A radical and challenging book which argues that artificial intelligence needs a completely different set of foundations, based on ecological intelligence rather than human intelligence, if it is to deliver on the promise of a better world. This can usher in the greatest transformation in human history, an age of re-integration. Our very existence is dependent upon our context within the Earth System, and so, surely, artificial intelligence must also be grounded within this context, embracing emergence, interconnectedness and real-time feedback. We discover many positive outcomes across the societal, economic and environmental arenas and discuss how this transformation can be delivered. Key Features: Identifies a key weakness in current AI thinking, that threatens any hope of a better world. Highlights the importance of realizing that systems theory is an essential foundation for any technology that hopes to positively transform our world. Emphasizes the need for a radical new approach to AI, based on ecological systems. Explains why ecosystem intelligence, not human intelligence, offers the best framework for AI. Examines how this new approach will impact on the three arenas of society, environment and economics, ushering in a new age of re-integration.

Underwater robots play a significant role in ocean exploration. This book provides full coverage of the theoretical and practical aspects of bionic gliding underwater robots, including system design, modeling control, and motion planning. To overcome the inherent shortcomings of traditional underwater robots that can simultaneously lack maneuverability and endurance, a new type of robot, the bionic gliding underwater robot, has attracted much attention from scientists and engineers. On the one hand, by imitating the appearance and swimming mechanisms of natural creatures, bionic gliding underwater robots achieve high maneuverability, swimming efficiency, and strong concealment. On the other hand, borrowing from the buoyancy adjustment systems of underwater gliders, bionic gliding underwater robots can obtain strong endurance, which is significant in practical applications. Taking gliding robotic dolphin and fish as examples, the designed prototypes and proposed methods are discussed, offering valuable insights into the development of next-generation underwater robots that are well suited for various oceanic applications. This book will be of great interest to students and professionals alike in the field of robotics or intelligent control. It will also be a great reference for engineers or technicians who deal with the development of underwater robots.

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 book describes concepts and tools needed for water resources management, including methods for modeling, simulation, optimization, big data analysis, data mining, remote sensing, geographical information system, game theory, conflict resolution, System dynamics, agent-based models, multiobjective, multicriteria, and multiattribute decision making and risk and uncertainty analysis, for better and sustainable management of water resources and consumption, thus mitigating the present and future global water shortage crisis. It presents the applications of these tools through case studies which demonstrate its benefits of proper management of water resources systems. This book acts as a reference for students, professors, industrial practitioners, and stakeholders in the field of water resources and hydrology.

Introduce yourself to the nuances of modern monitoring for cloud-native applications running on Kubernetes clusters. This book will help you get started with the concepts of monitoring, introduce you to popular open-source monitoring tools, and help with finding the correct set of use cases for their implementation. It covers the in-depth technical details of open-source software used in modern monitoring systems that are tailor made for environments running microservices. Monitoring Cloud-Native Applications is divided into two parts. Part 1 starts with an introduction to cloud-native applications and the foundational concepts of monitoring. It then walks you through the various aspects of monitoring containerized workloads using Kubernetes as the de-facto orchestration platform. You will dive deep into the architecture of a modern monitoring system and look at its individual components in detail. Part 2 introduces you to popular open-source tools which are used by enterprises and startups alike and are well established as the tools of choice for industry stalwarts. First off, you will look at Prometheus and understand its architecture and usage. You will also learn about InfluxDB, formerly called TICK Stack (Telegraf, InfluxDB, Chronograf, and Kapacitor). You will explore the technical details of its architecture and the use cases which it solves. In the next chapter, you will be introduced to Grafana, a multi-platform open source analytics and interactive visualization tool that can help you with visualization of data and dashboards. After reading this book, you will have a much better understanding of key terminologies and general concepts around monitoring and observability. You will also be able to select a suitable monitoring solution from the bouquet of open-source monitoring solutions available for applications, microservices, and containers. Armed with this knowledge, you will be better prepared to design and lead a successful agile operations team. What You Will Learn Monitor and observe of metrics, events, logs, and traces Carry out infrastructure and application monitoring for microservices architecture Analyze and visualize collected data Use alerting, reporting, and automated actions for problem resolution Who This Book Is For DevOps administrators, cloud administrators, and site reliability engineers (SREs) who manage and monitor applications and cloud infrastructure on a day-to-day basis within their organizations.

