Introduces Intelligent IoT as applicable to key areas towards smart healthcare Discusses computational intelligence and IoT based optimizations of smart healthcare systems Explores effective management of healthcare systems using dedicated IoT based infrastructures Includes dedicated chapters on securing patient's confidential data Reviews diagnosis of critical diseases from medical imaging using advanced deep learning-based approaches

Proposing a new paradigm for Computer Supported Cooperative Work (CSCW), this ground-breaking book presents a research agenda for developing and testing that paradigm. It constitutes the first attempt to outline a comprehensive model of collaboration that integrates the cognitive/conceptual and social dynamics of groups. br br The challenge faced by all groups engaged in intellectual work is, on the one hand, to divide the task so that efforts of i individual members /i may proceed in parallel and, on the other hand, to synthesize their separate contributions to form a coherent whole. Addressing this challenge, Smith examines the general form of a theory of computer-based collaboration that extends across different tasks and working situations. He uses the work of Newell, Simon, and Anderson as a base from which to consider a group as a form of distributed information processing system. Within groups, there are constructs analogous to human long-term and short-term memory, conceptual processes, and problem solving and knowledge-construction strategies. He discusses two metacognitive issues -- awareness and control -- as they occur in collaborative behavior. And he reviews a number of advanced computer systems that support collaboration, focusing on their impact on the thinking and behavior of groups. br br Smith's theoretical framework combines elements of Information Processing System theory -- and its detailed process models of cognitive behavior -- with the situated perspective of activity theory. The book suggests new and useful ways of conceiving problems and solutions to all those interested in the ways in which people interact with each other and with computers to achievegoals. br

The primary aim of this volume is to provide researchers and engineers from both academic and industry with up-to-date coverage of new results in the field of robotic welding, intelligent systems and automation. The book is mainly based on papers selected from the 2019 International Workshop on Intelligentized Welding Manufacturing (IWIWM'2019) in USA. The articles show that the intelligentized welding manufacturing (IWM) is becoming an inevitable trend with the intelligentized robotic welding as the key technology. The volume is divided into four logical parts: Intelligent Techniques for Robotic Welding, Sensing of Arc Welding Processing, Modeling and Intelligent Control of Welding Processing, as well as Intelligent Control and its Applications in Engineering.

This work presents a goal-based model of decision making in which the relative priorities of goals drive the decision process -- a psychological alternative to traditional decision analysis. Building on the work of Schank and Abelson, the author uses goals as the basis for a model of interpersonal relations which permits decisions to incorporate personal and adopted goals in a uniform manner. The theory is modelled on the VOTE computer program which simulates Congressional roll-call voting decisions.
The VOTE program expands traditional decision making and simulation models by providing not only a choice, but also a natural language explanation, in either English or French. It simulates real members of Congress voting on real bills, and producing reasonable explanations. The program is consistent with much of the descriptive political science literature on Congressional decision making and provides an explicit model of political issues, relationships, and strategies that converge in voting behavior.
In developing the VOTE program, the author draws on his own practical experience in politics from four presidential campaigns and the White House. Given the underlying psychological basis of the program, VOTE can be extended to other decision making domains different from politics. Another use for the program is to simulate business decisions such as securities analysis, as well as mundane decision making such as choosing a college or deciding whether to get a Mohawk haircut.

The result of the first Appalachian Conference on neurodynamics, this volume focuses on processing in biological neural networks. How do brain processes become organized during decision making? That is, what are the neural antecedents that determine which course of action is to be pursued? Half of the contributions deal with modelling synapto-dendritic and neural ultrastructural processes; the remainder, with laboratory research findings, often cast in terms of the models. The interchanges at the conference and the ensuing publication also provide a foundation for further meetings. These will address how processes in different brain systems, coactive with the neural residues of experience and with sensory input, determine decisions.

