- Table View
- List View
AI and Emerging Technologies: Automated Decision-Making, Digital Forensics, and Ethical Considerations
by Archana Patel Purvi Pokhariyal Shubham PandeyIn the past decade, Artificial Intelligence (AI) has made significant advancements in various sectors of society, such as education, health, e-commerce, media and entertainment, banking and finance, transportation, and defense, among others. Its application has permeated every sector, leaving no area untouched. However, the utilization of AI brings forth crucial legal, ethical, and technical concerns and obstacles that must be appropriately addressed through thoughtful deliberation, discussions, and the implementation of effective regulations.AI and Emerging Technologies: Automated Decision-Making, Digital Forensics, and Ethical Considerations provides a comprehensive and insightful roadmap for exploring the advancements, challenges, solutions, and implications of AI in three key areas: the legal field, gaming applications, digital forensic, and decision-making. By delving into these topics, this book offers a deep understanding of how AI can be optimally utilized to deliver maximum benefits to users, all within a single, comprehensive source. One of the focuses of this book is to shed light on the preictal application of emerging technologies in automated decision-making while also addressing the ethical considerations that arise from their use. By examining the integration of these technologies into digital forensics and their impact on other domains, such as gaming applications deep fake, this book presents valuable insights into the broader implications of AI.The book serves as an invaluable resource for anyone seeking to understand and navigate the complex world of AI. By offering a comprehensive exploration of its applications, ethical considerations, and data protection techniques, it provides researchers and scholars, graduate students, software engineers along with data scientists the necessary insights to harness the full potential of AI while ensuring its responsible and ethical use.
AI and Gamification Technologies for Complex Work
by James C. FerraroThe medium through which training in the workplace is delivered has been changing in recent years to offer a more personalized and immersive experience. The invention of virtual reality (VR) and augmented reality (AR) platforms has created opportunities to take a more hands-on approach to familiarizing oneself with a task or environment with mitigated time and monetary commitments. Written assessments are being swiftly replaced with more interactive and scientifically validated training simulations and this essential technology is in high demand in the government and private sectors. This book highlights many of the ways simulation-based training can be leveraged to create personalized training curricula for those in high-risk careers and how it can be assessed successfully. AI and Gamification Technologies for Complex Work uncovers the use of artificial intelligence (AI) and machine learning (ML) for the purposes of creating adaptive, personalized training for individuals who work in complex jobs. It covers adaptive simulation-based training, fighting skill decay through game-based training, and additional uses of AI/ML and other tools in measuring human performance. Insights from professionals and experts in the fields of simulation and training provide readers with information about current applications of AI/ML in creating adaptive or personalized training, as well as investigations into the future of simulation and game-based training, as virtual and augmented realities proliferate modern training programs. The book looks at how data science, AI, and ML contribute to adaptive training systems and the reader is encouraged to look further into the engines that drive adaptive training while devising their own systems for training in complex jobs. This book is ideal for professionals in human factors engineering and psychology, artificial intelligence, military training and simulation, game development, data science, modeling and simulation and industrial and organizational psychology.
AI and Human Thought and Emotion
by Sam FreedThe field of artificial intelligence (AI) has grown dramatically in recent decades from niche expert systems to the current myriad of deep machine learning applications that include personal assistants, natural-language interfaces, and medical, financial, and traffic management systems. This boom in AI engineering masks the fact that all current AI systems are based on two fundamental ideas: mathematics (logic and statistics, from the 19th century), and a grossly simplified understanding of biology (mainly neurons, as understood in 1943). This book explores other fundamental ideas that have the potential to make AI more anthropomorphic. Most books on AI are technical and do not consider the humanities. Most books in the humanities treat technology in a similar manner. AI and Human Thought and Emotion, however is about AI, how academics, researchers, scientists, and practitioners came to think about AI the way they do, and how they can think about it afresh with a humanities-based perspective. The book walks a middle line to share insights between the humanities and technology. It starts with philosophy and the history of ideas and goes all the way to usable algorithms. Central to this work are the concepts of introspection, which is how consciousness is viewed, and consciousness, which is accessible to humans as they reflect on their own experience. The main argument of this book is that AI based on introspection and emotion can produce more human-like AI. To discover the connections among emotion, introspection, and AI, the book travels far from technology into the humanities and then returns with concrete examples of new algorithms. At times philosophical, historical, and technical, this exploration of human emotion and thinking poses questions and provides answers about the future of AI.
