The joint breakthrough of big data, cloud computing and deep learning has made artificial intelligence (AI) the new focus in the international arena. AI is a branch of computer science, developing intelligent machine with imitating, extending and augmenting human intelligence through artificial means and techniques to realize intelligent behaviour.This comprehensive compendium, consisting of 15 chapters, captures the updated achievements of AI. It is completely revised to reflect the current researches in the field, through numerous techniques and strategies to address the impending challenges facing computer scientists today.The unique volume is useful for senior or graduate students in the information field and related tertiary specialities. It is also a suitable reference text for professionals, researchers, and academics in AI, machine learning, electrical & electronic engineering and biocomputing.

Artificial intelligence is a branch of computer science and a discipline in the study of machine intelligence, that is, developing intelligent machines or intelligent systems imitating, extending and augmenting human intelligence through artificial means and techniques to realize intelligent behavior.Advanced Artificial Intelligence consists of 16 chapters. The content of the book is novel, reflects the research updates in this field, and especially summarizes the author's scientific efforts over many years. The book discusses the methods and key technology from theory, algorithm, system and applications related to artificial intelligence. This book can be regarded as a textbook for senior students or graduate students in the information field and related tertiary specialities. It is also suitable as a reference book for relevant scientific and technical personnel.

Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples Key FeaturesAI-based examples to guide you in designing and implementing machine intelligenceBuild machine intelligence from scratch using artificial intelligence examplesDevelop machine intelligence from scratch using real artificial intelligenceBook Description AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions. What you will learnApply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google TranslateUnderstand chained algorithms combining unsupervised learning with decision treesSolve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graphLearn about meta learning models with hybrid neural networksCreate a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data loggingBuilding conversational user interfaces (CUI) for chatbotsWriting genetic algorithms that optimize deep learning neural networksBuild quantum computing circuitsWho this book is for Developers and those interested in AI, who want to understand the fundamentals of Artificial Intelligence and implement them practically. Prior experience with Python programming and statistical knowledge is essential to make the most out of this book.

This comprehensive text acquaints the readers with the important aspects of artificial intelligence (AI) and intelligent systems and guides them towards a better understanding of the subject. The text begins with a brief introduction to artificial intelligence, including application areas, its history and future, and programming. It then deals with symbolic logic, knowledge acquisition, representation and reasoning. The text also lucidly explains AI technologies such as computer vision, natural language processing, pattern recognition and speech recognition. Topics such as expert systems, neural networks, constraint programming and case-based reasoning are also discussed in the book. In the Second Edition, the contents and presentation have been improved thoroughly and in addition six new chapters providing a simulating and inspiring synthesis of new artificial intelligence and an appendix on AI tools have been introduced. The treatment throughout the book is primarily tailored to the curriculum needs of B.E./B.Tech. students in Computer Science and Engineering, B.Sc. (Hons.) and M.Sc. students in Computer Science, and MCA students. The book is also useful for computer professionals interested in exploring the field of artificial intelligence. Key Features • Exposes the readers to real-world applications of AI. • Concepts are duly supported by examples and cases. • Provides appendices on PROLOG, LISP and AI Tools. • Incorporates most recommendations of the Curriculum Committee on Computer Science/Engineering for AI and Intelligent Systems. • Exercises provided will help readers apply what they have learned.

This book focuses on the design of displays and user interfaces for the older user. Aging is related to complex mental, physical, and social changes. While conventional wisdom says getting older leads to a decline, the reality is that some capabilities decline with age while others remain stable or increase. This book distills decades of aging research into practical advice on the design of displays. Technology has changed dramatically since the publication of the first edition. This new edition covers cutting-edge technology design such as ubiquitous touchscreens, smart speakers, and augmented reality interfaces, among others.