This introductory overview explores the methods, models and interdisciplinary links of artificial economics, a new way of doing economics in which the interactions of artificial economic agents are computationally simulated to study their individual and group behavior patterns. Conceptually and intuitively, and with simple examples, Mercado addresses the differences between the basic assumptions and methods of artificial economics and those of mainstream economics. He goes on to explore various disciplines from which the concepts and methods of artificial economics originate; for example cognitive science, neuroscience, artificial intelligence, evolutionary science and complexity science. Introductory discussions on several controversial issues are offered, such as the application of the concepts of evolution and complexity in economics and the relationship between artificial intelligence and the philosophies of mind. This is one of the first books to fully address artificial economics, emphasizing its interdisciplinary links and presenting in a balanced way its occasionally controversial aspects.

This book constitutes the refereed proceedings of the 15th International Conference on Brain Informatics, BI 2022, held as hybrid event in Padua, Italy (in person) and Queensland, Australia (online) in July 2022. The 29 papers were selected from 65 submissions and the main theme of BI 2022 is Brain Science meets Artificial Intelligence with respect to the five tracks: Cognitive and computational foundations of brain science; human information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; and brain-machine intelligence and brain inspired computing.

Computational intelligence, a sub-branch of artificial intelligence, is a field which draws on the natural world and adaptive mechanisms in order to study behaviour in changing complex environments. This book provides an interdisciplinary view of current technological advances and challenges concerning the application of computational intelligence techniques to financial time-series forecasting, trading and investment. The book is divided into five parts. The first part introduces the most important computational intelligence and financial trading concepts, while also presenting the most important methodologies from these different domains. The second part is devoted to the application of traditional computational intelligence techniques to the fields of financial forecasting and trading, and the third part explores the applications of artificial neural networks in these domains. The fourth part delves into novel evolutionary-based hybrid methodologies for trading and portfolio management, while the fifth part presents the applications of advanced computational intelligence modelling techniques in financial forecasting and trading. This volume will be useful for graduate and postgraduate students of finance, computational finance, financial engineering and computer science. Practitioners, traders and financial analysts will also benefit from this book.

This book aims to provide the latest research findings, innovative research results, methods, and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and their applications. The networks and information systems of today are evolving rapidly. There are new trends and applications in information networking such as wireless sensor networks, ad hoc networks, peer-to-peer systems, vehicular networks, opportunistic networks, grid and cloud computing, pervasive and ubiquitous computing, multimedia systems, security, multi-agent systems, high-speed networks, and web-based systems. These kinds of networks need to manage the increasing number of users, provide support for different services, guarantee the QoS, and optimize the network resources. For these networks, there are many research issues and challenges that should be considered and find solutions.

Under current business law, it is already possible to give legal personhood, or a very close surrogate of it, to software systems of any kind (from a simple automated escrow agent to a more hypothetical, truly smart artificial intelligence). This means that, for example, robots could enter into contracts, serve as legal agents, or own property. Ultimately, entire companies could actually be run by non-human agents. This study argues that this is not as scary as it might sound at first. Legal theorist and noted software developer Shawn Bayern argues that autonomous or zero-person organizations offer an opportunity for useful new types of interactions between software and the law. This creative contribution to the theory and practice of law and technology explores the social and political aspects of these new organizational structures and their implications for legal theory.

This book is addressed to young researchers and engineers in the fields of Computational Science and Artificial Intelligence, ranging from innovative computational methods to digital machine learning tools and their coupling used for solving challenging industrial and societal problems.This book provides the latest knowledge from jointly academic and industries experts in Computational Science and Artificial Intelligence fields for exploring possibilities and identifying challenges of applying Computational Sciences and AI methods and tools in industrial and societal sectors.

Marxist discourse around automation has recently become waylaid with breathless techno-pessimist dystopias and fanciful imaginations of automated luxury communism. This collection of essays by both established veterans of the field and new voices is a refreshingly sober materialist reflection on recent technological developments within capitalist production. It covers a broad range of digital aspects now proliferating across our work and lives, including chapters on the digitalisation of agriculture, robotics in the factory and the labour process on crowdworking platforms. It looks to how 20th century Marxist predictions of the 'workerless factory' are, or are not, coming true, and how 'Platform Capitalism' should be understood and critiqued. Through rich empirical, theoretical and historical material, this book is necessary reading for those wanting a clear overview of our digital world.