Artificial intelligence (AI) is presented as a solution to the greatest challenges of our time, from global pandemics and chronic diseases to cybersecurity threats and the climate crisis. But AI also contributes to the climate crisis by running on technology that depletes scarce resources and by relying on data centres that demand excessive energy use. Is AI Good for the Planet? brings the climate crisis to the centre of debates around AI, exposing its environmental costs and forcing us to reconsider our understanding of the technology. It reveals why we should no longer ignore the environmental problems generated by AI. Embracing a green agenda for AI that puts the climate crisis at centre stage is our urgent priority. Engaging and passionately written, this book is essential reading for scholars and students of AI, environmental studies, politics, and media studies and for anyone interested in the connections between technology and the environment.

Highlighting and illustrating several important and interesting theoretical trends that have emerged in the continuing development of instructional technology, this book's organizational framework is based on the notion of two opposing camps. One evolves out of the intelligent tutoring movement, which employs artificial-intelligence technologies in the service of student modeling and precision diagnosis, and the other emerges from a constructivist/developmental perspective that promotes exploration and social interaction, but tends to reject the methods and goals of the student modelers. While the notion of opposing camps tends to create an artificial rift between groups of researchers, it represents a conceptual distinction that is inherently more interesting and informative than the relatively meaningless divide often drawn between "intelligent" and "unintelligent" instructional systems.
An evident trend is that researchers in both "camps" view their computer learning environments as "cognitive tools" that can enhance learning, performance, and understanding. Cognitive tools are objects provided by the instructional environment that allow students to incorporate new auxiliary methods or symbols into their social problem solving which otherwise would be unavailable. A final section of the book represents researchers who are assimilating and accommodating the wisdom and creativity of their neighbors from both camps, perhaps forming the look of technology for the future. When the idea of model tracing in a computer-based environment is combined with appreciation for creative mind-extension cognitive tools and for how a community of learners can facilitate learning, a camp is created where AI technologists and social constructivist learning theorists can feel equally at home.

Over the last decade research into design processes utilizing ideas and models drawn from artificial intelligence has resulted in a better understanding of design -- particularly routine design -- as a process. Indeed, most of the current research activity directly or indirectly deals only with routine design. Not surprisingly, many practicing designers state that the level of understanding represented by these models is only of mild interest because they fail to embody any ideas about creativity.
This volume provides a set of chapters in the areas of modeling creativity and knowledge-based creative design that examines the potential role and form of computer-aided design which supports creativity. It aims to define the state-of-the-art of computational creativity in design as well as to identify research directions. Published at a time when the field of computational creativity in design is still immature, it should influence the directions of growth and assist the field in reaching maturity.

This book aims to present a summary of recent work on the interface between Artificial Intelligence and Statistics. It does this through presenting a series of papers by different authors working in different areas of this interface. These papers are a selected and referenced subset of papers presented at the 3rd International Workshop on Artificial Intelligence and Statistics, Florida, January 1991.

Morality seems to be irrational. Moral agents spread co-operation - this is good for all, but even better for the amoral. If "the virtuous" finish last, one cannot defend morality as rational. "Artificial Morality" addresses and answers this objection, by showing how to build moral agents that succeed in competition with amoral agents. Professor Danielson's agents deviate from the received theory of rational choice. They are bound by moral principles and communicate their principles to others. The central thesis of the book is that these moral agents are more successful in crucial tests, and therefore rational. Why design agents? Human agents and the situations they create are too complex for an investigation of the most elementary aspects of rationality and morality. Danielson uses instead robots paired in abstract games that model social problems, such as environmental pollution, which reward co-operators but even more those that benefit from others' constraint. It is shown that virtuous, not vicious, robots do better in these virtual games. This book should be of interest to those working in the fields of philosophy, artificial intelligence and computer studies.

