To endow computers with common sense is one of the major long-term goals of artificial intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic. Commonsense Reasoning: An Event Calculus Based Approach is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions that span many areas of the commonsense world. The Second Edition features new chapters on commonsense reasoning using unstructured information including the Watson system, commonsense reasoning using answer set programming, and techniques for acquisition of commonsense knowledge including crowdsourcing.

Recent advances in socio-cognitive and affective computing require further study as countless benefits and opportunities have emerged from these innovative technologies that may be useful in a number of contexts throughout daily life. In order to ensure these technologies are appropriately utilized across sectors, the challenges and strategies for adoption as well as potential uses must be thoroughly considered. Principles and Applications of Socio-Cognitive and Affective Computing discusses several aspects of affective interactions and concepts in affective computing, the fundamentals of emotions, and emerging research and exciting techniques for bridging the emotional disparity between humans and machines, all within the context of interactions. The book also considers problem and solution guidelines emerging in cognitive computing, thus summarizing the roadmap of current machine computational intelligence techniques for affective computing. Covering a range of topics such as social interaction, robotics, and virtual reality, this reference work is crucial for scientists, engineers, industry professionals, academicians, researchers, scholars, practitioners, instructors, and students.

The Intelligent Systems Series publishes reference works and handbooksin three core sub-topic areas: Intelligent Automation, Intelligent Transportation Systems, and Intelligent Computing. They include theoretical studies, design methods, and real-world implementations and applications. The series' readership is broad, but focuses on engineering, electronics, and computer science.

Budget constraints and optimization in sponsored search auctions takes into account consideration of the entire life cycle of campaigns for researchers and developers working on search systems and ROI maximization. The highly experienced authors compiled their knowledge and experience to provide insight, algorithms and development techniques for successful optimized/constrained systems. The book presents a cutting-edge budget optimization approach that embraces three-level budget decisions in the life cycle of search auctions: allocation across markets at the system level, distribution over temporal slots at the campaign level, and real-time adjustment at the keyword level.
Delivers a systematic overview and technique for understanding budget constraints and ROI optimization in sponsored search auction systems, including algorithms and developer guides for a range of scenariosExplores effects of constraints on mechanisms, bidding and keyword strategies, and the strategies for budget optimization that developers can employAn informative reference source for both software and systems developers working in the search auctions, marketing and sales strategy optimization, services development for online marketing and advertisement, e-commerce, social and economic networking"

Review of Marketing Research pushes the boundaries of marketing-broadening the marketing concept to make the world a better place. Here, leading scholars explore how marketing is currently shaping, and being shaped by, the evolution of Artificial Intelligence (AI). Topics covered include the effects of AI on: economics; personalisation; pricing; content generation; the identification, structuring, and prioritization of customer needs; customer feedback; Natural Language Processing; image analytics; deep learning; and the anthropomorphism of AI, such as in virtual assistants and chatbots. Each chapter provides thought provoking discussions which will be relevant to researchers, professionals, and students.

Revealing the unfolding story of Artificial Intelligence, Richard Susskind presents a short non-technical guide that challenges us to think differently about AI. Susskind brings AI out of computing laboratories, big tech companies, and start-ups - and into everyday life.

In recent years, and certainly since the launch of ChatGPT, there has been massive public and professional interest in Artificial Intelligence. But people are confused about what AI is, what it can and cannot do, what is yet to come, and whether AI is good or bad for humanity and civilisation - whether it will provide solutions to mankind's major challenges or become our gravest existential threat. There is also confusion about how we should regulate AI and where we should draw moral boundaries on its use.

In How To Think About AI, Richard Susskind draws on his experience of working on AI since the early 1980s. For Susskind, balancing the benefits and threats of artificial intelligence is the defining challenge of our age. He explores the history of AI and possible scenarios for its future. His views on AI are not always conventional. He positions ChatGPT and generative AI as no more than the latest chapter in the ongoing story of AI and claims we are still at the foothills of developments. He argues that to think responsibly about the impact of AI requires us to look well beyond todayâs technologies, suggesting that not-yet-invented technologies will have far greater impact on us in the 2030s than the tools we have today. This leads Susskind to discuss the possibility of conscious machines, magnificent new AI-enabled virtual worlds, and the impact of AI on the evolution of biological humans.

