Swarm Intelligence

This book provides a detailed look at models of social insect behavior and how to apply these models in the design of complex systems.

Swarm Intelligence

Author: Eric Bonabeau

Publisher: Oxford University Press

ISBN: 9780198030157

Page: 320

View: 664

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

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 ...

Swarm Intelligence

Author: Felix Chan

Publisher: BoD – Books on Demand

ISBN: 3902613092

Page: 548

View: 486

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.

Swarm Intelligence

The surprising truth is that the future will be pioneered by the collective problem-solvers, making Swarm Intelligence a must-read for business leaders, educators, and anyone else concerned with nurturing creative intelligence and ...

Swarm Intelligence

Author: James Haywood Rolling, Jr.

Publisher: St. Martin's Press

ISBN: 1137401516

Page: 256

View: 447

Companies and organizations everywhere cite creativity as the most desirable - and elusive - leadership quality of the future. Yet scores measuring creativity among American children have been on the wane for decades. A specialist in creative leadership, professor James Haywood Rolling, Jr. knows firsthand that the classroom is a key to either unlocking or blocking the critical imagination. He argues that today's schools, with their focus on rote learning and test-taking, work to stymie creativity, leaving children cut off from their natural impulses and boxed in by low expectations. Drawing on cutting-edge research in the realms of biological swarm theory, systems theory, and complexity theory, Rolling shows why group collaboration and adaptive social networking make us both smarter and more creative, and how we can design education and workplace practices around these natural principles, instead of pushing a limited focus on individual achievement that serves neither children nor their future colleagues, managers and mentors. The surprising truth is that the future will be pioneered by the collective problem-solvers, making Swarm Intelligence a must-read for business leaders, educators, and anyone else concerned with nurturing creative intelligence and innovative habits in today's youth.

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.

Swarm Intelligence

Author: Christian Blum

Publisher: Springer Science & Business Media

ISBN: 3540740899

Page: 286

View: 613

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.

Innovations in Swarm Intelligence

In this chapter, advances in techniques and applications of swarm intelligence
are presented. An overview of different swarm intelligence models is described.
The dynamics of each swarm intelligence model and the associated
characteristics ...

Innovations in Swarm Intelligence

Author: Chee Peng Lim

Publisher: Springer Science & Business Media

ISBN: 3642042244

Page: 255

View: 167

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.

Handbook of Swarm Intelligence

particle swarm optimization algorithm is used as a global search method to find
good initial starting point(s), and then a local ... Similar to the traditional
algorithms for solving large scale problems, swarm intelligence algorithms also
suffer the ...

Handbook of Swarm Intelligence

Author: Bijaya Ketan Panigrahi

Publisher: Springer Science & Business Media

ISBN: 9783642173905

Page: 544

View: 369

From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.

Swarm Intelligence

These proceedings contain the papers presented at ANTS 2010, the 7th
International Conference on Swarm Intelligence, organized by IRIDIA, CoDE,
Université Libre de Bruxelles, Brussels, Belgium, during September 8–10, 2010.
The ANTS ...

Swarm Intelligence

Author: Marco Dorigo

Publisher: Springer Science & Business Media

ISBN: 3642154603

Page: 582

View: 856

These proceedings contain the papers presented at ANTS 2010, the 7th Int- national Conference on Swarm Intelligence, organized by IRIDIA, CoDE, U- versitéLibre de Bruxelles,Brussels, Belgium, during September 8–10,2010.The ANTS series started in 1998 with the First International Workshop on Ant Colony Optimization (ANTS 1998), which attracted more than 50 participants. Since then ANTS, which is held bi-annually, has gradually become an inter- tional forum for researchers in the wider ?eld of swarm intelligence. In the past (since 2004), this development has been acknowledged by the inclusion of the term“SwarmIntelligence” (nextto“AntColonyOptimization”)intheconference title. This year's ANTS conference was o?cially devoted to the ?eld of swarm intelligence as a whole, without any bias towards speci?c research directions. As a result, the title of the conference was changed to “The International Conf- ence on SwarmIntelligence.” This name change is already in place this year,and future ANTS conferences will continue to use the new title. Thisvolumecontainsthebestpapersselectedoutof99submissions.Ofthese, 28 were accepted as full-length papers, while 27 were accepted as short papers. This corresponds to an overall acceptance rate of 56%. Also included in this volume are 14 extended abstracts. Of the full-length papers, 15 were selected for oral presentation at the c- ference. All other contributions, including short papers and extended abstracts, werepresentedin the formof poster presentations.Following the conference,the journal Swarm Intelligence will publish extended versions of some of the best papers presented at the conference.

Swarm Intelligence

Swarm Intelligence

Author: Ying Tan

Publisher: Control, Robotics and Sensors

ISBN: 1785616315

Page: 880

View: 213

This book includes 27 chapters and presents a great number of real-world applications of swarm intelligence algorithms and related evolutionary algorithms.