Morality seems to be irrational. Moral agents spread co-operation - this is good for all, but even better for the amoral. If "the virtuous" finish last, one cannot defend morality as rational. "Artificial Morality" addresses and answers this objection, by showing how to build moral agents that succeed in competition with amoral agents. Professor Danielson's agents deviate from the received theory of rational choice. They are bound by moral principles and communicate their principles to others. The central thesis of the book is that these moral agents are more successful in crucial tests, and therefore rational. Why design agents? Human agents and the situations they create are too complex for an investigation of the most elementary aspects of rationality and morality. Danielson uses instead robots paired in abstract games that model social problems, such as environmental pollution, which reward co-operators but even more those that benefit from others' constraint. It is shown that virtuous, not vicious, robots do better in these virtual games. "Artificial Morality" is inspired by artificial intelligence. The solution presented to the problem of rationality and morality is construct

This book presents the 2nd International Conference on Artificial Intelligence and Computer Visions (AICV 2021) proceeding, which took place in Settat, Morocco, from June 28- to 30, 2021. AICV 2021 is organized by the Scientific Research Group in Egypt (SRGE) and the Computer, Networks, Mobility and Modeling Laboratory (IR2M), Hassan 1st University, Faculty of Sciences Techniques, Settat, Morocco. This international conference highlighted essential research and developments in the fields of artificial intelligence and computer visions. The book is divided into sections, covering the following topics: Deep Learning and Applications; Smart Grid, Internet of Things, and Mobil Applications; Machine Learning and Metaheuristics Optimization; Business Intelligence and Applications; Machine Vision, Robotics, and Speech Recognition; Advanced Machine Learning Technologies; Big Data, Digital Transformation, AI and Network Analysis; Cybersecurity; Feature Selection, Classification, and Applications.

In light of the enormous interest in building intelligent systems, this volume blends theory, applications, and methodology of cybernetics taking it out of the realm of the abstract and explaining how cybernetics can contribute to an improved understanding of intelligence. Among the topics of the 17

The design and functioning of an information system improve to the extent that the system can handle the questions people ask. Surprisingly, however, researchers in the cognitive, computer, and information sciences have not thoroughly examined the multitude of relationships between information systems and questions -- both question asking and answering. The purpose of this book is to explicitly examine these relationships. Chapter contributors believe that questions play a central role in the analysis, design, and use of different kinds of natural or artificial information systems such as human cognition, social interaction, communication networks, and intelligent tutoring systems. Their efforts show that data structures and representations need to be organized around the questioning mechanisms in order to achieve a quick retrieval of relevant useful information.

This book introduces the applications of Industry 4.0 in machine tools through an overview of the latest available digital technologies. It focuses on digital twining, communication between industrial controls, motion, and input/output devices, along with sustainability in SMEs. Machine Tools: An Industry 4.0 Perspective focuses on the digital twining of machine tools, which improves the life of the machines and provides a method of operating a factory during times of complete lockdown resulting from various conditions. It presents an overview of the communication between industrial controls, motion, and input/output devices through standardized digital interfaces such as SERCOS and USB. The book goes on to discuss industrial cybersecurity systems applicable to discrete manufacturing, which includes cyberattacks and human errors, and address the security aspects related to software, hardware, and data. The book also explores the application of big data for different stages of production and illustrates the uses such as predictive maintenance, product quality, product life cycle management (PLM), and more. This book is an ideal reference for undergraduate, graduate, and postgraduate students of industrial, mechanical, and mechatronics engineering, along with professionals, and general readers.

This book highlights the most important research areas in Information and Communication Technologies as well as research in fields of telecommunication system characteristics at the physical level, deep discussion of telecommunication traffic and its performance indicators, studying of information systems technological parameters, review of public and special applications of information technologies. The book includes strictly selected results of the most interesting scientific research presented at the 10th International Conference "Infocommunications - Present and Future" (IPF'2020) that was held in Odesa, Ukraine. The respective chapters share in-depth and extended results in these areas with a view to resolving practically relevant and challenging issues including: 1. research of telecommunication system characteristics at the physical level: the discussion of various aspects of the signal transmission quality indicators analysis for solving practically important issues in telecommunication systems; 2. research of telecommunication traffic and its performance indicators: the significant aspects of research for forecasting of services characteristics of telecommunication systems; 3.research of information systems technological parameters: the discission of some effective technological solutions that can be used for the implementation of novel systems; 4. research of public and special applications of information technologies: the discussion of the various aspects of scientific and educational applications, etc. These results can be used in the implementation of novel systems and to promote the exchange of information in e-societies. Given its scope, the book offers a valuable resource for scientists, lecturers, specialists working at enterprises, graduate and undergraduate students who engage with problems in Information and Communication Technologies as well as Radio Electronics.

