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Swarm Intelligent Systems by Nadia Nedjah,Luiza Macedo Mourelle Pdf
Systems designers have learned that many agents co-operating within the system can solve very complex problems with a minimal design effort. In general, multi-agent systems that use swarm intelligence are said to be swarm intelligent systems. Today, these are mostly used as search engines and optimization tools. This volume reviews innovative methodologies of swarm intelligence, outlines the foundations of engineering swarm intelligent systems and applications, and relates experiences using the particle swarm optimisation.
In the era globalisation the emerging technologies are governing engineering industries to a multifaceted state. The escalating complexity has demanded researchers to find the possible ways of easing the solution of the problems. This has motivated the researchers to grasp ideas from the nature and implant it in the engineering sciences. This way of thinking led to emergence of many biologically inspired algorithms that have proven to be efficient in handling the computationally complex problems with competence such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), etc. Motivated by the capability of the biologically inspired algorithms the present book on "Swarm Intelligence: Focus on Ant and Particle Swarm Optimization" aims to present recent developments and applications concerning optimization with swarm intelligence techniques. The papers selected for this book comprise a cross-section of topics that reflect a variety of perspectives and disciplinary backgrounds. In addition to the introduction of new concepts of swarm intelligence, this book also presented some selected representative case studies covering power plant maintenance scheduling; geotechnical engineering; design and machining tolerances; layout problems; manufacturing process plan; job-shop scheduling; structural design; environmental dispatching problems; wireless communication; water distribution systems; multi-plant supply chain; fault diagnosis of airplane engines; and process scheduling. I believe these 27 chapters presented in this book adequately reflect these topics.
Multi-Objective Swarm Intelligent Systems by Leandro dos Santos Coelho Pdf
This book covers the latest in multi-objective swarm intelligence and cooperative behavior. It contains innovative and intriguing applications as well as additions to the methodology and theory of genetic programming.
Swarm Intelligence by Eric Bonabeau,Marco Dorigo,Guy Theraulaz Pdf
Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks of interactions among individuals and between individuals and the environment. A fascinating subject, social insects are also a powerful metaphor for artificial intelligence, and the problems they solve--finding food, dividing labor among nestmates, building nests, responding to external challenges--have important counterparts in engineering and computer science. This book provides a detailed look at models of social insect behavior and how to apply these models in the design of complex systems. The book shows how these models replace an emphasis on control, preprogramming, and centralization with designs featuring autonomy, emergence, and distributed functioning. These designs are proving immensely flexible and robust, able to adapt quickly to changing environments and to continue functioning even when individual elements fail. In particular, these designs are an exciting approach to the tremendous growth of complexity in software and information. Swarm Intelligence draws on up-to-date research from biology, neuroscience, artificial intelligence, robotics, operations research, and computer graphics, and each chapter is organized around a particular biological example, which is then used to develop an algorithm, a multiagent system, or a group of robots. The book will be an invaluable resource for a broad range of disciplines.
Swarm Intelligence by Kuldeep Singh Kaswan,Jagjit Singh Dhatterwal,Avadhesh Kumar Pdf
SWARM INTELLIGENCE This important authored book presents valuable new insights by exploring the boundaries shared by cognitive science, social psychology, artificial life, artificial intelligence, and evolutionary computation by applying these insights to solving complex engineering problems. Motivated by the capability of the biologically inspired algorithms, “Swarm Intelligence: An Approach from Natural to Artificial” focuses on ant, cat, crow, elephant, grasshopper, water wave and whale optimization, swarm cyborg and particle swarm optimization, and presents recent developments and applications concerning optimization with swarm intelligence techniques. The goal of the book is to offer a wide spectrum of sample works developed in leading research throughout the world about innovative methodologies of swarm intelligence and foundations of engineering swarm intelligent systems; as well as applications and interesting experiences using particle swarm optimization, which is at the heart of computational intelligence. Discussed in the book are applications of various swarm intelligence models to operational planning of energy plants, modeling, and control of robots, organic computing, techniques of cloud services, bioinspired optimization, routing protocols for next-generation networks inspired by collective behaviors of insect societies and cybernetic organisms. Audience The book is directed to researchers, practicing engineers, and students in computational intelligence who are interested in enhancing their knowledge of techniques and swarm intelligence.
