Swarm Intelligence

Swarm Intelligence

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.

Author: Christian Blum

Publisher: Springer Science & Business Media

ISBN: 9783540740896

Category: Computers

Page: 286

View: 322

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.
Categories: Computers

Innovations in Swarm Intelligence

Innovations in Swarm Intelligence

In this chapter, advances in techniques and applications of swarm intelligence are presented. ... The dynamics of each swarm intelligence model and the associated characteristics in solving optimization as well as other problems are ...

Author: Chee Peng Lim

Publisher: Springer Science & Business Media

ISBN: 9783642042249

Category: Mathematics

Page: 255

View: 757

Over the past two decades, swarm intelligence has emerged as a powerful approach to solving optimization as well as other complex problems. Swarm intelligence models are inspired by social behaviours of simple agents interacting among themselves as well as with the environment, e.g., flocking of birds, schooling of fish, foraging of bees and ants. The collective behaviours that emerge out of the interactions at the colony level are useful in achieving complex goals. The main aim of this research book is to present a sample of recent innovations and advances in techniques and applications of swarm intelligence. Among the topics covered in this book include: particle swarm optimization and hybrid methods, ant colony optimization and hybrid methods, bee colony optimization, glowworm swarm optimization, and complex social swarms, application of various swarm intelligence models to operational planning of energy plants, modeling and control of nanorobots, classification of documents, identification of disease biomarkers, and prediction of gene signals. The book is directed to researchers, practicing professionals, and undergraduate as well as graduate students of all disciplines who are interested in enhancing their knowledge in techniques and applications of swarm intelligence.
Categories: Mathematics

Swarm Intelligence

Swarm Intelligence

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 ...

Author: Eric Bonabeau

Publisher: Oxford University Press

ISBN: 0195131592

Category: Computers

Page: 307

View: 972

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.
Categories: Computers

Swarm Intelligence

Swarm Intelligence

It is, however, fair to say that very few applications of swarm intelligence have been developed. One of the main reasons for this relative lack of success resides in the fact that swarm-intelligent systems are hard to "program," ...

Author: Eric Bonabeau

Publisher: Oxford University Press

ISBN: 0198030150

Category: Computers

Page: 320

View: 918

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.
Categories: Computers

Critical Developments and Applications of Swarm Intelligence

Critical Developments and Applications of Swarm Intelligence

algorithm, fish school search optimization algorithm, particle swarm optimization algorithm, to name just a few. These swarm intelligence algorithms were developed from different inspiration sources, and in general have different ...

Author: Shi, Yuhui

Publisher: IGI Global

ISBN: 9781522551355

Category: Computers

Page: 478

View: 154

Artificial intelligence is a constantly advancing field that requires models in order to accurately create functional systems. The use of natural acumen to create artificial intelligence creates a field of research in which the natural and the artificial meet in a new and innovative way. Critical Developments and Applications of Swarm Intelligence is a critical academic publication that examines developing research, technologies, and function regarding natural and artificial acumen specifically, in regards to self-organized systems. Featuring coverage on a broad range of topics such as evolutionary algorithms, optimization techniques, and computational comparison, this book is geared toward academicians, students, researchers, and engineers seeking relevant and current research on the progressive research based on the implementation of swarm intelligence in self-organized systems.
Categories: Computers

Advances in Swarm Intelligence

Advances in Swarm Intelligence

The 104 full papers presented in this volume were carefully reviewed and selected from 177 submissions.

Author: Ying Tan

Publisher: Springer Nature

ISBN: 9783030787431

Category: Swarm intelligence

Page: 589

View: 362

This two-volume set LNCS 12689-12690 constitutes the refereed proceedings of the 12th International Conference on Advances in Swarm Intelligence, ICSI 2021, held in Qingdao, China, in July 2021. The 104 full papers presented in this volume were carefully reviewed and selected from 177 submissions. They cover topics such as: Swarm Intelligence and Nature-Inspired Computing; Swarm-based Computing Algorithms for Optimization; Particle Swarm Optimization; Ant Colony Optimization; Differential Evolution; Genetic Algorithm and Evolutionary Computation; Fireworks Algorithms; Brain Storm Optimization Algorithm; Bacterial Foraging Optimization Algorithm; DNA Computing Methods; Multi-Objective Optimization; Swarm Robotics and Multi-Agent System; UAV Cooperation and Control; Machine Learning; Data Mining; and Other Applications.
Categories: Swarm intelligence

Swarm Intelligence in Data Mining

Swarm Intelligence in Data Mining

This book deals with the application of swarm intelligence in data mining. Addressing the various issues of swarm intelligence and data mining using different intelligent approaches is the novelty of this edited volume.

