61 Best Books on Artificial Intelligence

“Heart of the Machine: Our Future in a World of Artificial Emotional Intelligence” Book Review: The book primarily explores the realm of emotions and feelings in a future where artificial emotional intelligence plays a significant role. It is organized into three sections, each addressing distinct aspects of this subject. The first section, titled “The Road to Affective Computing,” provides an introduction to the emotional landscape, tracing its origins and exploring the initial development of emotionally aware affective computers and social robots. The second section, “The Rise of the Emotional Machines,” delves into the practical applications of these techniques and the benefits they offer. Finally, the third section, “The Future of Artificial Emotional Intelligence,” examines the societal impact of these technological advancements. It delves into topics such as consciousness, super-intelligence, and their influence on the relationship between humans and machines. By delving into these areas, the book offers valuable insights into the future implications of artificial emotional intelligence.

“Artificial Intelligence in Theory and Practice III” Book Review: This is an insightful book written by Max Bramer. It delves into the realm of artificial intelligence, covering a wide range of topics and practical applications. The chapters in the book explore various aspects of AI, including machine learning, natural language processing, intelligent agents, expert systems, computer vision, and data mining. With its comprehensive coverage and practical approach, this book serves as a valuable resource for students, researchers, and professionals interested in advancing their knowledge and understanding of artificial intelligence.

“KI 2001: Advances in Artificial Intelligence: Joint German/Austrian Conference on AI, Vienna, Austria” Book Review: This book consists of contributions from the joint German/Austrian conference on artificial intelligence, KI 2001. The contents of the book are categorized as follows: it includes 2 contributions by invited speakers from the conference, 29 accepted technical papers (including 5 application papers and 24 papers on the foundations of AI), and 4 contributions from participants of the industrial day.

“Artificial Intelligence: Its Scope and Limits (Studies in Cognitive Systems)” Book Review: This book is designed for postgraduate students studying computer engineering and can be a helpful reference for professionals in the field. It explores various studies focused on information and data processing systems. The book covers topics such as cognitive psychology and sociobiology in the context of artificial intelligence. It also delves into the theoretical and epistemological aspects of these domains. The symbol-system hypothesis proposed by Simon and Newell is discussed in detail. The book provides theorem proofs and presents practical case studies to aid in understanding the concepts.

“Artificial Organic Networks: Artificial Intelligence Based on Carbon Networks” Book Review: This book introduces the principles of Artificial Hydrocarbon Networks (AHNs) and their corresponding computer algorithms. It is highly recommended for researchers and students in the field of computational intelligence. The book starts by providing an overview of various algorithms employed in approximation problems. It then delves into the creation and characterization of artificial organic networks, with a specific focus on AHNs. The concepts of organic networks are explained using graph theory as a foundation. Additionally, the book explores various aspects such as approximation, interference, clustering, control, classification, and audio-signal filtering within the context of AHNs. Finally, the book concludes with a discussion on potential future developments in the field of AHNs.

“Introduction to Artificial Intelligence and Expert Systems” Book Review: This textbook offers a thorough exploration of key elements in artificial intelligence and expert systems. It is structured into five parts, meticulously designed based on a comprehensive knowledge analysis. The sections cover essential topics including Introduction to Artificial Intelligence, Knowledge Representation, Knowledge Organization and Manipulation, Perception, Communication and Expert Systems, and Knowledge Acquisition. Throughout the textbook, you will find extensive discussions on various subjects such as Knowledge Representation, Natural Language Processing (NLP), Computer Vision, Neural Networks, Expert Systems, and Memory Organization.

“Foundations of Artificial Intelligence and Expert Systems” Book Review: This book offers a clear and accessible exposition of various aspects of artificial intelligence. It covers a wide range of concepts, starting from the basics and progressively building upon them. The chapters in the book include an introduction to 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, and Computer Vision. Additionally, it delves into topics such as Successful Expert Systems, Introduction to Expert Systems, Knowledge Engineering, Logic Programming and PROLOG, Artificial Intelligence in Industry, and Artificial Intelligence Machines. This book serves as a valuable reference for both graduate and postgraduate students in the field.

“Artificial Intelligence: A Guide to Intelligent Systems” Book Review: This textbook presents the concepts of intelligent systems in a clear and accessible manner. It explores various types of intelligent systems, including rule-based expert systems, fuzzy expert systems, frame-based expert systems, artificial neural networks, evolutionary computations, hybrid intelligent systems, and knowledge engineering. With a total of nine chapters, the book covers important topics such as Uncertainty Management in Rule-based Expert Systems, Knowledge Engineering and Data Mining, and Frame-Based Expert Systems. It is designed to be beneficial for undergraduate students in computer science engineering and related disciplines.