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data.

The book examines the extent to which Chinese cyber and network security laws and policies act as a constraint on the emergence of Chinese entrepreneurialism and innovation. Specifically, how the contradictions and tensions between data localisation laws (as part of Network Sovereignty policies) affect innovation in artificial intelligence (AI). The book surveys the globalised R&D networks, and how the increasing use of open-source platforms by leading Chinese AI firms during 2017-2020, exacerbated the apparent contradiction between Network Sovereignty and Chinese innovation. The drafting of the Cyber Security Law did not anticipate the changing nature of globalised AI innovation. It is argued that the deliberate deployment of what the book refers to as 'fuzzy logic' in drafting the Cyber Security Law allowed regulators to subsequently interpret key terms regarding data in that Law in a fluid and flexible fashion to benefit Chinese innovation.

It is often said that quantum technologies are poised to change the world as we know it, but cutting through the hype, what will quantum technologies actually mean for countries and their citizens? In Law and Policy for the Quantum Age, Chris Jay Hoofnagle and Simson L. Garfinkel explain the genesis of quantum information science (QIS) and the resulting quantum technologies that are most exciting: quantum sensing, computing, and communication. This groundbreaking, timely text explains how quantum technologies work, how countries will likely employ QIS for future national defense and what the legal landscapes will be for these nations, and how companies might (or might not) profit from the technology. Hoofnagle and Garfinkel argue that the consequences of QIS are so profound that we must begin planning for them today. This title is available as Open Access on Cambridge Core.

This book presents findings from the papers accepted at the Cyber Security Education Stream and Cyber Security Technology Stream of The National Cyber Summit's Research Track, reporting on the latest advances on topics ranging from software security to cyber attack detection and modelling to the use of machine learning in cyber security to legislation and policy to surveying of small businesses to cyber competition, and so on. Understanding the latest capabilities in cyber security ensures that users and organizations are best prepared for potential negative events. This book is of interest to cyber security researchers, educators, and practitioners, as well as students seeking to learn about cyber security.

CYBERSECURITY IN INTELLIGENT NETWORKING SYSTEMS Help protect your network system with this important reference work on cybersecurity Cybersecurity and privacy are critical to modern network systems. As various malicious threats have been launched that target critical online services--such as e-commerce, e-health, social networks, and other major cyber applications--it has become more critical to protect important information from being accessed. Data-driven network intelligence is a crucial development in protecting the security of modern network systems and ensuring information privacy. Cybersecurity in Intelligent Networking Systems provides a background introduction to data-driven cybersecurity, privacy preservation, and adversarial machine learning. It offers a comprehensive introduction to exploring technologies, applications, and issues in data-driven cyber infrastructure. It describes a proposed novel, data-driven network intelligence system that helps provide robust and trustworthy safeguards with edge-enabled cyber infrastructure, edge-enabled artificial intelligence (AI) engines, and threat intelligence. Focusing on encryption-based security protocol, this book also highlights the capability of a network intelligence system in helping target and identify unauthorized access, malicious interactions, and the destruction of critical information and communication technology. Cybersecurity in Intelligent Networking Systems readers will also find: Fundamentals in AI for cybersecurity, including artificial intelligence, machine learning, and security threats Latest technologies in data-driven privacy preservation, including differential privacy, federated learning, and homomorphic encryption Key areas in adversarial machine learning, from both offense and defense perspectives Descriptions of network anomalies and cyber threats Background information on data-driven network intelligence for cybersecurity Robust and secure edge intelligence for network anomaly detection against cyber intrusions Detailed descriptions of the design of privacy-preserving security protocols Cybersecurity in Intelligent Networking Systems is an essential reference for all professional computer engineers and researchers in cybersecurity and artificial intelligence, as well as graduate students in these fields.

This book presents the proceedings of the International Conference on Computers Communications and Control 2020 (ICCCC2020), covering topics such as theory for computing and communications, integrated solutions in computer-based control, computational intelligence and soft computing, decision-making and support systems. The ICCCC was founded in Romania in 2006, and its eight editions have featured respected keynote speakers and leading computer scientists from around the globe.

Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Applications of Artificial Intelligence reviews the research, focusing on state-of-the-art projects in the field. The book captures the breadth and depth of the medical applications of artificial intelligence, exploring new developments and persistent challenges.