AI and Humanity (The\mit Press Ser.)
by Illah Reza Nourbakhsh Jennifer KeatingAn examination of the implications for society of rapidly advancing artificial intelligence systems, combining a humanities perspective with technical analysis; includes exercises and discussion questions.AI and Humanity provides an analytical framing and a common language for understanding the effects of technological advances in artificial intelligence on society. Coauthored by a computer scientist and a scholar of literature and cultural studies, it is unique in combining a humanities perspective with technical analysis, using the tools of literary explication to examine the societal impact of AI systems. It explores the historical development of these technologies, moving from the apparently benign Roomba to the considerably more sinister semi-autonomous weapon system Harpy. The book is driven by an exploration of the cultural and etymological roots of a series of keywords relevant to both AI and society. Works examined range from Narrative of the Life of Frederick Douglass, given a close reading for its themes of literacy and agency, to Simon Head's critique of the effects of surveillance and automation on the Amazon labor force in Mindless.Originally developed as a textbook for an interdisciplinary humanities-science course at Carnegie Mellon, AI & Humanity offers discussion questions, exercises (including journal writing and concept mapping), and reading lists. A companion website provides updated resources and a portal to a video archive of interviews with AI scientists, sociologists, literary theorists, and others.
AI and IOT in Renewable Energy (Studies in Infrastructure and Control)
by Saad Mekhilef Ankush Ghosh Rabindra Nath Shaw Nishad MendisThis book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.
AI and IoT Technology and Applications for Smart Healthcare Systems (Advances in Computational Collective Intelligence)
by Alex KhangIn recent years, the application of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in smart healthcare has been increasing. We are approaching a world where connected smart devices tell people when they need to visit a doctor because these devices will be able to detect health problems and discover symptoms of illness that may need medical care. AI-collaborative IoT technologies can help medical professionals with decision-making. These technologies can also help develop a sustainable and smart healthcare system.AI and IoT Technology and Applications for Smart Healthcare Systems helps readers understand complex scientific topics in a simple and accessible way. It introduces the world of AI-collaborative IoT physics, explaining how this technology behaves at the smallest level and how this can revolutionize healthcare. The book shows how IoT technology and AI can work together to make computers more powerful and capable of solving complex problems in the healthcare sector. Exploring the effect of AI-collaborative technology on IoT technologies, the book discusses how IoT can benefit from AI algorithms to enable machines to learn, make decisions, and process information more efficiently. Because smart machines create more perceptive devices and systems, the application of this technology raises important ethical questions about privacy, security, and the responsible development of healthcare IoT technology, which this book covers. The book also provides insight into the potential applications of these technologies not only in the healthcare industry but also in related fields, such as smart transportation, smart manufacturing, and smart cities.
AI and IoT for Smart City Applications (Studies in Computational Intelligence #1002)
by Vincenzo Piuri Rabiul Islam Ankush Ghosh Rabindra Nath ShawThis book provides a valuable combination of relevant research works on developing smart city ecosystem from the artificial intelligence (AI) and Internet of things (IoT) perspective. The technical research works presented here are focused on a number of aspects of smart cities: smart mobility, smart living, smart environment, smart citizens, smart government, and smart waste management systems as well as related technologies and concepts. This edited book offers critical insight to the key underlying research themes within smart cities, highlighting the limitations of current developments and potential future directions.
