Artificial Intelligence Books

“Introduction to Artificial Intelligence and Expert Systems” Book Review: This textbook provides a comprehensive coverage of the important aspects of artificial intelligence and expert systems. The book is organized into five parts based on a detailed analysis of knowledge: Introduction to Artificial Intelligence, Knowledge representation, Knowledge Organization and Manipulation, Perception, Communication and Expert Systems, and Knowledge Acquisition. The textbook contains substantial discussions on Knowledge Representation, NLP, Computer Vision, Neural Networks, Expert Systems, and Memory Organization etc.

“Foundations of Artificial Intelligence and Expert Systems” Book Review: This book provides exposition on various facets of artificial intelligence in an easy to understand format. The coverage of the book sweeps through a broad range of concepts, focusing on the basics and building through the concepts. The various chapters present in the book are: Concept of Artificial Intelligence, An overview of Japanese Fifth Generation Computer Systems, The Search Process, Game Playing, Logic, Robotics, Knowledge Representation, Non-Monotonic, Probabilistic, Certainty and Fuzzy-Based Reasoning Systems, Natural Language Processing, Computer Vision. It also discusses topics such as Successful Expert Systems, Introduction to Expert Systems, Knowledge Engineering, Logic Programming and PROLOG, Artificial Intelligence in Industry, Artificial Intelligence Machines etc. The book can serve as a relevant reference to graduate and postgraduate students.

“Artificial Intelligence: A Guide to Intelligent Systems” Book Review: This textbook demonstrates the ideas behind intelligent systems in a simple and straightforward manner. It covers rule-based expert systems, fuzzy expert systems, frame based expert systems, artificial neural networks, evolutionary computations, hybrid intelligent systems and knowledge engineering. The book is composed of a total of nine chapters. Some of the chapters present in the book are: Uncertainty Management in Rule-based Expert Systems, Knowledge Engineering and Data Mining, Frame-Based Expert Systems etc. The book can benefit undergraduate students in computer science engineering and related fields.

“Artificial Intelligence: A Beginner’s Guide (Beginner’s Guides)” Book Review: This textbook intends to provide a basic introduction to the concepts of Artificial Intelligence. The readers do not require any previous knowledge to understand the concepts covered in the textbook. The textbook is meant for a general audience. Therefore, the content of the book is neither hardcore technical nor scholarly. The book is organized into six chapters. The chapters present in the book are: What is AI? AI at Work, AI and Biology, Some Challenges, AI diffuses and Present and Future Trends. The book can provide an interesting read to those who have no idea what AI means but are willingly to dwell in the world of AI.

“Make Your Own Neural Network: A Gentle Journey Through the Mathematics of Neural Networks, and Making Your Own Using the Python Computer Language” Book Review: This book provides a detailed study of the mathematics of neural networks. It also describes how to make neural networks using the Python computer language. The book starts with the basics and then goes on to describe how the neural networks work. The first part introduces the mathematical ideas underlying the neural network. In the next part, it introduces the popular and easy way to learn the Python programming language. The readers get to know how to build up a neural network which can learn to recognise human handwritten numbers. The third part extends further the practical ideas discussed in part two. The combination of diagrams and mathematics help to clear the concepts in a concise way. It is useful for beginners in neural networks.

“Artificial Intelligence and Neural Networks” Book Review: This book provides the fundamental concepts of Artificial Intelligence and Artificial Neural Networks. The first five chapters deal with artificial intelligence and the next 6 chapters deal with neural networks. The first part of the book covers the introduction and history of AI, applications of AI, modelling of intelligent systems and their characterization using PEAS. Search algorithms, Propositional logic and First Order Predicate Logic are also discussed. The second part covers topics in neural networks such as the evolution of ANN, McCulloch Pitts Model, Learning paradigms, learning tasks, perception, etc. The diagrams given in the book provide technical understanding of the subject matter. The book is a useful learning source for students of undergraduate courses in electrical science.

“Artificial Intelligence and Neural Networks” Book Review: This book contains the thorough proceedings of the 14th Turkish Symposium on Artificial Intelligence and Neural Networks. It provides lecture notes in several topics of computer science. The book presents 26 revised full papers in different topics. The topics covered in the book are robotics, image processing, classification, learning theory and support vector machines. Besides, fuzzy neural networks, robotics, fuzzy logic, machine learning, engineering applications, and neural networks architecture are also included in the book. The book is useful for specialists in the area of artificial intelligence and neural networks.