“Artificial Intelligence: A Beginner’s Guide (Beginner’s Guides)” Book Review: This textbook offers a fundamental introduction to the concepts of Artificial Intelligence, making it accessible to readers without prior knowledge in the field. It caters to a general audience, providing content that is neither excessively technical nor scholarly. The book is divided into six chapters, covering topics such as the definition of AI, its applications in various fields, the connection between AI and biology, existing challenges, the widespread influence of AI, and current and future trends. With its engaging approach, the book serves as an interesting read for individuals who are new to AI but curious to explore its field.

“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 offers an extensive exploration of the mathematical principles behind neural networks, coupled with practical guidance on implementing them using the Python programming language. Beginning with the fundamentals, it progressively delves into the inner workings of neural networks. The initial section introduces the mathematical concepts underlying these networks, while the following part provides a user-friendly introduction to the Python programming language. Readers gain insight into constructing a neural network capable of recognizing handwritten numbers. The third section builds upon the practical knowledge presented in the previous part. The inclusion of diagrams and mathematical explanations facilitates a concise comprehension of the concepts. This book is particularly beneficial for individuals new to neural networks, providing a valuable resource for beginners.

“Artificial Intelligence and Neural Networks” Book Review: This book provides an introduction to Artificial Intelligence (AI) and Artificial Neural Networks (ANNs). The first five chapters cover AI, discussing topics such as its history, applications, intelligent systems modeling, and the PEAS framework. The subsequent six chapters focus on neural networks, including the evolution of ANNs, the McCulloch Pitts Model, learning paradigms, and perception. The book incorporates diagrams to aid in understanding the subject matter. It is a valuable resource for undergraduate students in electrical science seeking to learn about AI and ANNs.

“Artificial Intelligence and Neural Networks” Book Review: This book comprises the comprehensive proceedings of the 14th Turkish Symposium on Artificial Intelligence and Neural Networks. It offers lecture notes covering various topics in computer science. The book features 26 revised full papers encompassing a range of subjects, including robotics, image processing, classification, learning theory, and support vector machines. Additionally, it explores fuzzy neural networks, fuzzy logic, machine learning, engineering applications, and neural network architecture. With its diverse content, the book serves as a valuable resource for specialists in the field of artificial intelligence and neural networks.

“VLSI for Artificial Intelligence and Neural Networks” Book Review: This book features a compilation of papers presented at the International Workshop on VLSI for Artificial Intelligence and Neural Networks. It sheds light on the growing complexity of algorithms in artificial intelligence and neural networks. The book delves into the expanding range of applications for these systems, while also discussing the specific requirements of artificial intelligence, including symbolic manipulation, knowledge representation, non-deterministic computations, and dynamic resource allocation. Furthermore, it explores the constraints and demands placed on computer architectures to support these applications. By providing practical insights into artificial intelligence systems, this book serves as a valuable resource for students and practicing engineers in the fields of software engineering and computer science.

“Applied Artificial Intelligence: A compact introduction to neural networks and deep learning” Book Review: This book provides a comprehensive overview of Artificial Neural Networks (ANN) and their implementation in Python. It guides the reader through step-by-step examples to understand how neural networks can be built and applied to solve non-linear problems. The book also explores the training process using sample datasets and showcases the capability of neural networks to tackle complex tasks. Additionally, it delves into machine learning models with Google TensorFlow and offers practical examples and case studies. Suitable for students and practicing engineers in software engineering, Python, and computer science.

“Neural Networks: Artificial Intelligence and Industrial Applications” Book Review: This book compiles papers presented at the Third Annual SNN Symposium on Neural Networks. It is divided into two sections: the first provides an overview of recent advancements in neurobiology, cognitive sciences, robotics, vision, and data modeling. The second section showcases practical neural network solutions for real-world industrial challenges, such as process control, finance, and marketing. By offering a comprehensive view of the state of the art in 1995, this book serves as a valuable resource for postgraduate students, academic researchers, and professionals in the industry. Through insightful case studies, the book aims to provide a practical understanding of neural networks.

