my ideas, and providing useful comments. In particular, I would like to thank Matt Ginsberg, Vineet Singh, Devika Subramanian, Richard Trietel, Dave Smith, Jock Mackinlay, and Glenn Kramer for their pointed criticisms. This research was supported by Schlumberger Palo Alto Research (previously Fairchild Laboratory for Artificial Intelligence). I am grateful to Peter Hart, the former head of the AI lab, and his successor Marty Tenenbaum for providing an excellent environment for performing this research."

The book provides a comprehensive and timely report on the topic of decision making and decision analysis in economics and the social sciences. The various contributions included in the book, selected using a peer review process, present important studies and research conducted in various countries around the globe. The majority of these studies are concerned with the analysis, modeling and formalization of the behavior of groups or committees that are in charge of making decisions of social and economic importance. Decisions in these contexts have to meet precise coherence standards and achieve a significant degree of sharing, consensus and acceptance, even in uncertain and fuzzy environments. This necessitates the confluence of several research fields, such as foundations of social choice and decision making, mathematics, complexity, psychology, sociology and economics. A large spectrum of problems that may be encountered during decision making and decision analysis in the areas of economics and the social sciences, together with a broad range of tools and techniques that may be used to solve those problems, are presented in detail in this book, making it an ideal reference work for all those interested in analyzing and implementing mathematical tools for application to relevant issues involving the economy and society.

This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the latest advances in statistical modeling in biomedical research, identifies impactful new directions, and seeks to drive the field forward. It also fosters the interaction of scholars in the arena, offering great opportunities to stimulate further collaborations. This book will appeal to industry data scientists and statisticians, researchers, and graduate students in biostatistics and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications Large scale data analysis and its applications Biomedical research and modeling Survival analysis with complex data structure and its applications.

This book discusses the challenges facing current research in knowledge discovery and data mining posed by the huge volumes of complex data now gathered in various real-world applications (e.g., business process monitoring, cybersecurity, medicine, language processing, and remote sensing). The book consists of 14 chapters covering the latest research by the authors and the research centers they represent. It illustrates techniques and algorithms that have recently been developed to preserve the richness of the data and allow us to efficiently and effectively identify the complex information it contains. Presenting the latest developments in complex pattern mining, this book is a valuable reference resource for data science researchers and professionals in academia and industry.

Global networks, which are the primary pillars of the modern manufacturing industry and supply chains, can only cope with the new challenges, requirements and demands when supported by new computing and Internet-based technologies. Cloud Manufacturing: Distributed Computing Technologies for Global and Sustainable Manufacturing introduces a new paradigm for scalable service-oriented sustainable and globally distributed manufacturing systems. The eleven chapters in this book provide an updated overview of the latest technological development and applications in relevant research areas. Following an introduction to the essential features of Cloud Computing, chapters cover a range of methods and applications such as the factors that actually affect adoption of the Cloud Computing technology in manufacturing companies and new geometrical simplification method to stream 3-Dimensional design and manufacturing data via the Internet. This is further supported case studies and real life data for Waste Electrical and Electronic Equipment (WEEE) remanufacturing. This compilation of up to date research and literature can be used as a textbook or reference for mechanical, manufacturing, and computer engineering graduate students and researchers for efficient utilization, deployment and development of distributed and Cloud manufacturing systems, services and applications.

With this book, Onn Shehory and Arnon Sturm, together with further contributors, introduce the reader to various facets of agent-oriented software engineering (AOSE). They provide a selected collection of state-of-the-art findings, which combines research from information systems, artificial intelligence, distributed systems and software engineering and covers essential development aspects of agent-based systems.

The book chapters are organized into five parts. The first part introduces the AOSE domain in general, including introduction to agents and the peculiarities of software engineering for developing MAS. The second part describes general aspects of AOSE, like architectural models, design patterns and communication. Next, part three discusses AOSE methodologies and associated research directions and elaborates on Prometheus, O-MaSE and INGENIAS. Part four then addresses agent-oriented programming languages. Finally, the fifth part presents studies related to the implementation of agents and multi-agent systems.