This unique volume focuses on computing systems that exhibit intelligent behavior. As such, it discusses research aimed at building a computer that has the same cognitive architecture as the mind -- permitting evaluations of it as a model of the mind -- and allowing for comparisons between computer performance and experimental data on human performance. It also examines architectures that permit large, complex computations to be performed -- and questions whether the computer so structured can handle these difficult tasks intelligently.

ARTIFICIAL INTELLIGENCE-BASED SMART POWER SYSTEMS Authoritative resource describing artificial intelligence and advanced technologies in smart power systems with simulation examples and case studies Artificial Intelligence-based Smart Power Systems presents advanced technologies used in various aspects of smart power systems, especially grid-connected and industrial evolution. It covers many new topics such as distribution phasor measurement units, blockchain technologies for smart power systems, the application of deep learning and reinforced learning, and artificial intelligence techniques. The text also explores the potential consequences of artificial intelligence and advanced technologies in smart power systems in the forthcoming years. To enhance and reinforce learning, the editors include many learning resources throughout the text, including MATLAB, practical examples, and case studies. Artificial Intelligence-based Smart Power Systems includes specific information on topics such as: Modeling and analysis of smart power systems, covering steady state analysis, dynamic analysis, voltage stability, and more Recent advancement in power electronics for smart power systems, covering power electronic converters for renewable energy sources, electric vehicles, and HVDC/FACTs Distribution Phasor Measurement Units (PMU) in smart power systems, covering the need for PMU in distribution and automation of system reconfigurations Power and energy management systems Engineering colleges and universities, along with industry research centers, can use the in-depth subject coverage and the extensive supplementary learning resources found in Artificial Intelligence-based Smart Power Systems to gain a holistic understanding of the subject and be able to harness that knowledge within a myriad of practical applications.

This is a collection of essays on issues related to the evolutionary design and the practical future of intelligent tutoring systems. Following in the tradition of Foundations of Intelligent Tutoring Systems and Intelligent Tutoring Systems: Lessons Learned, this volume examines some of the visions and near-term issues that have been further explored and better defined since those groundbreaking books first appeared. Questions addressed in this volume include:
*How can knowledge bases generate explanations?
*Will case-based reasoning techniques be worth pursuing in the ITS framework?
*Will high performance skills be successfully taught in an ITS design?
*Are there dimensions of ITS design which the research laboratories are ignoring, and ignoring at the customer's peril?
Of particular importance to those engaged in research and development, this book will be of value to all who wish to apprise themselves of the advances being made in the rapidly evolving field of intelligent tutoring systems.

This is a collection of essays on issues related to the evolutionary design and the practical future of intelligent tutoring systems. Following in the tradition of Foundations of Intelligent Tutoring Systems and Intelligent Tutoring Systems: Lessons Learned, this volume examines some of the visions and near-term issues that have been further explored and better defined since those groundbreaking books first appeared. Questions addressed in this volume include:
*How can knowledge bases generate explanations?
*Will case-based reasoning techniques be worth pursuing in the ITS framework?
*Will high performance skills be successfully taught in an ITS design?
*Are there dimensions of ITS design which the research laboratories are ignoring, and ignoring at the customer's peril?
Of particular importance to those engaged in research and development, this book will be of value to all who wish to apprise themselves of the advances being made in the rapidly evolving field of intelligent tutoring systems.