“Neural Networks and Artificial Intelligence” Book Review: This book comprises the proceedings of the 8th International Conference on Neural Networks and Artificial Intelligence. It features nineteen papers that offer a comprehensive overview of various topics. The papers are categorized into sections covering diverse subjects such as forest resource management, artificial intelligence using neural networks, optimization, and classification. Additionally, topics like fuzzy approaches, machine intelligence, analytical approaches, mobile robots, and real-world applications are thoroughly explored. The inclusion of examples and illustrations enhances the practical understanding of the subject matter. This book serves as a valuable resource 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 compiles tutorial lectures from an industrial-focused school on Artificial Neural Networks. It covers the major ANN architectures and their applications in empirical data analysis, particularly when other methods prove inadequate. The book offers a detailed exploration of the underlying mathematical principles, providing both theoretical insight and practical experience. Real-world applications in control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM are discussed. With its blend of theory and practical examples, this book is beneficial for researchers, graduate students, and practicing engineers in computer science and software engineering.

“Artificial Neural Networks (Methods in Molecular Biology)” Book Review: This book offers a practical perspective on the application of ANNs in the field of biological sciences and related areas. The chapters delve into various topics, such as the analysis of intracellular sorting information, prediction of bacterial community behavior, and biometric authentication. Additionally, the book explores studies on Tuberculosis, gene signatures for breast cancer classification, metabolite identification using mass spectrometry, visual navigation, and computer diagnosis. Each chapter provides an introduction to its respective topic, along with application details and troubleshooting tips. With its focus on practical applications, this book serves as a valuable resource for scientists studying artificial neural networks.

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

“Robotics and Artificial Intelligence” Book Review: This book comprises a compilation of papers focused on Robotics and Artificial Intelligence, including topics presented at the NATO advanced study institute program. Through various examples, readers gain insights into sensing techniques and educational methodologies in these fields. The Introduction and Overview chapter, titled “State-of-the-Art and Predictions for Artificial Intelligence and Robotics,” offers an in-depth understanding of the subject matter. The book is valuable for practitioners in artificial intelligence and software engineering, as well as students and researchers exploring the realms 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 provides a description of traditional, tried, and advanced methods for overcoming darkness. It also offers an overview of scientific, technological, and philosophical advances including cybernetics, bio-engineering, nanotechnology, and more. Focusing on the concept of transhumanism, the book explores the potential future dominated by superior humans created through rewriting DNA and merging human and animal characteristics. It is a detailed exploration of this concept with illustrations. The book is intended for readers interested in scientific fiction and those curious about technological advancements.

“Computational Intelligence, Control and Computer Vision in Robotics and Automation” Book Review: This book showcases the latest advancements in robotics research, highlighting state-of-the-art technologies. It features a range of recent investigations on topics such as navigation, motion planning of mobile robots, and more. The book also explores soft computing approaches for controlling single and multiple rigid robots. Drawing from research conducted in various countries including India, USA, Canada, United Kingdom, Mexico, and Malaysia, it offers a diverse perspective on robotics and automation. Furthermore, the book introduces new directions in robotics applications, such as electrical power line maintenance. With its blend of practical insights and theoretical foundations, this book is valuable for researchers and practitioners in the fields of robotics and artificial intelligence.

“Robotics: Modelling, Planning and Control (Advanced Textbooks in Control and Signal Processing)” Book Review: This textbook serves as a valuable resource for understanding robot manipulators. It covers a wide range of topics, including visual control, motion planning, and mobile robots. The book provides essential knowledge about the foundational aspects of robotics, such as modeling, planning, and control. It explores important concepts like kinematics and trajectory planning, as well as the technological components involved, such as actuators and sensors. Throughout the book, practical skills are emphasized, with numerous examples and case studies provided. Each chapter includes exercises to test understanding, and an electronic solutions manual with MATLAB code is available. This book is designed for graduate students and professionals in the field of robotics.

“Hand book of Artificial Intelligence Vol. I” Book Review: This book offers a comprehensive introduction to artificial intelligence, covering its key principles and expanding applications. It discusses essential aspects such as parsing, grammars, and search methods. The book explores various topics, including problem representation, search methods, and sample search programs. It provides a survey of representation techniques and schemes, along with an examination of understanding natural languages, machine translation, grammars, parsing, test generation, and natural language processing systems. With a focus on fundamental concepts, this book serves as a valuable resource for those interested in gaining a solid understanding of artificial intelligence.

“Assistive Technology and Artificial Intelligence: Applications in Robotics, User Interfaces and Natural Language Processing (Lecture Notes in Computer Science)” Book Review: This book comprises a compilation of research papers presented at the AAAI workshops, focusing on the field of assistive technology. It highlights the advancements and applications of AI-driven technology aimed at extending users’ cognitive and sensory abilities and overcoming motor disabilities. The book addresses a range of topics related to assistive technology, including natural language processing, planning, robotics, user interface design, computer vision, and learning. Through these research papers, readers gain practical insights into these areas. The book is a valuable resource for graduate students, researchers, and practicing engineers working in the field of artificial intelligence.