Author: Ajith Abraham

Publisher: Springer

ISBN: 9783540349563

Category: Computers

Page: 268

View: 392

This volume examines the application of swarm intelligence in data mining, addressing the issues of swarm intelligence and data mining using novel intelligent approaches. The book comprises 11 chapters including an introduction reviewing fundamental definitions and important research challenges. Important features include a detailed overview of swarm intelligence and data mining paradigms, focused coverage of timely, advanced data mining topics, state-of-the-art theoretical research and application developments and contributions by pioneers in the field.
Categories: Computers

Swarm Intelligence

Swarm Intelligence

Recently, in computer science there are developed different multi-agent systems which are inspired by intelligent ... Swarm intelligence can provide the Internet of Things with a new technology of modeling some social functions of these ...

Author: Andrew Schumann

Publisher: CRC Press

ISBN: 9780429650246

Category: Computers

Page: 184

View: 611

The notion of swarm intelligence was introduced for describing decentralized and self-organized behaviors of groups of animals. Then this idea was extrapolated to design groups of robots which interact locally to cumulate a collective reaction. Some natural examples of swarms are as follows: ant colonies, bee colonies, fish schooling, bird flocking, horse herding, bacterial colonies, multinucleated giant amoebae Physarum polycephalum, etc. In all these examples, individual agents behave locally with an emergence of their common effect. An intelligent behavior of swarm individuals is explained by the following biological reactions to attractants and repellents. Attractants are biologically active things, such as food pieces or sex pheromones, which attract individuals of swarm. Repellents are biologically active things, such as predators, which repel individuals of swarm. As a consequence, attractants and repellents stimulate the directed movement of swarms towards and away from the stimulus, respectively. It is worth noting that a group of people, such as pedestrians, follow some swarm patterns of flocking or schooling. For instance, humans prefer to avoid a person considered by them as a possible predator and if a substantial part of the group in the situation of escape panic (not less than 5%) changes the direction, then the rest follows the new direction, too. Some swarm patterns are observed among human beings under the conditions of their addictive behavior such as the behavior of alcoholics or gamers. The methodological framework of studying swarm intelligence is represented by unconventional computing, robotics, and cognitive science. In this book we aim to analyze new methodologies involved in studying swarm intelligence. We are going to bring together computer scientists and cognitive scientists dealing with swarm patterns from social bacteria to human beings. This book considers different models of simulating, controlling, and predicting the swarm behavior of different species from social bacteria to humans.
Categories: Computers

Swarm Intelligence Algorithms

Swarm Intelligence Algorithms

Apart from these, in the literature, there are a large number of other modifications of different kinds that combine GSO with other swarm intelligence algorithms and obtain superior results. These results are indicative of the ...

Author: Adam Slowik

Publisher: CRC Press

ISBN: 9780429749476

Category: Computers

Page: 349

View: 136

Nature-based algorithms play an important role among artificial intelligence algorithms. Among them are global optimization algorithms called swarm intelligence algorithms. These algorithms that use the behavior of simple agents and various ways of cooperation between them, are used to solve specific problems that are defined by the so-called objective function. Swarm intelligence algorithms are inspired by the social behavior of various animal species, e.g. ant colonies, bird flocks, bee swarms, schools of fish, etc. The family of these algorithms is very large and additionally includes various types of modifications to enable swarm intelligence algorithms to solve problems dealing with areas other than those for which they were originally developed. This book presents 24 swarm algorithms together with their modifications and practical applications. Each chapter is devoted to one algorithm. It contains a short description along with a pseudo-code showing the various stages of its operation. In addition, each chapter contains a description of selected modifications of the algorithm and shows how it can be used to solve a selected practical problem. This book should also be useful for undergraduate and postgraduate students studying nature-based optimization algorithms, and can be a helpful tool for learning these algorithms, along with their modifications and practical applications. In addition, it can be a useful source of knowledge for scientists working in the field of artificial intelligence, as well as for engineers interested in using this type of algorithms in their work. If the reader wishes to expand his knowledge beyond the basics of swarm intelligence algorithms presented in this book and is interested in more detailed information, we recommend the book "Swarm Intelligence Algorithms: A Tutorial" (Edited by A. Slowik, CRC Press, 2020). It contains a detailed explanation of how each algorithm works, along with relevant program codes in Matlab and the C ++ programming language, as well as numerical examples illustrating step-by-step how individual algorithms work.
Categories: Computers

Evolutionary and Swarm Intelligence Algorithms

Evolutionary and Swarm Intelligence Algorithms

The term Swarm Intelligence was coined by Beni and Wang in connection with cellular robotic systems [3]. They developed a set of algorithms for controlling robotic swarms. However, there is at least one earlier work (there may be more) ...