Over the last 20 years, the role of unmanned aircraft systems in modern warfare has grown at an unprecedented rate. No longer simply used for intelligence, data collection or reconnaissance, drones are routinely used for target acquisition and to strike enemy targets with missiles and bombs. Organized by nationality, Military Drones offers a compact guide to the main unmanned aerial vehicles being flown in combat zones today. These include classics, such as the MQ-1 Predator, primarily used for intelligence gathering; the Black Hornet Nano, a micro UAV that is so small it can fit in the palm of your hand and is used by ground troops for local situational awareness; the Chinese tri-copter Scorpion, which is ideal for the stationary observation and strike role in a built-up area; and the French EADS Talarion, a twinjet long-endurance UAV designed for high-altitude surveillance. Illustrated with more than 100 photographs and artworks, Military Drones provides a detailed insight into the specialist military unmanned aerial vehicles that play a key role in the modern battle space.

The internet provides a vast amount of data which can be utilised to explore different approaches to solving industry problems. Efficient methods for the retrieval of this information are essential for streamlined business processes. Information Retrieval Methods for Multidisciplinary Applications provides innovative research on information gathering, web data mining, and automation systems. Addressing multidisciplinary applications and focusing on theories and methods with an enterprise-wide perspective, this book is essential for information engineers, scientists, and related professionals.

This textbook offers an insightful study of the intelligent Internet-driven revolutionary and fundamental forces at work in society. Readers will have access to tools and techniques to mentor and monitor these forces rather than be driven by changes in Internet technology and flow of money. These submerged social and human forces form a powerful synergistic foursome web of (a) processor technology, (b) evolving wireless networks of the next generation, (c) the intelligent Internet, and (d) the motivation that drives individuals and corporations. In unison, the technological forces can tear human lives apart for the passive or provide a cohesive set of opportunities for the knowledgeable to lead and reap the rewards in the evolved knowledge society.

The book also provides in-depth coverage of the functions embedded in modern processors and intelligent communication networks. It focuses on the convergence of the design of modern processor technologies with the switching and routing methodologies of global intelligent networks. Most of the concepts that are generic to the design of terra-flop parallel processors and the terra-bit fiber-optic networks are presented. This book also highlights recent developments in computer and processor technologies into the microscopic and macroscopic medical functions in hospitals and medical centers.
Examination of the latest technologies and innovations presented from academic and industrial perspectives of the concurrent dynamic changes in computer and communication industriesAn up-to-date and coherent perspective of the developments in the wireless and fiber optic network technologies based on the experience and developments in the older copper, cable and hybrid fiber-coaxial communication systemsProvides a set of novel concepts and methodologies for the innovators in industry

"Calculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines" is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus Ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems.

The reduced error logistic regression (RELR) method is proposed as such a "Calculus of Thought." This book reviews how RELR's completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELR's new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today s big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior.
Provides a high-level introduction and detailed reviews of the neural, statistical and machine learning knowledge base as a foundation for a new era of smarter machines Argues that smarter machine learning to handle both explanation and prediction without cognitive bias must have a foundation in cognitive neuroscience and must embody similar explicit and implicit learning principles that occur in the brainOffers a new neuromorphic foundation for machine learning based upon the reduced error logistic regression (RELR) method and provides simple examples of RELR computations in toy problems that can be accessed in spreadsheet workbooks through a companion website"

In recent years, swarm intelligence has become a popular computational approach among researchers working on optimization problems throughout the globe. Several algorithms inside swarm intelligence have been implemented due to their application to real-world issues and other advantages. A specific procedure, Fireworks Algorithm, is an emerging method that studies the explosion process of fireworks within local areas. Applications of this developing program are undiscovered, and research is necessary for scientists to fully understand the workings of this innovative system. The Handbook of Research on Fireworks Algorithms and Swarm Intelligence is a pivotal reference source that provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm. This book is ideally designed for researchers, data scientists, mathematicians, engineers, software developers, postgraduates, and academicians seeking coverage on this evolutionary computation method.

Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field.

The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security.
very relevant to current research challenges faced in various fieldsself-contained reference to machine learning

emphasis on applications-oriented techniques

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers.
Focuses on the introduction and analysis of key algorithms Includes case studies for real-world applicationsContains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

Image and Video Processing is an active area of research due to its potential applications for solving real-world problems. Integrating computational intelligence to analyze and interpret information from image and video technologies is an essential step to processing and applying multimedia data. Emerging Technologies in Intelligent Applications for Image and Video Processing presents the most current research relating to multimedia technologies including video and image restoration and enhancement as well as algorithms used for image and video compression, indexing and retrieval processes, and security concerns. Featuring insight from researchers from around the world, this publication is designed for use by engineers, IT specialists, researchers, and graduate level students.

In clear, readable language, consultant and researcher Kevin Desouza accomplishes an unlikely feat: explaining artificial intelligence to nonspecialists, in a way that experts will recognize and accept as correct and immediately applicable. Workers in knowledge management are relatively isolated from each other, businesspeople are still unconvinced that artificial intelligence has much to offer, and engineers creating the latest algorithm or device seldom consider its value for businesspeople--Desouza seeks to change all that.

He maintains that knowledge will be traded like physical goods, and that businesses must leverage knowledge resources within its organizations to survive in a highly competitive marketplace. Introducing us the concepts and significance of knowledge management, he shows that incorporating artificial intelligence computer-based techniques into business settings can provide truly significant gains in productivity. This book is among the first of its kind to provide a comprehensive one-stop guide to the basics of knowledge management, plus a lucid explanation of A.I., and how to use it in almost all types of organizational settings.

Recent advances in eye tracking technology will allow for a proliferation of new applications. Improvements in interactive methods using eye movement and gaze control could result in faster and more efficient human computer interfaces, benefitting users with and without disabilities. Gaze Interaction and Applications of Eye Tracking: Advances in Assistive Technologies focuses on interactive communication and control tools based on gaze tracking, including eye typing, computer control, and gaming, with special attention to assistive technologies. For researchers and practitioners interested in the applied use of gaze tracking, the book offers instructions for building a basic eye tracker from off-the-shelf components, gives practical hints on building interactive applications, presents smooth and efficient interaction techniques, and summarizes the results of effective research on cutting edge gaze interaction applications.

Modern devices, from phones and cars to houses and the appliances within them, are being designed with formidable computational power and expanded functionality. To be truly effective, these smart devices must effectively process data from their environment and experiences and make decisions based on that information. Recent Advances in Ambient Intelligence and Context-Aware Computing investigates the functionality of ubiquitous computational systems and how they may adapt to their environment to improve the quality of interaction for the end-user. This reference book will be of value to under- and post-graduate students, professionals, and researchers networking, computer science, communications, and other information technology disciplines.

This book provides a snapshot of the state of current research at the interface between machine learning and healthcare with special emphasis on machine learning projects that are (or are close to) achieving improvement in patient outcomes. The book provides overviews on a range of technologies including detecting artefactual events in vital signs monitoring data; patient physiological monitoring; tracking infectious disease; predicting antibiotic resistance from genomic data; and managing chronic disease. With contributions from an international panel of leading researchers, this book will find a place on the bookshelves of academic and industrial researchers and advanced students working in healthcare technologies, biomedical engineering, and machine learning.

The development of artificial intelligence (AI) involves the creation of computer systems that can do activities that would ordinarily require human intelligence, such as visual perception, speech recognition, decision making, and language translation. Through increasingly complex programming approaches, it has been transforming and advancing the discipline of computer science. Artificial Intelligence Methods and Applications in Computer Engineering illuminates how today's computer engineers and scientists can use AI in real-world applications. It focuses on a few current and emergent AI applications, allowing a more in-depth discussion of each topic. Covering topics such as biomedical research applications, navigation systems, and search engines, this premier reference source is an excellent resource for computer scientists, computer engineers, IT managers, students and educators of higher education, librarians, researchers, and academicians.

Information in today's advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.