“Fundamentals of Robotic Mechanical Systems: Theory, Methods, and Algorithms (Mechanical Engineering Series)” Book Review: This book offers a comprehensive exploration of various types of robots, including remote manipulators, multifingered hands, walking machines, flight simulators, and machine tools. It begins by providing a review of the fundamental principles of rigid-body mechanics and linear transformations, enabling readers to establish a solid foundation in the subject. Throughout the book, exercises are strategically placed within chapters and at the end of each chapter to allow readers to assess their comprehension and apply their knowledge. With its practical focus, this book is valuable for practicing engineers, as well as undergraduate and graduate students seeking a thorough understanding of robotics.

“McGraw-Hill Illustrated Encyclopedia of Robotics and Artificial Intelligence” Book Review: This book is a comprehensive study of robotics and artificial intelligence (AI). It contains 500 articles organized alphabetically for easy reference. The articles cover various topics, including robots and automation, robots and AI in medicine, and military use of robots. It also explores technical subjects like robotics and safety, robotics and security, and reliability factors in robotic space probes. The book features illustrations, pictures, and diagrams to enhance understanding and encourage self-study. It is a valuable resource for researchers, practitioners, and students interested in robotics and artificial intelligence.

“Introduction to Artificial Neural Systems” Book Review: The book discusses the algorithms of Artificial Neural Networks with a focus on their stability. It is highly recommended for neural engineers who are interested in this field. The initial chapters provide a solid foundation of the fundamentals of neural networks. As the book progresses, it delves into more advanced topics, including software applications. The inclusion of illustrations and pseudocodes throughout the book enhances the clarity and understanding of the subject matter. The book is written in a clear and accessible manner.

“Intelligent Systems in Process Engineering” Book Review: The book combines the principles of Artificial Intelligence with those of operations research, estimation and control theory, and statistics. It presents these concepts through the use of various models, each tailored to address specific engineering problems such as product design, process design, process operations monitoring, planning, scheduling, and control. Through these models, key AI concepts are explored, including modeling languages, automation in design, symbolic and quantitative reasoning, inductive and deductive reasoning. The book also covers additional topics such as searching spaces of discrete solutions, non-monotonic reasoning, analogical learning, empirical learning through neural networks, reasoning in time, and logic in numerical computing.

“Artificial Intelligence: Building Intelligent Systems” Book Review: This book focuses on Artificial Intelligence and is organized into 21 chapters. It provides a comprehensive understanding of concepts related to intelligent systems, covering various fundamental aspects. Readers will gain insights into problem solving, search techniques, intelligent agents, constraint satisfaction problems, knowledge representation, and planning. The book also explains key concepts such as machine learning, natural language processing, pattern recognition, game playing, hybrid and fuzzy systems, and neural network-based learning. It is specifically designed to be beneficial for undergraduate and postgraduate students studying computer science, engineering, and information technology.

“Knowledge Representation and Reasoning (The Morgan Kaufmann Series in Artificial Intelligence)” Book Review: This book is specifically written for postgraduate students in the field of computer engineering, but it can also serve as a valuable reference for working professionals. It delves into the concepts of knowledge representation and artificial representation, providing a comprehensive understanding of building intelligent systems using a top-down approach. The book covers topics such as symbolic representation of knowledge, automated reasoning procedures, information retrieval, database management, and object-oriented systems. In order to enhance understanding, the book includes numerous theorem proofs and practical case studies, making the concepts more accessible and applicable.

“Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems (Studies in Fuzziness and Soft Computing)” Book Review: This book targets postgraduate students of computer engineering and can serve as a useful reference for working professionals. It focuses on the rough set approach to reasoning when dealing with insufficient and incomplete data. The book explores knowledge representation under different constraints, such as discernibility or similarity of objects. It covers essential topics including reducts, dependencies, and association rules. Theoretical notions, as well as heuristic and algorithmic tools for knowledge discovery, are reviewed. The book includes theorem proofs and practical case studies to aid in understanding the concepts effectively.

“Inheritance Hierarchies in Knowledge Representation and Programming Languages” Book Review: This is a comprehensive book written by Maurizio Lenzerini and Daniele Nardi. The book explores the concept of inheritance hierarchies in the fields of knowledge representation and programming languages. It delves into various topics, including inheritance mechanisms, object-oriented programming, semantic networks, and ontologies. The authors provide detailed explanations and examples to illustrate the principles and applications of inheritance hierarchies. This book is highly recommended for researchers, professionals, and students seeking a deeper understanding of knowledge representation and programming languages.