AI and IoT for Sustainable Development in Emerging Countries: Challenges and Opportunities (Lecture Notes on Data Engineering and Communications Technologies #105)
by Mariya Ouaissa Zakaria Boulouard Mariyam Ouaissa Sarah El HimerThis book comprises a number of state-of-the-art contributions from both scientists and practitioners working in a large pool of fields where AI and IoT can open up new horizons. Artificial intelligence and Internet of Things have introduced themselves today as must-have technologies in almost every sector. Ranging from agriculture to industry and health care, the scope of applications of AI and IoT is as wide as the horizon. Nowadays, these technologies are extensively used in developed countries, but they are still at an early stage in emerging countries. AI and IoT for Sustainable Development in Emerging Countries—Challenges and Opportunities is an invaluable source to dive into the latest applications of AI and IoT and how they have been used by researchers from emerging countries to solve sustainable development-related issues by taking into consideration the specifities of their countries. This book starts by presenting how AI and IoT can tackle the challenges of sustainable development in general and then focuses on the following axes: · AI and IoT for smart environment and energy · Industry 4.0 and intelligent transportation · A vision towards an artificial intelligence of medical things · AI, social media, and big data analytics. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in these particular areas or those interested in grasping its diverse facets and exploring the latest advances on their respective fields and the role of AI and IoT in them.
AI and IoT-Based Intelligent Automation in Robotics
by Abhishek Kumar Ashutosh Kumar Dubey N. Gayathri S. Rakesh Kumar Prasenjit DasThe 24 chapters in this book provides a deep overview of robotics and the application of AI and IoT in robotics. It contains the exploration of AI and IoT based intelligent automation in robotics. The various algorithms and frameworks for robotics based on AI and IoT are presented, analyzed, and discussed. This book also provides insights on application of robotics in education, healthcare, defense and many other fields which utilize IoT and AI. It also introduces the idea of smart cities using robotics.
AI and IoT: Volume 1 (Studies in Systems, Decision and Control #601)
by Bahaa AwwadThis book explores the integration of AI technologies with emerging trends such as IoT, blockchain, and cloud computing. In this book readers will embark on a transformative journey that explores the powerful convergence of Artificial Intelligence (AI), Internet of Things (IoT), and business management. With the advent of these cutting-edge technologies, businesses have unprecedented opportunities to revolutionize their operations, drive innovation, and achieve remarkable success in today's digital landscape.
AI and Law: How Automation is Changing the Law (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Aurelia Tamo-Larrieux Clement Guitton Simon MayerThis book provides insights into how AI is changing legal practice, government processes, and individuals’ access to those processes, encouraging each of us to consider how technological advances are changing the legal system. Particularly, and distinct from current debates on how to regulate AI, this books focuses on how the progressive merger between computational methods and legal rules changes the very structure and application of the law itself.We investigate how automation is changing the legal analysis, legal rulemaking, legal rule extraction, and application of legal rules and how this impacts individuals, policymakers, civil servants, and society at large. We show through many examples that a debate on how automation is changing the law is needed, which must revolve around the democratic legitimacy of the automation of legal processes, and be informed by the technical feasibility and tradeoffs of specific endeavors.
AI and ML Techniques in Image Processing and Object Detection
by Lalit Kumar Awasthi Maheep Singh Raj Singh Sandeep Chand KumainThis book highlights the evolution and interdisciplinary approach of AI and ML in image processing, tracing historical development and exploring their convergence with different fields. It delves into optimizing neural architectures and making deep learning models interpretable while exploring recent trends like versatile CNN applications and edge computing deployment. The intersection of AI and creativity, dynamic transfer learning, and domain adaptation are discussed alongside object detection techniques and reinforcement learning. It examines advanced applications in satellite imagery, healthcare, and smart cities, addressing ethical considerations like bias mitigation and transparency. This book also outlines future trends such as quantum-inspired computing and the evolution of edge AI ecosystems.