Ant Colony Optimization and Swarm Intelligence

These observations have inspired studies in the field of swarm intelligence that
seek to demonstrate similar properties in synthetic swarms [2,3]. Most reported
demonstrations of robotic swarms use groups of individual swarmers already in ...

Ant Colony Optimization and Swarm Intelligence

Author: Marco Dorigo

Publisher: Springer Science & Business Media

ISBN: 3540875263

Page: 416

View: 693

The series of biannual international conferences “ANTS – International C- ference on Ant Colony Optimization and Swarm Intelligence”, now in its sixth edition, was started ten years ago, with the organization of ANTS’98. As some readers might recall, the ?rst edition of ANTS was titled “ANTS’98 – From Ant Colonies to Arti?cial Ants: First International Workshop on Ant Colony Op- mization. ” In fact, at that time the focus was mainly on ant colony optimization (ACO), the ?rst swarm intelligence algorithm to go beyond a pure scienti?c interest and to enter the realm of real-world applications. Interestingly, in the ten years after the ?rst edition there has been a gr- ing interest not only for ACO, but for a number of other studies that belong more generally to the area of swarmintelligence. The rapid growth of the swarm intelligence ?eld is attested by a number of indicators. First, the number of s- missions and participants to the ANTS conferences has steadily increased over the years. Second, a number of international conferences in computational - telligence and related disciplines organize workshops on subjects such as swarm intelligence, ant algorithms, ant colony optimization, and particle swarm op- mization. Third, IEEE startedorganizing,in 2003,the IEEE SwarmIntelligence Symposium (in order to maintain unity in this growing ?eld, we are currently establishingacooperationagreementbetweenIEEE SISandANTSsoastohave 1 IEEE SIS in odd years and ANTS in even years). Last, the Swarm Intelligence journal was born.

Swarm Intelligence in Data Mining

Swarm. Clustering. Based. on. Flowers. Pollination. by. Artificial. Bees. Majid
Kazemian, Yoosef Ramezani, Caro Lucas and Behzad Moshiri Control and
Intelligent Processing Center of Excellence, School of Electrical and Computer ...

Swarm Intelligence in Data Mining

Author: Ajith Abraham

Publisher: Springer Science & Business Media

ISBN: 3540349553

Page: 268

View: 577

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.

Advances in Swarm Intelligence

Advances in Swarm Intelligence

Author: Ying Tan

Publisher: Springer Science & Business Media

ISBN: 3642134971

Page: 772

View: 280

The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available. The scope of LNCS, including its subseries LNAI and LNBI, spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields. In parallel to the printed book, each new volume is published electronically in LNCS Online.

Advances in Swarm Intelligence

This book and its companion volume, LNCS vols. 6145 and 6146, constitute the proceedings of the International Conference on Swarm Intelligence (ICSI 2010) held in Beijing, the capital of China, during June 12-15, 2010.

Advances in Swarm Intelligence

Author: KAY CHEN TAN

Publisher: Springer

ISBN: 3642134955

Page: 746

View: 780

This book and its companion volume, LNCS vols. 6145 and 6146, constitute the proceedings of the International Conference on Swarm Intelligence (ICSI 2010) held in Beijing, the capital of China, during June 12-15, 2010. ICSI 2010 was the ?rst gathering in the world for researchers working on all aspects of swarm intelligence, and providedan academic forum for the participants to disseminate theirnewresearch?ndingsanddiscussemergingareasofresearch.Italsocreated a stimulating environment for the participants to interact and exchange inf- mation on future challenges and opportunities of swarm intelligence research. ICSI 2010 received 394 submissions from about 1241 authors in 22 countries and regions (Australia, Belgium, Brazil, Canada, China, Cyprus, Hong Kong, Hungary, India, Islamic Republic of Iran, Japan, Jordan, Republic of Korea, Malaysia, Mexico, Norway, Pakistan, South Africa, Chinese Taiwan, UK, USA, Vietnam) across six continents (Asia, Europe, North America, South America, Africa, and Oceania). Each submission was reviewed by at least three reviewers. Based on rigorous reviews by the Program Committee members and reviewers, 185 high-quality papers were selected for publication in the proceedings with the acceptance rate of 46.9%. The papers are organized in 25 cohesive sections covering all major topics of swarm intelligence research and development.

Advances in Swarm Intelligence Part II

6728 and 6729, constitute the proceedings of the Second International
Conference on Swarm Intelligence (ICSI 2011) held during June 12–15, 2011 in
Chongqing, well known as the Mountain City, the southwestern commercial
capital of ...

Advances in Swarm Intelligence  Part II

Author: Ying Tan

Publisher: Springer Science & Business Media

ISBN: 3642215238

Page: 587

View: 783

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.