Swarm Intelligence by Eric Bonabeau,Marco Dorigo,Guy Theraulaz Pdf
This book provides a rigorous look at the mechanisms underlying collective behavior in social insects. The field is developing rapidly, and the book includes up-to-date research from biology, neuroscience, artificial intelligence, robotics, operations research, and computer graphics.
Swarm Intelligence by Christian Blum,Daniel Merkle Pdf
The book’s contributing authors are among the top researchers in swarm intelligence. The book is intended to provide an overview of the subject to novices, and to offer researchers an update on interesting recent developments. Introductory chapters deal with the biological foundations, optimization, swarm robotics, and applications in new-generation telecommunication networks, while the second part contains chapters on more specific topics of swarm intelligence research.
Intelligent Systems by Amit Sheth,Amit Sinhal,Abhinav Shrivastava,Amit Kumar Pandey Pdf
This book contains the latest computational intelligence methodologies and applications. This book is a collection of selected papers presented at International Conference on Sustainable Computing and Intelligent Systems (SCIS 2021), held in Jaipur, India, during February 5–6, 2021. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers selected papers in the area of artificial intelligence and intelligent systems, intelligent business systems, machine intelligence, computer vision, Web intelligence, big data analytics, swarm intelligence, and related topics.
Intelligent Systems by Crina Grosan,Ajith Abraham Pdf
Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. The current experimental systems have many of the characteristics of biological computers (brains in other words) and are beginning to be built to perform a variety of tasks that are difficult or impossible to do with conventional computers. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. This book comprising of 17 chapters offers a step-by-step introduction (in a chronological order) to the various modern computational intelligence tools used in practical problem solving. Staring with different search techniques including informed and uninformed search, heuristic search, minmax, alpha-beta pruning methods, evolutionary algorithms and swarm intelligent techniques; the authors illustrate the design of knowledge-based systems and advanced expert systems, which incorporate uncertainty and fuzziness. Machine learning algorithms including decision trees and artificial neural networks are presented and finally the fundamentals of hybrid intelligent systems are also depicted. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques, machine learning and data mining would find the comprehensive coverage of this book invaluable.
Foundations of Trusted Autonomy by Hussein A. Abbass,Jason Scholz,Darryn J. Reid Pdf
This book establishes the foundations needed to realize the ultimate goals for artificial intelligence, such as autonomy and trustworthiness. Aimed at scientists, researchers, technologists, practitioners, and students, it brings together contributions offering the basics, the challenges and the state-of-the-art on trusted autonomous systems in a single volume. The book is structured in three parts, with chapters written by eminent researchers and outstanding practitioners and users in the field. The first part covers foundational artificial intelligence technologies, while the second part covers philosophical, practical and technological perspectives on trust. Lastly, the third part presents advanced topics necessary to create future trusted autonomous systems. The book augments theory with real-world applications including cyber security, defence and space.