AI and ML for Coders in PyTorch
by Laurence MoroneyEager to learn AI and machine learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for programmers, it focuses on practical applications using PyTorch, helping you build real-world models without feeling overwhelmed.From computer vision and natural language processing (NLP) to generative AI with Hugging Face Transformers, this book equips you with the skills most in demand for AI development today. You'll also learn how to deploy your models across the web and cloud confidently.Gain the confidence to apply AI without needing advanced math or theory expertiseDiscover how to build AI models for computer vision, NLP, and sequence modeling with PyTorchLearn generative AI techniques with Hugging Face Diffusers and Transformers
AI and Machine Learning (SAGE Essentials)
by Was RahmanWas Rahman′s AI and Machine Learning achieves that rare balance of making a difficult and complex topic accessible to non-specialists, without dumbing down. He starts with an enlightening and entertaining explanation of what artificial intelligence (AI) is and how it works. This includes often-overlooked fundamentals like what we actually mean by ′intelligence′, artificial or otherwise. Rahman brings his explanations to life with lucid and, at times, surprising examples of AI already in use around us. He takes these back to first principles, deftly avoiding any need to understand the maths or computing involved. This allows him to demystify what the technology is really doing and show us that much of it is reassuringly mundane, despite the hype. This distinctive approach comes into its own when examining the challenges and risks of AI. It allows the author to remove the drama and fear of sensationalized headlines and doom-laden movie plots. In their place, he offers an insightful analysis of how the major issues surface, what options we have for addressing them and why some dilemmas may prove intractable. A must-read to understand the reality and implications of AI beyond the hype!
AI and Machine Learning Paradigms for Health Monitoring System: Intelligent Data Analytics (Studies in Big Data #86)
by Jafar A. Alzubi Hasmat Malik Nuzhat FatemaThis book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health, engineering and/or applied sciences such as the clinical services, medical image analysis, management support, quality analysis, bioinformatics, device analysis and operations. The book presents knowledge of experts in the form of chapters with the objective to introduce the theme of intelligent data analytics and discusses associated theoretical applications. At last, it presents simulation codes for the problems included in the book for better understanding for beginners.
AI and Machine Learning for Coders: A Programmer's Guide To Artificial Intelligence
by Laurence MoroneyIf you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code.You'll learn:How to build models with TensorFlow using skills that employers desireThe basics of machine learning by working with code samplesHow to implement computer vision, including feature detection in imagesHow to use NLP to tokenize and sequence words and sentencesMethods for embedding models in Android and iOSHow to serve models over the web and in the cloud with TensorFlow Serving
AI and Machine Learning for Network and Security Management (IEEE Press Series on Networks and Service Management)
by Yulei Wu Tong Li Jingguo GeAI AND MACHINE LEARNING FOR NETWORK AND SECURITY MANAGEMENT Extensive Resource for Understanding Key Tasks of Network and Security Management AI and Machine Learning for Network and Security Management covers a range of key topics of network automation for network and security management, including resource allocation and scheduling, network planning and routing, encrypted traffic classification, anomaly detection, and security operations. In addition, the authors introduce their large-scale intelligent network management and operation system and elaborate on how the aforementioned areas can be integrated into this system, plus how the network service can benefit. Sample ideas covered in this thought-provoking work include: How cognitive means, e.g., knowledge transfer, can help with network and security management How different advanced AI and machine learning techniques can be useful and helpful to facilitate network automation How the introduced techniques can be applied to many other related network and security management tasks Network engineers, content service providers, and cybersecurity service providers can use AI and Machine Learning for Network and Security Management to make better and more informed decisions in their areas of specialization. Students in a variety of related study programs will also derive value from the work by gaining a base understanding of historical foundational knowledge and seeing the key recent developments that have been made in the field.
AI and Machine Learning for On-Device Development: A Programmer's Guide
by Laurence MoroneyAI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating and running models on popular mobile platforms such as iOS and Android.Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today.Explore the options for implementing ML and AI on mobile devicesCreate ML models for iOS and AndroidWrite ML Kit and TensorFlow Lite apps for iOS and Android, and Core ML/Create ML apps for iOSChoose the best techniques and tools for your use case, such as cloud-based versus on-device inference and high-level versus low-level APIsLearn privacy and ethics best practices for ML on devices
AI and Metaverse: Volume 2 (Studies in Computational Intelligence #1160)
by Roger Lee Jongbae Kim Gwangyoung GimThe book reports the state-of-the-art results in Artificial Intelligence and Metaverse in both printed and electronic form. Studies in Computation Intelligence (SCI) has grown into the most comprehensive computational intelligence research forum available in the world. This book publishes original papers on both theory and practice that address foundations, state-of-the-art problems and solutions, and crucial challenges.