Swarm Intelligence for Multi objective Problems in Data Mining

Further, by dynamically weighting and combining the measurements from these
classifiers, performance is improved. Weights are found using a Particle Swarm
Optimization search algorithm and are a function of required accuracy and
degree ...

Swarm Intelligence for Multi objective Problems in Data Mining

Author: Carlos Coello Coello

Publisher: Springer Science & Business Media

ISBN: 3642036244

Page: 287

View: 727

The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining.

Swarm Intelligence and Bio Inspired Computation

The “firefly algorithm” (FA) is a nature-inspired technique originally designed for solving continuous optimization problems.

Swarm Intelligence and Bio Inspired Computation

Author: Gilang Kusuma Jati

Publisher: Elsevier Inc. Chapters

ISBN: 012806899X

Page: 450

View: 646

The “firefly algorithm” (FA) is a nature-inspired technique originally designed for solving continuous optimization problems. There are several existing approaches that apply FA also as a basis for solving discrete optimization problems, in particular the “traveling salesman problem” (TSP). In this chapter, we present a new movement scheme called edge-based movement, an operation which guarantees that a candidate solution more closely resembles another one. This leads to a more FA-like behavior of the algorithm. We investigate the performance of the ‘evolutionary discrete firefly algorithm” when using this new edge-based movement and compare it against previous methods. Computer simulations show that the new movement scheme produces slightly better accuracy with much faster average time. The average speedup factor is 14.06 times.

Swarm Intelligence

These proceedings contain the papers presented at ANTS 2012, the 8th
International Conference on Swarm Intelligence, held at IRIDIA, Université Libre
de Bruxelles, Brussels, Belgium, during September 12–14, 2012. The ANTS
series ...

Swarm Intelligence

Author: Mauro Birattari

Publisher: Springer

ISBN: 3642326501

Page: 356

View: 325

This book constitutes the proceedings of the 8th International Conference on Swarm Intelligence, held in Brussels, Belgium, in September 2012. This volume contains 15 full papers, 20 short papers, and 7 extended abstracts carefully selected out of 81 submissions. The papers cover various topics of swarm intelligence.

Swarm Intelligence and Bio Inspired Computation

This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research ...

Swarm Intelligence and Bio Inspired Computation

Author: Xin-She Yang

Publisher: Newnes

ISBN: 0124051774

Page: 450

View: 312

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. Focuses on the introduction and analysis of key algorithms Includes case studies for real-world applications Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

Recent Algorithms and Applications in Swarm Intelligence Research

Swarm intelligence algorithms are a collection of population-based stochastic
optimization algorithms which are generally categorized under the big umbrella
of evolutionary computation algorithms. There is no standard definition that
defines ...

Recent Algorithms and Applications in Swarm Intelligence Research

Author: Shi, Yuhui

Publisher: IGI Global

ISBN: 1466624809

Page: 340

View: 314

Advancements in the nature-inspired swarm intelligence algorithms continue to be useful in solving complicated problems in nonlinear, non-differentiable, and un-continuous functions as well as being applied to solve real-world applications. Recent Algorithms and Applications in Swarm Intelligence Research highlights the current research on swarm intelligence algorithms and its applications. Including research and survey and application papers, this book serves as a platform for students and scholars interested in achieving their studies on swarm intelligence algorithms and their applications.

Multi objective Swarm Intelligence

The purpose of this volume entitled “Multi-objective Swarm Intelligence:
Theoretical Advances and Applications” is to attract a wide range of researchers
and readers from all fields of science and engineering performing
interdisciplinary ...

Multi objective Swarm Intelligence

Author: Satchidananda Dehuri

Publisher: Springer

ISBN: 3662463091

Page: 201

View: 176

The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.

Swarm Intelligence Based Optimization

These post-proceedings include a selection of the best papers presented at the
International Conference on Swarm Intelligence-Based Optimization, ICSIBO
2014, held in Mulhouse (France). ICSIBO 2014 is a continuation of the
conferences ...

Swarm Intelligence Based Optimization

Author: Patrick Siarry

Publisher: Springer

ISBN: 3319129708

Page: 193

View: 988

This book constitutes the thoroughly refereed post-conference proceedings of the 1st International Conference on Swarm Intelligence Based Optimization, ICSIBO 2014, held in Mulhouse, France, in May 2014. The 20 full papers presented were carefully reviewed and selected from 48 submissions. Topics of interest presented and discussed in the conference focuses on the theoretical progress of swarm intelligence metaheuristics and their applications in areas such as: theoretical advances of swarm intelligence metaheuristics, combinatorial, discrete, binary, constrained, multi-objective, multi-modal, dynamic, noisy, and large-scale optimization, artificial immune systems, particle swarms, ant colony, bacterial foraging, artificial bees, fireflies algorithm, hybridization of algorithms, parallel/distributed computing, machine learning, data mining, data clustering, decision making and multi-agent systems based on swarm intelligence principles, adaptation and applications of swarm intelligence principles to real world problems in various domains.