Understanding Artificial Intelligence Provides students across majors with a clear and accessible overview of new artificial intelligence technologies and applications Artificial intelligence (AI) is broadly defined as computers programmed to simulate the cognitive functions of the human mind. In combination with the Neural Network (NN), Big Data (BD), and the Internet of Things (IoT), artificial intelligence has transformed everyday life: self-driving cars, delivery drones, digital assistants, facial recognition devices, autonomous vacuum cleaners, and mobile navigation apps all rely on AI to perform tasks. With the rise of artificial intelligence, the job market of the near future will be radically different many jobs will disappear, yet new jobs and opportunities will emerge. Understanding Artificial Intelligence: Fundamentals and Applications covers the fundamental concepts and key technologies of AI while exploring its impact on the future of work. Requiring no previous background in artificial intelligence, this easy-to-understand textbook addresses AI challenges in healthcare, finance, retail, manufacturing, agriculture, government, and smart city development. Each chapter includes simple computer laboratories to teach students how to develop artificial intelligence applications and integrate software and hardware for robotic development. In addition, this text: Focuses on artificial intelligence applications in different industries and sectors Traces the history of neural networks and explains popular neural network architectures Covers AI technologies, such as Machine Vision (MV), Natural Language Processing (NLP), and Unmanned Aerial Vehicles (UAV) Describes various artificial intelligence computational platforms, including Google Tensor Processing Unit (TPU) and Kneron Neural Processing Unit (NPU) Highlights the development of new artificial intelligence hardware and architectures Understanding Artificial Intelligence: Fundamentals and Applications is an excellent textbook for undergraduates in business, humanities, the arts, science, healthcare, engineering, and many other disciplines. It is also an invaluable guide for working professionals wanting to learn about the ways AI is changing their particular field.

This book presents the proceedings of the 2020 International Conference on Intelligent Systems Applications in Multi-modal Information Analytics, held in Changzhou, China, on June 18-19, 2020. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. It addresses a number of broad themes, including data mining, multi-modal informatics, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and a useful reference guide for newcomers to the field.

This proceedings book features selected papers on 12 themes, including telecommunication, power systems, digital signal processing, robotics, control systems, renewable energy, power electronics, soft computing and more. Covering topics such as optoelectronic oscillator at S-band and C-band for 5G telecommunications, neural networks identification of eleven types of faults in high voltage transmission lines, cyber-attack mitigation on smart low voltage distribution grids, optimum load of a piezoelectric-based energy harvester, the papers present interesting ideas and state-of-the-art overviews.

Successful games merge art and technology in truly unique ways. Fused under tight production deadlines and strict performance requirements, shaped by demanding player expectations, games are among the most complex software projects created today. Game AI Pro: Collected Wisdom of Game AI Professionals covers both the art and the technology of game AI. Nothing covered is theory or guesswork. The book brings together the accumulated wisdom, cutting-edge ideas, and clever tricks and techniques of 54 of today's top game AI professionals. Some chapters present techniques that have been developed and passed down within the community for years while others discuss the most exciting new research and ideas from today's most innovative games. The book includes core algorithms that you'll need to succeed, such as behavior trees, utility theory, spatial representation, path planning, motion control, and tactical reasoning. It also describes tricks and techniques that will truly bring your game to life, including perception systems, social modeling, smart camera systems, player prediction, and even an AI sound designer. Throughout, the book discusses the optimizations and performance enhancements that enable your game to run while maintaining 60 frames per second.

The increasing use of artificial intelligence within the workplace is likely to cause significant disruption to the labour market and in turn, to the economy, due to a reduction in the number of taxable workers. In this innovative book, Xavier Oberson proposes taxing robots as a possible solution to the anticipated problem of declining tax revenues. In accordance with guiding legal and economic principles, the book explores the various tax models that could be applied to both the use of robots, such as a usage or automation tax, and to robots directly. Numerous associated issues are discussed, such as the definition of robots for tax purposes, the difficulty of granting a tax capacity to robots, as well as the compatibility of robot taxes with international tax rules. The author concludes by putting forward a possible system for the taxation of robots, taking all of these issues into consideration. Being the first work of its kind to explore the potential for taxing robots in detail, this book will be a unique resource for researchers in the fields of law and economics who have an interest in the impact of artificial intelligence. Lawyers and tax professionals can also benefit from Oberson's insights on what future models of taxation may look like and what the legal consequences may be.