AI and Microservices: Integrating AI into API Design and Distributed Microservice Architecture
by Dileep Kumar Pandiya Nilesh CharankarThis book explores how artificial intelligence (AI) is transforming the design and operation of microservices and API architecture. It provides a clear and practical guide to using AI to automate tasks, enhance performance, and improve the scalability of microservice-based systems. Starting with the basics, you will learn about the core concepts of microservices and API design, gradually building an understanding of how AI can be seamlessly integrated. Through real-world examples, visual diagrams, and mock APIs, the book shows you how to bring theory into practice, making complex systems easier to manage and more efficient. You will also discover strategies for testing and scaling systems, securing APIs, and addressing ethical challenges in AI-powered environments. Case studies highlight successful implementations, offering valuable insights you can apply to your own projects. Whether you're a developer, architect, or tech enthusiast, this book gives you the tools and inspiration to build smarter, more resilient systems while staying ahead of future trends in AI and distributed computing. What You'll Learn: Understand the basics of microservices and API design and see how AI can make these systems smarter and more efficient. Discover how to use AI in microservices and APIs to automate tasks, improve performance, and boost security. Learn how to design scalable and secure systems by following best practices and innovative approaches. Get practical tips on troubleshooting and solving challenges in AI-powered microservice architectures. Who is this book for: Software architects and engineers, AI and machine learning professionals, and DevOps engineers
AI and Multimodal Services – AIMS 2024: 13th International Conference, Held as Part of the Services Conference Federation, SCF 2024, Bangkok, Thailand, November 16–19, 2024, Proceedings (Lecture Notes in Computer Science #15421)
by Mengxing Huang Liang-Jie Zhang Xiuqin Pan Jiajia Zhang Junyang ChenThis book constitutes the refereed proceedings of the 13th International Conference on AI and Multimodal Services – AIMS 2024, AIMS 2024, Held as Part of the Services Conference Federation, SCF 2024, held in Bangkok, Thailand, during November 16-19, 2024. The 7 full papers and one short paper included in this book were carefully reviewed and selected from 16 submissions. They were organized in topical sections as follows: research track; application track; and short paper track.
AI and Neuro-Degenerative Diseases: Insights and Solutions (Studies in Computational Intelligence #1131)
by Ajith Abraham Loveleen Gaur Reuel AjithThis book explores the current state of healthcare practice and provides a roadmap for harnessing artificial intelligence (AI) and other modern cognitive technologies for neurogenerative diseases. The main goal of this book is to look at how these techniques can be used to classify patients with neurodegenerative diseases by extracting data from multiple modalities. It demonstrates that the growing development of computer-aided diagnosis systems has a lot of potential to help with the diagnostic process. It offers an analysis of the prospective and perils in implementing such state of the art.Progressive brain disorders with a high prevalence in the general population include Parkinson's disease, Alzheimer's disease and other types of dementia, Huntington's disease, and motor neuron disease. Worldwide, it is estimated that 33 million people have Alzheimer's disease, and 10 million people have Parkinson's disease. The global health economy is significantly impacted by these disorders, which affect both the patient and the caregivers. Various diagnostic techniques are used for differential diagnoses, such as brain imaging, EEG analysis, molecular analysis, and cognitive, psychological, and physical examination. The book aims to develop effective treatments, enhance patient quality of life, and extend life expectancy. It focuses on novel artificial intelligence approaches to clarify the pathogenesis of neurodegenerative disorders and provide early diagnosis.The authors compile recent developments based on machine learning and deep learning techniques to diagnose neurodegenerative diseases using imaging, genetic, and clinical data. The authors support initiatives and methods that aim to improve the application of algorithms in diagnostic practice.