Swarm Intelligence for Resource Management in Internet of Things by Aboul Ella Hassanien,Ashraf Darwish Pdf
Internet of Things (IoT) is a new platform of various physical objects or “things equipped with sensors, electronics, smart devices, software, and network connections. IoT represents a new revolution of the Internet network which is driven by the recent advances of technologies such as sensor networks (wearable and implantable), mobile devices, networking, and cloud computing technologies. IoT permits these the smart devices to collect, store and analyze the collected data with limited storage and processing capacities. Swarm Intelligence for Resource Management in the Internet of Things presents a new approach in Artificial Intelligence that can be used for resources management in IoT, which is considered a critical issue for this network. The authors demonstrate these resource management applications using swarm intelligence techniques. Currently, IoT can be used in many important applications which include healthcare, smart cities, smart homes, smart hospitals, environment monitoring, and video surveillance. IoT devices cannot perform complex on-site data processing due to their limited battery and processing. However, the major processing unit of an application can be transmitted to other nodes, which are more powerful in terms of storage and processing. By applying swarm intelligence algorithms for IoT devices, we can provide major advantages for energy saving in IoT devices. Swarm Intelligence for Resource Management in the Internet of Things shows the reader how to overcome the problems and challenges of creating and implementing swarm intelligence algorithms for each application Examines the development and application of swarm intelligence systems in artificial intelligence as applied to the Internet of Things Discusses intelligent techniques for the implementation of swarm intelligence in IoT Prepared for researchers and specialists who are interested in the use and integration of IoT and cloud computing technologies
Swarm Intelligence by Aboul Ella Hassanien,Eid Emary Pdf
Swarm Intelligence: Principles, Advances, and Applications delivers in-depth coverage of bat, artificial fish swarm, firefly, cuckoo search, flower pollination, artificial bee colony, wolf search, and gray wolf optimization algorithms. The book begins with a brief introduction to mathematical optimization, addressing basic concepts related to swarm intelligence, such as randomness, random walks, and chaos theory. The text then: Describes the various swarm intelligence optimization methods, standardizing the variants, hybridizations, and algorithms whenever possible Discusses variants that focus more on binary, discrete, constrained, adaptive, and chaotic versions of the swarm optimizers Depicts real-world applications of the individual optimizers, emphasizing variable selection and fitness function design Details the similarities, differences, weaknesses, and strengths of each swarm optimization method Draws parallels between the operators and searching manners of the different algorithms Swarm Intelligence: Principles, Advances, and Applications presents a comprehensive treatment of modern swarm intelligence optimization methods, complete with illustrative examples and an extendable MATLAB® package for feature selection in wrapper mode applied on different data sets with benchmarking using different evaluation criteria. The book provides beginners with a solid foundation of swarm intelligence fundamentals, and offers experts valuable insight into new directions and hybridizations.
Swarm Intelligence for Cloud Computing by Indrajit Pan,Mohamed Abd Elaziz,Siddhartha Bhattacharyya Pdf
Swarm Intelligence in Cloud Computing is an invaluable treatise for researchers involved in delivering intelligent optimized solutions for reliable deployment, infrastructural stability, and security issues of cloud-based resources. Starting with a bird’s eye view on the prevalent state-of-the-art techniques, this book enriches the readers with the knowledge of evolving swarm intelligent optimized techniques for addressing different cloud computing issues including task scheduling, virtual machine allocation, load balancing and optimization, deadline handling, power-aware profiling, fault resilience, cost-effective design, and energy efficiency. The book offers comprehensive coverage of the most essential topics, including: Role of swarm intelligence on cloud computing services Cloud resource sharing strategies Cloud service provider selection Dynamic task and resource scheduling Data center resource management. Indrajit Pan is an Associate Professor in Information Technology of RCC Institute of Information Technology, India. He received his PhD from Indian Institute of Engineering Science and Technology, Shibpur, India. With an academic experience of 14 years, he has published around 40 research publications in different international journals, edited books, and conference proceedings. Mohamed Abd Elaziz is a Lecturer in the Mathematical Department of Zagazig University, Egypt. He received his PhD from the same university. He is the author of more than 100 articles. His research interests include machine learning, signal processing, image processing, cloud computing, and evolutionary algorithms. Siddhartha Bhattacharyya is a Professor in Computer Science and Engineering of Christ University, Bangalore. He received his PhD from Jadavpur University, India. He has published more than 230 research publications in international journals and conference proceedings in his 20 years of academic experience.