“VLSI for Artificial Intelligence and Neural Networks” Book Review: This book is a selection of the papers presented at the International Workshop on VLSI for Artificial Intelligence and Neural Networks. The readers get to know about the increasing complexity of artificial intelligence and neural networks algorithms. The book describes the increasing applications of these systems. The readers learn about the requirements of artificial intelligence namely- symbolic manipulation, knowledge representation, non-deterministic computations and dynamic resource allocation. The book ends with a description of constraints and demands that are imposed on the computer architectures for these applications. It provides a practical knowledge of artificial intelligence systems. The book will benefit students and practising engineers dealing with software engineering and computer science.

“Applied Artificial Intelligence: A compact introduction to neural networks and deep learning” Book Review: This book covers the basics of Artificial Neural Networks (ANN). The first part explains how to implement neural networks in Python and apply this technique to any given problem. In step-by-step examples, the reader learns how to implement neural networks in Python and to solve non-linear problems. The book explains how neural networks are built, trained with sample data sets and how these networks are capable of solving complex problems. The second part shows how to build machine learning models in Google TensorFlow and how to bring Artificial Intelligence into production. The last part deals with practical and machine learning examples. The book is useful for students and practising engineers working with software engineering, python and computer science.

“Neural Networks: Artificial Intelligence and Industrial Applications” Book Review: This book contains papers presented at the Third Annual SNN Symposium on Neural Networks. The papers are divided into two sections- the first gives an overview of new developments in neurobiology, the cognitive sciences, robotics, vision and data modelling. The second presents working neural network solutions to real industrial problems, including process control, finance and marketing. The book gives a comprehensive view of the state of the art in 1995. It is useful for postgraduate students and academic as well as industrial researchers. Through case studies, the book attempts to provide a practical understanding of neural networks.

“Neural Networks and Artificial Intelligence” Book Review: This book is a compilation of the proceedings of the 8th International Conference on Neural Networks and Artificial Intelligence. The nineteen papers provide a comprehensive overview in several topics. The papers are organized in sections covering different topics such as forest resource management, artificial intelligence by neural networks, optimization and classification. Other topics like fuzzy approach, machine intelligence, analytical approach, mobile robot and real world application are also described thoroughly. The examples and pictures provide a practice-oriented understanding of the subject matter. The book is useful for software engineers, researchers and students in the field of computer science engineering.

“Artificial Neural Networks: An Introduction to ANN Theory and Practice” Book Review: This book presents a compilation of tutorial lectures given during a school on Artificial Neural Networks for the industrial world. The major ANN architectures are discussed to show their powerful possibilities for empirical data analysis, particularly in situations where other methods seem to fail. Theoretical insight is offered by examining the underlying mathematical principles in a detailed manner. Practical experience is provided by discussing several real-world applications such areas as control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM. The book thus presents a blend of theoretical and practice-oriented learning. It will benefit researchers, graduate students and practising engineers in the field of computer science and software engineering.

“Artificial Neural Networks (Methods in Molecular Biology)” Book Review: This book provides a practical understanding of how ANNs are applied in biological sciences and related areas. The chapters included in the book focus on the analysis of intracellular sorting information, prediction of the behavior of bacterial communities and biometric authentication. In addition, the book discusses studies of Tuberculosis, gene signatures in breast cancer classification, use of mass spectrometry in metabolite identification, visual navigation, and computer diagnosis. For more convenience, chapters include introductions to their respective topics. The book includes application details for the readers and tips on troubleshooting as well. It will be a helpful learning source for scientists studying artificial neural networks.

“Intelligent Engineering Systems through Artificial Neural Networks” Book Review: This book contains the proceedings of the Annie Conference, November 2006, St. Louis, Missouri. The papers present the concept of smart engineering system design and its applications in data mining, neural networks, complex networks, evolutionary programming, adaptive control, pattern recognition, and fuzzy logic.

“Robotics and Artificial Intelligence” Book Review: This book is a collection of papers on the subject of Robotics and Artificial Intelligence. It also includes the topics that were presented at the program of NATO advanced study institute. The readers are able to attain knowledge from several examples on sensing and educational methodologies in the subject area. The Introduction and Overview chapter of this book includes a topic “State-of-the-Art and Predictions for Artificial Intelligence and Robotics”. This chapter provides an advanced understanding on the topics of artificial intelligence and robotics. The book is useful for practitioners of artificial intelligence and software engineering. It will also benefit students and researchers in the field of artificial intelligence and robotics.

“Forbidden Gates: How Genetics, Robotics, Artificial Intelligence, Synthetic Biology, Nanotechnology, and Human Enhancement Herald, The Dawn of the Techno-Dimensional” Book Review: The book includes description of traditional, tried and advanced methods of overcoming darkness. It also provides an overview of advances in science, technology, and philosophy including cybernetics, bio-engineering, nanotechnology, etc. The book is an interesting study of the technological, cultural, and metaphysical shift that predicts a future dominated by this new species of superior humans. This includes among other things rewriting human DNA and combining men with beasts. The concept of transhumanism is explained in a detailed manner with illustrations. The book is meant for the readers interested in scientific fiction. It will also appeal to those interested in advancement of technology.