Author: Jagdish Chand Bansal

Publisher: Springer

ISBN: 9783319913414

Category: Computers

Page: 190

View: 841

This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.
Categories: Computers

Swarm Intelligence and Bio Inspired Computation

Swarm Intelligence and Bio Inspired Computation

with social living habits often exhibit similar swarm intelligent behavior. Therefore, the refined artificial system model mainly reflects the behavior characteristics of ant colony (Bonabeau et al., 1999), bird flock (particle swarm) ...

Author: Renbin Xiao

Publisher: Elsevier Inc. Chapters

ISBN: 9780128068915

Category: Computers

Page: 450

View: 885

In view of labor division in swarm intelligence, a new research paradigm of “problem-oriented approach to swarm intelligence” is constructed. The key to the success of such an approach is to grasp the features of problem objects sufficiently. At first, the labor division behaviors of ant colonies are discoursed and some descriptions of ant colony’s labor division models are given. Taking three practical problems as the backgrounds, the corresponding modeling and simulation approaches to ant colony’s labor division are investigated. Considering the diverse nature of virtual enterprise tasks, ant colony’s labor division model with multitask is proposed. Similarly, ant colony’s labor division model with multistate is also proposed by considering the diverse characteristics of product varieties in pull production systems. According to the relation of resource constraints of task allocation in resilient supply chains, ant colony’s labor division model with multiconstraint is put forward. Finally, the key points to implement “problem-oriented approach to swarm intelligence” are refined and expounded.
Categories: Computers

Swarm Intelligence

Swarm Intelligence

The discussion is a high-level overview to help researchers design their investigations; you should be conversant with these tools if you're going to evaluate what you are doing with particle swarm optimization—or any other stochastic ...

Author: Russell C. Eberhart

Publisher: Elsevier

ISBN: 9780080518268

Category: Mathematics

Page: 512

View: 243

Traditional methods for creating intelligent computational systems have privileged private "internal" cognitive and computational processes. In contrast, Swarm Intelligence argues that human intelligence derives from the interactions of individuals in a social world and further, that this model of intelligence can be effectively applied to artificially intelligent systems. The authors first present the foundations of this new approach through an extensive review of the critical literature in social psychology, cognitive science, and evolutionary computation. They then show in detail how these theories and models apply to a new computational intelligence methodology—particle swarms—which focuses on adaptation as the key behavior of intelligent systems. Drilling down still further, the authors describe the practical benefits of applying particle swarm optimization to a range of engineering problems. Developed by the authors, this algorithm is an extension of cellular automata and provides a powerful optimization, learning, and problem solving method. This important book presents valuable new insights by exploring the boundaries shared by cognitive science, social psychology, artificial life, artificial intelligence, and evolutionary computation and by applying these insights to the solving of difficult engineering problems. Researchers and graduate students in any of these disciplines will find the material intriguing, provocative, and revealing as will the curious and savvy computing professional. * Places particle swarms within the larger context of intelligent adaptive behavior and evolutionary computation. * Describes recent results of experiments with the particle swarm optimization (PSO) algorithm * Includes a basic overview of statistics to ensure readers can properly analyze the results of their own experiments using the algorithm. * Support software which can be downloaded from the publishers website, includes a Java PSO applet, C and Visual Basic source code.
Categories: Mathematics

Swarm Intelligence Optimization

Swarm Intelligence Optimization

Chakraborty, A. and Kar, A.K., Swarm Intelligence: A Review of Algorithms. In: Patnaik S., Yang XS., Nakamatsu K. (eds) Nature-Inspired Computing and Optimization. Modeling and Optimization in Science and Technologies, vol 10.