What Is Swarm Intelligence - Traders deciding on the next big market bet. - A navigation app quickly mapping out a less-explored area. - Fashion brands choosing the hottest color of the season. - An airport managing fight delays. What do these scenarios have in common? In each one, swarm intelligence blends global and local insight to improve how businesses make decisions. Swarm intelligence is a form of artificial intelligence (AI) inspired by the insect kingdom. In nature, it describes how honeybees migrate, how ants form perfect trails, and how birds flock. In the world of AI, swarm systems draw input from individual people or machine sensors and then use algorithms to optimize the overall performance of the group or system in real time. Consider Waze, the popular road navigation app that uses swarm intelligence to create and modify maps. Starting with limited digital maps, it began making tweaks based on its users’ GPS data along with manual map modifications by registered users. Entire cities have been mapped using this method, as was the case in Costa Rica’s capital, San José. And just as ants signal danger to their counterparts, so too do Waze users contribute live information from accident locations and traffic jams. Swarm intelligence is now being used to predict everything from the outcome of the Super Bowl to fashion trends to major political events. Using swarm intelligence, investors can better predict market movements, and retailers can more accurately forecast sales. How You Will Benefit By the end of reading this book, you will have the answers to the public top 100 questions, queries, issues, doubts, problems and inquiries. Most importantly, you will be able master the discussion about the following topics in Swarm Intelligence, and explore the new ways of thinking about life and business: 01 - Fundamental Concepts: Definition, Systems, Nature 02 - Models of Swarm Behavior: Boids, Self-Propelled Particles 03 - Optimization Problem: Elements, Formulations, and Search Solutions 04 - Meta-Heuristic Nature Inspired Optimization Algorithms Inspired by Swarm Intelligence 05 - Meta-Heuristic and Monkeys Problems: Infinite, Finite, and the difference 06 - Common Algorithmic Characteristics and Comparisons: Ant Colony Optimization, Bee Colony Optimization, Bat Algorithm, Cuckoo Search, Particle Swarm Optimization, Firefly Algorithm, Flower Pollination Algorithm, Swarm Intelligence Application Areas, Travelling Salesman Problem, Telecommunication, Image Processing, Engineering Design, Vehicle Routing 07 - Swarm Intelligence Systems: Taxonomy, Natural vs. Artificial, Scientific vs. Engineering 08 - Examples of Swarm Intelligence Systems: Foraging Behavior of Ants, Clustering by a Swarm of Robots, Exploitation of Collective Behaviors of Animal Societies, Swarm-based Data Analysis 09 - Properties of Swarm Intelligence Systems: Individual, Homogeneous, Interaction, Self-Organized 10 - Studies and Applications of Swarm Intelligence Systems: Clustering Behavior of Ants, Nest Building Behavior of Wasp and Termites, Flocking and Schooling in Birds and Fish, Any Colony Optimization, Particle Swarm Optimization, Swarm-based Network Management, Cooperative Behavior in Swarm of Robots. 11- Swarm Intelligence as a Whole New Way of Thinking About Business: Perspective and Advantages 12 - Swarm Intelligence Foraging for Solutions in Telecommunication, Information Technology, Logistics, Manufacturing. 13 - Advantages of Swarm Intelligence for Organizations: Simple Rules Rule, Raiding New Markets, A swarm of Possibilities.
Applications of Advanced Computing in Systems by Rajesh Kumar,R. K. Dohare,Harishchandra Dubey,V. P. Singh Pdf
This book covers advances in system, control and computing. This book gathers selected high-quality research papers presented at the International Conference on Advances in Systems, Control and Computing (AISCC 2020), held at MNIT Jaipur during February 27–28, 2020. The first part is advances in systems and it is dedicated to applications of the artificial neural networks, evolutionary computation, swarm intelligence, artificial immune systems, fuzzy system, autonomous and multi-agent systems, machine learning, other intelligent systems and related areas. In the second part, machine learning and other intelligent algorithms for design of control/control analysis are covered. The last part covers advancements, modifications, improvements and applications of intelligent algorithms.