The book not only provides a comprehensive review of design approaches for specifying agent-based systems, but also covers implementation aspects such as communication, standards and tools and environments for developing agent-based systems. It is thus of interest to researchers, practitioners and students who are interested in exploring the agent paradigm for developing software systems.

Implementation of Smart Healthcare Systems using AI, IoT, and Blockchain provides imperative research on the development of data fusion and analytics for healthcare and their implementation into current issues in a real-time environment. While highlighting IoT, bio-inspired computing, big data, and evolutionary programming, the book explores various concepts and theories of data fusion, IoT, and Big Data Analytics. It also investigates the challenges and methodologies required to integrate data from multiple heterogeneous sources, analytical platforms in healthcare sectors. This book is unique in the way that it provides useful insights into the implementation of a smart and intelligent healthcare system in a post-Covid-19 world using enabling technologies like Artificial Intelligence, Internet of Things, and blockchain in providing transparent, faster, secure and privacy preserved healthcare ecosystem for the masses.

Combinatorial optimization is the process of finding the best, or optimal, so lution for problems with a discrete set of feasible solutions. Applications arise in numerous settings involving operations management and logistics, such as routing, scheduling, packing, inventory and production management, lo cation, logic, and assignment of resources. The economic impact of combi natorial optimization is profound, affecting sectors as diverse as transporta tion (airlines, trucking, rail, and shipping), forestry, manufacturing, logistics, aerospace, energy (electrical power, petroleum, and natural gas), telecommu nications, biotechnology, financial services, and agriculture. While much progress has been made in finding exact (provably optimal) so lutions to some combinatorial optimization problems, using techniques such as dynamic programming, cutting planes, and branch and cut methods, many hard combinatorial problems are still not solved exactly and require good heuristic methods. Moreover, reaching "optimal solutions" is in many cases meaningless, as in practice we are often dealing with models that are rough simplifications of reality. The aim of heuristic methods for combinatorial op timization is to quickly produce good-quality solutions, without necessarily providing any guarantee of solution quality. Metaheuristics are high level procedures that coordinate simple heuristics, such as local search, to find solu tions that are of better quality than those found by the simple heuristics alone: Modem metaheuristics include simulated annealing, genetic algorithms, tabu search, GRASP, scatter search, ant colony optimization, variable neighborhood search, and their hybrids."

Data Mining is the process of posing queries and extracting useful information, patterns and trends previously unknown from large quantities of data [Thu, 00]. It is the process where intelligent tools are applied in order to extract data patterns [JM, 01]. This encompasses a number of different technical approaches, such as cluster analysis, learning classification and association rules, and finding dependencies. Agents are defined as software entities that perform some set of tasks on behalf of users with some degree of autonomy. This research work deals about developing a automated data mining system which encompasses the familiar data mining algorithms using intelligent agents in object oriented databases and proposing a framework. Because the data mining system uses the intelligent agents, a new user will be able to interact with the data mining system without much data mining technical knowledge. This system will automatically select the appropriate data mining technique and select the necessary field needed from the database at the appropriate time without expecting the users to specify the specific technique and the parameters. Also a new framework is proposed for incorporating intelligent agents with automated data mining. One of the major goals in developing this system is to give the control to the computer for learning automatically by using intelligent agents.

Intelligent systems enhance the capacities made available by the internet and other computer-based technologies. This book is devoted to various aspects of the management of intelligent systems. Particular attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of linguistic nature. Various methods developed to manage such information are discussed in the context of several domains of application. Topics included in the book include preference modelling and decision making, learning, clustering and data mining, information retrieval. The paradigm of computing with words is also addressed.

Intelligent systems enhance the capacities made available by the internet and other computer-based technologies. This book deals with the theory behind the solutions to difficult problems in the construction of intelligent systems. Particular attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of linguistic nature. Various methodologies for these cases are discussed, among which are probabilistic, possibilistic, fuzzy, logical, evidential and network-based frameworks. One purpose of the book is to consider how these methods can be used cooperatively. Topics included in the book include fundamental issues in uncertainty, the rapidly emerging discipline of information aggregation, neural networks, bayesian networks and other network methods, as well as logic-based systems.