AI and Robotic Technology in Materials and Chemistry Research
by Xi ZhuA singular resource for researchers seeking to apply artificial intelligence and robotics to materials science In AI and Robotic Technology in Materials and Chemistry Research, distinguished researcher Dr. Xi Zhu delivers an incisive and practical guide to the use of artificial intelligence and robotics in materials science and chemistry. Dr. Zhu explains the principles of AI from the perspective of a scientific researcher, including the challenges of applying the technology to chemical and biomaterials design. He offers concise interviews and surveys of highly regarded industry professionals and highlights the interdisciplinary and broad applicability of widely available AI tools like ChatGPT. The book covers computational methods and approaches from algorithms, models, and experimental data systems, and includes case studies that showcase the real-world applications of artificial intelligence and lab automation in a variety of scientific research settings from around the world. You'll also find: A thorough introduction to the challenges currently being faced by chemists and materials science researchers Comprehensive explorations of autonomous laboratories powered by artificial intelligence and robotics Practical discussions of a blockchain-powered anti-counterfeiting experimental data system in an autonomous laboratory In-depth treatments of large language models as applied to autonomous materials research Perfect for materials scientists, analytical chemists, and robotics engineers, AI and Robotic Technology in Materials and Chemistry Research will also benefit analytical and pharmaceutical chemists, computer analysts, and other professionals and researchers with an interest in artificial intelligence and robotics.
AI and Robotics in Disaster Studies (Disaster Research and Management Series on the Global South)
by T. V. Vijay Kumar Keshav SudThis book promotes a meaningful and appropriate dialogue and cross-disciplinary partnerships on Artificial Intelligence (AI) in governance and disaster management. The frequency and the cost of losses and damages due to disasters are rising every year. From wildfires to tsunamis, drought to hurricanes, floods to landslides combined with chemical, nuclear and biological disasters of epidemic proportions has increased human vulnerability and ecosystem sustainability. Life is not as it used to be and governance to manage disasters cannot be a business as usual. The quantum and proportion of responsibilities with the emergency services has increased many times to strain them beyond their human capacities. Its time that the struggling disaster management services get supported and facilitated by new technology of combining Artificial Intelligence (AI) and Machine Learning (ML) with Data Analytics Technologies (DAT)to serve people and government in disaster management. AI and ML have advanced to a state where they could be utilized for many operations in disaster risk reduction. Even though many disasters cannot be prevented and a number of them are blind natural disasters yet through an appropriate application of AI and ML quick predictions, vulnerability identification and classification of relief and rescue operations could be achieved.
AI and SWARM: Evolutionary Approach to Emergent Intelligence
by Hitoshi IbaThis book provides theoretical and practical knowledge on AI and swarm intelligence. It provides a methodology for EA (evolutionary algorithm)-based approach for complex adaptive systems with the integration of several meta-heuristics, e.g., ACO (Ant Colony Optimization), ABC (Artificial Bee Colony), and PSO (Particle Swarm Optimization), etc. These developments contribute towards better problem-solving methodologies in AI. The book also covers emerging uses of swarm intelligence in applications such as complex adaptive systems, reaction-diffusion computing, and diffusion-limited aggregation, etc. Another emphasis is its real-world applications. We give empirical examples from real-world problems and show that the proposed approaches are successful when addressing tasks from such areas as swarm robotics, silicon traffics, image understanding, Vornoi diagrams, queuing theory, and slime intelligence, etc. Each chapter begins with the background of the problem followed by the current state-of-the-art techniques of the field, and ends with a detailed discussion. In addition, the simulators, based on optimizers such as PSO and ABC complex adaptive system simulation, are described in detail. These simulators, as well as some source codes, are available online on the author’s website for the benefit of readers interested in getting some hands-on experience of the subject. The concepts presented in this book aim to promote and facilitate the effective research in swarm intelligence approaches in both theory and practice. This book would also be of value to other readers because it covers interdisciplinary research topics that encompass problem-solving tasks in AI, complex adaptive systems, and meta-heuristics.