These proceedings of the 2014 Pacific-Asia Workshop on Computational Intelligence in Industrial Application (CIIA 2014) include 81 peer-reviewed papers. The topics covered in the book include: (1) Computer Intelligence, (2) Application of Computer Science and Communication, (3) Industrial Engineering, Product Design and Manufacturing, (4) Automation and Control, Information Technology and MEMS.

Artificial Intelligence is a seemingly neutral technology, but it is increasingly used to manage workforces and make decisions to hire and fire employees. Its proliferation in the workplace gives the impression of a fairer, more efficient system of management. A machine can't discriminate, after all. Augmented Exploitation explores the reality of the impact of AI on workers' lives. While the consensus is that AI is a completely new way of managing a workplace, the authors show that, on the contrary, AI is used as most technologies are used under capitalism: as a smokescreen that hides the deep exploitation of workers. Going beyond platform work and the gig economy, the authors explore emerging forms of algorithmic governance and AI-augmented apps that have been developed to utilise innovative ways to collect data about workers and consumers, as well as to keep wages and worker representation under control. They also show that workers are not taking this lying down, providing case studies of new and exciting form of resistance that are springing up across the globe.

A recent area of interest in the Artificial Intelligence community has been the application of massively parallel algorithms to enhance the choice mechanism in traditional AI problems. This volume provides a detailed description of how marker-passing -- a parallel, non-deductive, spreading activation algorithm -- is a powerful approach to refining the choice mechanisms in an AI problem-solving system.
The author scrutinizes the design of both the algorithm and the system, and then reviews the current literature and research in planning and marker passing. Also included: a comparison of this computer model with some standard cognitive models, and a comparison of this model to the "connectionist" approach.

AI-ENABLED 6G NETWORKS AND APPLICATIONS Provides authoritative guidance on utilizing AI techniques in 6G network design and optimization Written and edited by active researchers, this book covers hypotheses and practical considerations and provides insights into the design of evolutionary AI algorithms for 6G networks, with focus on network transparency, interpretability and simulatability for vehicular networks, space systems, surveillance systems and their usages in different emerging engineering fields. AI-Enabled 6G Networks and Applications includes a review of AI techniques for 6G Networks and will focus on deployment of AI techniques to efficiently and effectively optimize the network performance, including AI-empowered mobile edge computing, intelligent mobility and handover management, and smart spectrum management. This book includes the design of a set of evolutionary AI hybrid algorithms with communication protocols, showing how to use them in practice to solve problems relating to vehicular networks, aerial networks, and communication networks. Reviews various types of AI techniques such as AI-empowered mobile edge computing, intelligent handover management, and smart spectrum management Describes how AI techniques manage computation efficiency, algorithm robustness, hardware development, and energy management Identifies and provides solutions to problems in current 4G/5G networks and emergent 6G architectures Discusses privacy and security issues in IoT-enabled 6G Networks Examines the use of machine learning to achieve closed-loop optimization and intelligent wireless communication AI-Enabled 6G Networks and Applications is an essential reference guide to advanced hybrid computational intelligence methods for 6G supportive networks and protocols, suitable for graduate students and researchers in network forensics and optimization, computer science, and engineering.

Artificial intelligence (AI) opens new opportunities for STEM education in K-12, higher education, and professional education contexts. This book summarizes AI in education (AIED) with a particular focus on the research, practice, and technological paradigmatic shifts of AIED in recent years. The 23 chapters in this edited collection track the paradigmatic shifts of AIED in STEM education, discussing how and why the paradigms have shifted, explaining how and in what ways AI techniques have ensured the shifts, and envisioning what directions next-generation AIED is heading in the new era. As a whole, the book illuminates the main paradigms of AI in STEM education, summarizes the AI-enhanced techniques and applications used to enable the paradigms, and discusses AI-enhanced teaching, learning, and design in STEM education. It provides an adapted educational policy so that practitioners can better facilitate the application of AI in STEM education. This book is a must-read for researchers, educators, students, designers, and engineers who are interested in the opportunities and challenges of AI in STEM education.