Author: Abhishek Kumar

Publisher: John Wiley & Sons

ISBN: 9781119778905

Category: Computers

Page: 384

View: 755

Resource optimization has always been a thrust area of research, and as the Internet of Things (IoT) is the most talked about topic of the current era of technology, it has become the need of the hour. Therefore, the idea behind this book was to simplify the journey of those who aspire to understand resource optimization in the IoT. To this end, included in this book are various real-time/offline applications and algorithms/case studies in the fields of engineering, computer science, information security, and cloud computing, along with the modern tools and various technologies used in systems, leaving the reader with a high level of understanding of various techniques and algorithms used in resource optimization.
Categories: Computers

Swarm Intelligence

Swarm Intelligence

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 ...

Author: Felix Chan

Publisher: BoD – Books on Demand

ISBN: 9783902613097

Category: Computers

Page: 548

View: 552

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.
Categories: Computers

Handbook of Research on Swarm Intelligence in Engineering

Handbook of Research on Swarm Intelligence in Engineering

In the following sections we discuss separately the general principles behind the swarm-inspired approaches to various problems. 4. SWARM INTELLIGENCE A swarm is a large number of homogenous, simple agents interacting locally among ...

Author: Bhattacharyya, Siddhartha

Publisher: IGI Global

ISBN: 9781466682924

Category: Computers

Page: 744

View: 447

Swarm Intelligence has recently emerged as a next-generation methodology belonging to the class of evolutionary computing. As a result, scientists have been able to explain and understand real-life processes and practices that previously remained unexplored. The Handbook of Research on Swarm Intelligence in Engineering presents the latest research being conducted on diverse topics in intelligence technologies such as Swarm Intelligence, Machine Intelligence, Optical Engineering, and Signal Processing with the goal of advancing knowledge and applications in this rapidly evolving field. The enriched interdisciplinary contents of this book will be a subject of interest to the widest forum of faculties, existing research communities, and new research aspirants from a multitude of disciplines and trades.
Categories: Computers

Advances in Swarm Intelligence

Advances in Swarm Intelligence

Swarm Intelligence and Nature-Inspired Computing 3 Swarm Unit Digital Control System Simulation . . . . . . . . . . Eugene Larkin ... Natural Emergence of Heterogeneous Strategies in Artificially Intelligent Competitive Teams .

Author:

Publisher: Springer Nature

ISBN: 9783030788117

Category: Swarm intelligence

Page: 591

View: 463

This two-volume set LNCS 12689-12690 constitutes the refereed proceedings of the 12th International Conference on Advances in Swarm Intelligence, ICSI 2021, held in Qingdao, China, in July 2021. The 104 full papers presented in this volume were carefully reviewed and selected from 177 submissions. They cover topics such as: Swarm Intelligence and Nature-Inspired Computing; Swarm-based Computing Algorithms for Optimization; Particle Swarm Optimization; Ant Colony Optimization; Differential Evolution; Genetic Algorithm and Evolutionary Computation; Fireworks Algorithms; Brain Storm Optimization Algorithm; Bacterial Foraging Optimization Algorithm; DNA Computing Methods; Multi-Objective Optimization; Swarm Robotics and Multi-Agent System; UAV Cooperation and Control; Machine Learning; Data Mining; and Other Applications.
Categories: Swarm intelligence

Swarm Intelligence and Bio Inspired Computation

Swarm Intelligence and Bio Inspired Computation

Swarm intelligence–based metaheuristic algorithms imitate the social behavior of insect colonies. Commonly accepted definition of swarm intelligence is that it is the property of a system whereby the collective behaviors of ...

Author: M.P. Saka

Publisher: Elsevier Inc. Chapters

ISBN: 9780128068885

Category: Computers

Page: 450

View: 809

Swarm intelligence refers to collective intelligence. Biologists and natural scientist have been studying the behavior of social insects due to their efficiency of solving complex problems such as finding the shortest path between their nest and food source or organizing their nests. In spite of the fact that these insects are unsophisticated individually, they make wonders as a swarm by interaction with each other and their environment. In last two decades, the behaviors of various swarms that are used in finding preys or mating are simulated into a numerical optimization technique. In this chapter, eight different swarm intelligence–based algorithms are summarized and their working steps are listed. These techniques are ant colony optimizer, particle swarm optimizer, artificial bee colony algorithm, glowworm algorithm, firefly algorithm, cuckoo search algorithm, bat algorithm, and hunting search algorithm. Two optimization problems taken from the literature are solved by all these eight algorithms and their performance are compared. It is noticed that most of the swarm intelligence–based algorithms are simple and robust techniques that determine the optimum solution of optimization problems efficiently without requiring much of a mathematical struggling.
Categories: Computers

Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development

Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development

In Advances in Swarm Intelligence for Optimizing Problems in Computer Science (pp. 53–78). Chapman and Hall/CRC, USA. [27] Kamble, T., & Rane, P. (2013, May). Brain tumor segmentation using swarm intelligence approach.