The quest for building an artificial brain developed in the fields of computer science and psychology. Artificial intelligence (AI), sometimes called machine intelligence, refers to intelligence demonstrated by machines, while the natural intelligence is the intelligence displayed by humans and animals. Typically, AI systems demonstrate at least some of the following human behaviors: planning, learning, reasoning, problem solving, knowledge representation, perception, speech recognition, decision-making, language translation, motion, manipulation, intelligence, and creativity. Artificial intelligence is an emerging technology which the educational sector can benefit from. In this book, we consider the applications of AI in key areas of education. Artificial intelligence in education (AIED) refers to the application of AI technologies in educational settings to facilitate teaching, learning, or decision making. AI will impact the education field in the areas of administration, instruction, and personalized, and individualized learning applications. In this book, AI is specifically applied in the following key educational sectors: education, natural sciences, social sciences, computer science, engineering, business, and medicine.

Systems theorists see common principles in the structure and operation of systems of all kinds and sizes. They promote an interdisciplinary science adapted for a universal application with a common language and area of concepts. In order to solve problems, make recommendations and predict the future, they use theories, models and concepts from the vast area of general systems theory. This approach is chosen as a means to overcome the fragmentation of knowledge and the isolation of the specialist but also to find new approaches to problems created by earlier 'solution of problems.'This revised and updated second edition of General Systems Theory — Ideas and Applications includes new systems theories and a new chapter on self-organization and evolution. The book summarizes most of the fields of systems theory and its application systems science in one volume. It provides a quick and readable reference guide for future learning containing both general theories and practical applications without the use of complicated mathematics.

A global perspective on AI The rise of AI and super-intelligent AI raises ethical issues. AI is the power behind Google’s search engine, enables social media sites to serve up targeted advertising, gives Alexa and Siri their voices, and enables OpenAI’s ChatGPT to produce written responses from just a few prompts by the user. It is also the technology enabling self-driving vehicles, predictive policing, and autonomous weapons that can kill without direct human intervention. All of these bring up complex ethical issues that are still unresolved and will continue to be the subject of ongoing debate. This book: Explores the complex topic of AI ethics in a cross-functional way; Enables understanding of the associated ethical challenges of AI technologies; Provides an up-to-date overview of the potential positive and negative outcomes of AI implementations; and Has been updated to reflect the ethical challenges of AI in 2024 and beyond, and the moral imperative of navigating this new terrain. This book presents a concrete approach to identifying appropriate ethical principles in AI solutions AI is much more than just a simple tool powering our smartphones or allowing us to ask Alexa about the latest cinema times. It is a technology that is, in very subtle but unmistakable ways, exerting an ever-increasing influence over our lives – and the more we use it, the more AI is altering our existence. This book presents a concrete approach to identifying appropriate ethical principles in AI solutions. There are untold how-to books on AI technology, replete with methods to improve and advance the statistics and algorithms of AI; however, the social, ethical and security impacts are often a secondary consideration – if they are discussed at all. This book explores the complex topic of AI ethics in a cross-functional way, alternating between theory and practice. Practical and recent events, and their associated challenges, are presented, such as the collateral effects of the COVID-19 pandemic on the application of AI technologies. The book also gives an up-to-date overview of the potential positive and negative outcomes of AI implementations together with an analysis of AI from an ethical perspective. Before you dive into a world populated with AI, read this book to understand the associated ethical challenges of AI technologies.

The most common form of severe dementia, Alzheimer’s disease (AD), is a cumulative neurological disorder because of the degradation and death of nerve cells in the brain tissue, intelligence steadily declines and most of its activities are compromised in AD. Before diving into the level of AD diagnosis, it is essential to highlight the fundamental differences between conventional machine learning (ML) and deep learning (DL). This work covers a number of photo-preprocessing approaches that aid in learning because image processing is essential for the diagnosis of AD. The most crucial kind of neural network for computer vision used in medical image processing is called a Convolutional Neural Network (CNN). The proposed study will consider facial characteristics, including expressions and eye movements using the diffusion model, as part of CNN’s meticulous approach to Alzheimer’s diagnosis. Convolutional neural networks were used in an effort to sense Alzheimer’s disease in its early stages using a big collection of pictures of facial expressions.