This volume in the NATO Special Programme on Advanced Educational Technology addresses fundamental principles in the design of a dialogue component in intelligent tutoring systems. The purpose of the book is to link fundamental issues of communication and interaction to the more restricted domain of instructional dialogue. The papers are grouped into parts on: theoretical issues in instructional dialogue; theory into practice - interaction in learning environments; natural dialogue and interaction theory; and feedback and control in human-machine communication. The book originates from a NATO Advanced Research Workshop held in Italy in 1992 and the authors are leading researchers in educational technology, dialogue research and user-interface design.

3. Textbook for a course in expert systems, if an emphasis is placed on Chapters 1 to 3 and on a selection of material from Chapters 4 to 7. There is also the option of using an additional commercially available sheU for a programming project. In assigning a programming project, the instructor may use any part of a great variety of books covering many subjects, such as car repair. Instructions for mostofthe "weekend mechanic" books are close stylisticaUy to expert system rules. Contents Chapter 1 gives an introduction to the subject matter; it briefly presents basic concepts, history, and some perspectives ofexpert systems. Then itpresents the architecture of an expert system and explains the stages of building an expert system. The concept of uncertainty in expert systems and the necessity of deal ing with the phenomenon are then presented. The chapter ends with the descrip tion of taxonomy ofexpert systems. Chapter 2 focuses on knowledge representation. Four basic ways to repre sent knowledge in expert systems are presented: first-order logic, production sys tems, semantic nets, and frames. Chapter 3 contains material about knowledge acquisition. Among machine learning techniques, a methodofrule learning from examples is explained in de tail. Then problems ofrule-base verification are discussed. In particular, both consistency and completeness oftherule base are presented."

Among the most important problems confronting computer science is that of developing a paradigm appropriate to the discipline. Proponents of formal methods - such as John McCarthy, C.A.R. Hoare, and Edgar Dijkstra - have advanced the position that computing is a mathematical activity and that computer science should model itself after mathematics. Opponents of formal methods - by contrast, suggest that programming is the activity which is fundamental to computer science and that there are important differences that distinguish it from mathematics, which therefore cannot provide a suitable paradigm. Disagreement over the place of formal methods in computer science has recently arisen in the form of renewed interest in the nature and capacity of program verification as a method for establishing the reliability of software systems. A paper that appeared in Communications of the ACM entitled, Program Verification: The Very Idea', by James H. Fetzer triggered an extended debate that has been discussed in several journals and that has endured for several years, engaging the interest of computer scientists (both theoretical and applied) and of other thinkers from a wide range of backgrounds who want to understand computer science as a domain of inquiry. The editors of this collection have brought together many of the most interesting and important studies that contribute to answering questions about the nature and the limits of computer science. These include early papers advocating the mathematical paradigm by McCarthy, Naur, R. Floyd, and Hoare (in Part I), others that elaborate the paradigm by Hoare, Meyer, Naur, and Scherlis and Scott (in Part II), challenges, limits and alternatives explored by C. Floyd, Smith, Blum, and Naur (in Part III), and recent work focusing on formal verification by DeMillo, Lipton, and Perlis, Fetzer, Cohn, and Colburn (in Part IV). It provides essential resources for further study. This volume will appeal to scientists, philosophers, and laypersons who want to understand the theoretical foundations of computer science and be appropriately positioned to evaluate the scope and limits of the discipline.

This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.

The International Workshop on "Human Interaction with Machines" is the sixth in a successful series of workshops that were established by Shanghai Jiao Tong University and Technische Universitat Berlin. The goal of those workshops is to bring together researchers from both universities in order to present research results to an international community. The series of workshops started in 1990 with the International Workshop on "Artificial Intelligence" and was continued with the International Workshop on "Advanced Software Technology" in 1994. Both workshops have been hosted by Shanghai Jiaotong University. In 1998 the third wo- shop took place in Berlin. This International Workshop on "Communi- tion Based Systems" was essentially based on results from the Graduiertenkolleg on Communication Based Systems that was funded by the German Research Society (DFG) from 1991 to 2000. The fourth Int- national Workshop on "Robotics and its Applications" was held in Sha- hai in 2000. The fifth International Workshop on "The Internet Challenge: Technology and Applications" was hosted by TU Berlin in 2002."