Author: Sandeep Kumar

Publisher: CRC Press

ISBN: 9781000726794

Category: Computers

Page: 146

View: 502

Healthcare sector is characterized by difficulty, dynamism and variety. In 21st century, healthcare domain is surrounded by tons of challenges in terms of Disease detection, prevention, high costs, skilled technicians and better infrastructure. In order to handle these challenges, Intelligent Healthcare management technologies are required to play an effective role in improvising patient’s life. Healthcare organizations also need to continuously discover useful and actionable knowledge to gain insight from tons of data for various purposes for saving lives, reducing medical operations errors, enhancing efficiency, reducing costs and making the whole world a healthy world. Applying Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development is essential nowadays. The objective of this book is to highlight various Swarm Intelligence and Evolutionary Algorithms techniques for various medical issues in terms of Cancer Diagnosis, Brain Tumor, Diabetic Retinopathy, Heart disease as well as drug design and development. The book will act as one-stop reference for readers to think and explore Swarm Intelligence and Evolutionary Algorithms seriously for real-time patient diagnosis, as the book provides solutions to various complex diseases found critical for medical practitioners to diagnose in real-world. Key Features: Highlights the importance and applications of Swarm Intelligence and Evolutionary Algorithms in Healthcare industry. Elaborates Swarm Intelligence and Evolutionary Algorithms for Cancer Detection. In-depth coverage of computational methodologies, approaches and techniques based on Swarm Intelligence and Evolutionary Algorithms for detecting Brain Tumour including deep learning to optimize brain tumor diagnosis. Provides a strong foundation for Diabetic Retinopathy detection using Swarm and Evolutionary algorithms. Focuses on applying Swarm Intelligence and Evolutionary Algorithms for Heart Disease detection and diagnosis. Comprehensively covers the role of Swarm Intelligence and Evolutionary Algorithms for Drug Design and Discovery. The book will play a significant role for Researchers, Medical Practitioners, Healthcare Professionals and Industrial Healthcare Research and Development wings to conduct advanced research in Healthcare using Swarm Intelligence and Evolutionary Algorithms techniques.
Categories: Computers

Integration of Swarm Intelligence and Artificial Neural Network

Integration of Swarm Intelligence and Artificial Neural Network

Principal component of particle swarm optimization. In IEEE Proceedings of Swarm Intelligence Symposium, pp. 401–404, (2005). I. H. Grundy and A. Stacey, Particle swarm optimization with combined mutation and hill climbing, ...

Author: Satchidananda Dehuri

Publisher: World Scientific

ISBN: 9789814280143

Category: Computers

Page: 338

View: 578

This book provides a new forum for the dissemination of knowledge in both theoretical and applied research on swarm intelligence (SI) and artificial neural network (ANN). It accelerates interaction between the two bodies of knowledge and fosters a unified development in the next generation of computational model for machine learning. To the best of our knowledge, the integration of SI and ANN is the first attempt to integrate various aspects of both the independent research area into a single volume.
Categories: Computers

Advances in Swarm Intelligence Part I

Advances in Swarm Intelligence  Part I

Average-Inertia Weighted Cat Swarm Optimization Maysam Orouskhani1,*, Mohammad Mansouri2, and Mohammad Teshnehlab3 1 Msc Student, Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, ...

Author: Ying Tan

Publisher: Springer

ISBN: 9783642215155

Category: Computers

Page: 639

View: 166

The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm Intelligence, ICSI 2011, held in Chongqing, China, in June 2011. The 143 revised full papers presented were carefully reviewed and selected from 298 submissions. The papers are organized in topical sections on theoretical analysis of swarm intelligence algorithms, particle swarm optimization, applications of pso algorithms, ant colony optimization algorithms, bee colony algorithms, novel swarm-based optimization algorithms, artificial immune system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining methods, machine learning methods, feature selection algorithms, pattern recognition methods, intelligent control, other optimization algorithms and applications, data fusion and swarm intelligence, as well as fish school search - foundations and applications.
Categories: Computers