“Computational Intelligence, Control and Computer Vision in Robotics and Automation” Book Review: This book presents the state-of-the-art technologies on robotics research. It includes several recent investigations on navigation, motion planning of mobile robots,etc. Soft computing approaches to control of single and multiple rigid robots are also looked at. The book provides research in the areas of robotics and automation from countries like India, USA, Canada, United Kingdom, Mexico and Malaysia. In addition, it provides new directions of robotics applications e.g. electrical power line maintenance. The book gives a blend of practical and theoretical understanding. It is useful for researchers and practitioners working in the fields of robotics and artificial intelligence.

“Robotics: Modelling, Planning and Control (Advanced Textbooks in Control and Signal Processing)” Book Review: This is a classic text on robot manipulators that covers visual control, motion planning and mobile robots.It provides the basic know-how on the foundations of robotics- modelling, planning and control. The book includes coverage of fundamental topics like kinematics, and trajectory planning and related technological aspects including actuators and sensors. To provide practical skills, examples and case studies are given throughout the book. In addition, the end-of-chapter exercises are included so that the readers can test their understanding of the subject matter. The book comes with an electronic solutions manual containing the MATLAB code for computer problems. It is useful for graduate students and industry practitioners.

“Robots” Book Review: The book provides an accessible and engaging account of robots. It covers the current state of the field, the fantasies of popular culture, and implications for life and work. The book includes the prehistory of robots and the treatment of robots in science fiction, movies, and television. The readers get to know the state of robotics in today’s world. It provides a detailed account of the components of robots and the complicating factors that make robotics so challenging. Applications such as driverless cars, unmanned warfare, and robots on the assembly line are also discussed. The book is useful for social scientists and engineers.

“Assistive Technology and Artificial Intelligence: Applications in Robotics, User Interfaces and Natural Language Processing (Lecture Notes in Computer Science)” Book Review: This book is a collection of research papers on assistive technology presented at the AAAI workshops. It focuses on the advancement and use of AI stimulated technology. The book explains how the users can extend their current range of cognitive and sensory abilities or overcome their motor disabilities. It addresses various issues in the area of assistive technology. The papers address topics from natural language processing, planning, robotics, user interface design, computer vision, and learning. The research helps the readers to get a practical understanding of the topics. The book will benefit graduate students, researchers and practising engineers in the field of artificial intelligence.

“Fundamentals of Robotic Mechanical Systems: Theory, Methods, and Algorithms (Mechanical Engineering Series)” Book Review: This book is a comprehensive study of robots. It discusses several kinds of robots such as remote manipulators, multifingered hands, walking machines, flight simulators, and machine tools. In the beginning, the book reviews the elements of rigid-body mechanics and of linear transformations. This helps the readers to get familiar with the basics of the subject. The book includes exercises at the end of each chapter as well as within the chapters, that helps the readers to test their understanding. The book is useful for practising engineers, undergraduate and graduate students.

“McGraw-Hill Illustrated Encyclopedia of Robotics and Artificial Intelligence” Book Review: This book provides an extensive study of robotics and artificial intelligence (AI). It includes 500 articles that are alphabetically arranged, so that these can be found easily by the readers. The articles are based on different topics such as robots and automation, robots and AI in medicine, military use of robots, etc. Other technical topics such as robotics and safety, robotics and security, robotic space probes and reliability factors are also discussed in detail. The articles provided in the book are illustrated with pictures and diagrams that encourage self study among readers. The book will benefit researchers, practitioners and students in robotics and artificial intelligence.

“Introduction to Artificial Neural Systems” Book Review: The book covers algorithms of Artificial Neural Networks while commenting on their stability. The book is recommended to neural engineers interested in the domain. The first chapters familiarize the readers with the fundamentals of neural networks. The book eventually dwells into more complex topics such as applications in software. The reader can find various illustrations, pseudocodes that help in a clearer understanding of the subject. The book is written in a comprehensible manner.

“Intelligent Systems in Process Engineering” Book Review: The book integrates concepts of Artificial Intelligence with those of operations research, estimation and control theory, and statistics. The book elucidates the concepts using various models, each developed pertaining to an engineering problem such as product design, process design, process operations monitoring, planning, scheduling, or control. Each developed pattern also brings forward a key concept of AI including modeling languages, automation in design. symbolic and quantitative reasoning, inductive and deductive reasoning. A few other concepts described in the book are searching spaces of discrete solutions, non-monotonic reasoning, analogical learning, empirical learning through neural networks, reasoning in time, and logic in numerical computing.