Bettina Büchel explores the relationship between information technology and organizations from a range of perspectives, with special focus on the managerial implications stemming from this relationship. She draws on organizational theory, management science and computer science, and case studies from companies in Europe and Asia.

Intelligent technologies are the essential factors of innovation, and enable the industry to overcome technological limitations and explore the new frontiers. Therefore it is necessary for scientists and practitioners to cooperate and inspire each other, and use the latest research results in creating new designs and products. The idea of this book came out with the industrial workshop organized at the ISMIS conference in Warsaw, 2011. The book covers several applications of emerging, intelligent technologies in various branches of the industry. The contributions describe modern intelligent tools, algorithms and architectures, which have the potential to solve real problems, experienced by practitioners in various industry sectors. We hope this volume will show new directions for cooperation between science and industry and will facilitate efficient transfer of knowledge in the area of intelligent information systems.

The goal of this book is to crystallize the emerging mobile computing technologies and trends by focusing on the most promising solutions in services computing. The book will provide clear proof that mobile technologies are playing an increasingly important and critical role in supporting toy computing. The goal of this book is to bring together academics and practitioners to describe the use and synergy between the above-mentioned technologies. This book is intended for researchers and students working in computer science and engineering, as well as toy industry technology providers, having particular interests in mobile services.

Computer-Aided Reasoning: ACL2 Case Studies illustrates how the computer-aided reasoning system ACL2 can be used in productive and innovative ways to design, build, and maintain hardware and software systems. Included here are technical papers written by twenty-one contributors that report on self-contained case studies, some of which are sanitized industrial projects. The papers deal with a wide variety of ideas, including floating-point arithmetic, microprocessor simulation, model checking, symbolic trajectory evaluation, compilation, proof checking, real analysis, and several others. Computer-Aided Reasoning: ACL2 Case Studies is meant for two audiences: those looking for innovative ways to design, build, and maintain hardware and software systems faster and more reliably, and those wishing to learn how to do this. The former audience includes project managers and students in survey-oriented courses. The latter audience includes students and professionals pursuing rigorous approaches to hardware and software engineering or formal methods. Computer-Aided Reasoning: ACL2 Case Studies can be used in graduate and upper-division undergraduate courses on Software Engineering, Formal Methods, Hardware Design, Theory of Computation, Artificial Intelligence, and Automated Reasoning. The book is divided into two parts. Part I begins with a discussion of the effort involved in using ACL2. It also contains a brief introduction to the ACL2 logic and its mechanization, which is intended to give the reader sufficient background to read the case studies. A more thorough, textbook introduction to ACL2 may be found in the companion book, Computer-Aided Reasoning: An Approach. The heart of the book isPart II, where the case studies are presented. The case studies contain exercises whose solutions are on the Web. In addition, the complete ACL2 scripts necessary to formalize the models and prove all the properties discussed are on the Web. For example, when we say that one of the case studies formalizes a floating-point multiplier and proves it correct, we mean that not only can you read an English description of the model and how it was proved correct, but you can obtain the entire formal content of the project and replay the proofs, if you wish, with your copy of ACL2. ACL2 may be obtained from its home page, http: //www.cs.utexas.edu/users/moore/acl2. The results reported in each case study, as ACL2 input scripts, as well as exercise solutions for both books, are available from this page.

Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications.

Cooperative working environments and their development are becoming increasingly important and ever more frequent in different industrial sectors and this book provides a scientific approach for managing Team Engineering. Meta-cognitive knowledge and networks are identified as the key resources enabling engineering teams to work effectively and to reduce engineering time and this book illustrates how computer support can aid cooperative work within the context of practical methodologies and examples. The fields covered in the book include: State-of-the-art research in cooperative learning tools; Practical examples and methodologies illustrating the implementation of cooperative networks; and An interdisciplinary approach to team engineering. This valuable new book is sponsored by the International Federation for Information Processing (IFIP) and will be essential reading for researchers, engineers, technical managers involved in the development of advanced applications for engineering and manufacturing, and software design and engineering.