Books

Swarm Intelligence (The Morgan Kaufmann Series in Artificial Intelligence)

Average customer rating:

I should need a little bit more
Good, but could have been more concise.
Interesting Paradigm
Needs more details, but a good introduction.
Mind is Social

Swarm Intelligence (The Morgan Kaufmann Series in Artificial Intelligence)
Russell C. Eberhart , Yuhui Shi , and James Kennedy
Manufacturer: Morgan Kaufmann
ProductGroup: Book
Binding: Hardcover

General | Graphic Design | Computers & Internet | Subjects | Books

General | Computers & Internet | Subjects | Books

General | Software | Computers & Internet | Subjects | Books

General | Social Sciences | Nonfiction | Subjects | Books

General | Engineering | Professional & Technical | Subjects | Books

Look Inside Computer Books | Trip | Specialty Stores | Books

Look Inside Nonfiction Books | Trip | Specialty Stores | Books

All Amazon Upgrade | Amazon Upgrade | Stores | Books

Computers & Internet | Amazon Upgrade | Stores | Books

Engineering | Amazon Upgrade | Stores | Books

Nonfiction | Amazon Upgrade | Stores | Books

Professional & Technical | Amazon Upgrade | Stores | Books

Qualifying Textbooks - Spring 2007 | Stores | Books

General | Software Books | Custom Stores | Stores | Software
Similar Items:

Ant Colony Optimization (Bradford Books)
Fundamentals of Computational Swarm Intelligence
Swarm Intelligence: From Natural to Artificial Systems (Santa Fe Institute Studies in the Sciences of Complexity Proceedings)
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
An Introduction to Genetic Algorithms (Complex Adaptive Systems)

ASIN: 1558605959

Book Description

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 methodologyparticle swarmswhich 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.

Customer Reviews:

I should need a little bit more.......2006-08-17

I have read the book at a stretch. In my view, the thesis (human is social) is a very simple, wit, and sound one. Maybe it is a very profound concern to us, whose complete consequences have not yet been taken in a serious consideration. Foundations and arguments in favor, coming from social and computer sciences, are orderly and properly unfolded along the book. The associated web page is being a very valuable resource for me. In short, I have made acquaintance with a good, satisfying mate. There is only a but for me: It has not moved me (but that is my but, not its...)

Good, but could have been more concise........2004-09-13

Swarm intelligence is burdened with an awful lot of material that is not core to PSO. A great deal of the book consists of the philosophical ramblings of the authors, rather than technical treatment of the topic at hand. An even larger chunk of the book was devoted to what was essentially a survey of AI: neural nets, evolutionary programming, heuristics, etc. Much too much space was devoted to grounding the reader in AI before proceeding. I must admit, however, that, while I found it out of place, the 'AI primer' part of the book is one of the most useful and lucid I have seen; I just think that it should have been a separate book (and this one should have been much thinner). The material that is specific to PSO is a very small fraction of the book, but is thorough and accessible; there really are few alternatives if one is particularly interested in PSO. However, if you are just interested in emergent behavior, and its applications to AI, take a look at Ant Colony Optimization (Dorigo). It covers ACO, rather than PSO, but is more more readable, and provides a much better technical treatment of the topic, if you want to avoid the philosophy and primer.

Interesting Paradigm.......2004-09-09

It's an immersive and powerful piece of scientific metrics and theoretical paradigm presentation. It shows that life can be a much deeper form of existence. The book presents the complexities of PSO in its network relativity but can be created using simple algorithms. The basis comes from the behavioural science andsocial patterns of insects such as bees and ants. Their process of colonial interaction and food foraging can be applied as a strong mathematical structure to computational science, robotics, and network technology. At the same time, you can take the exact principles -- in its raw idea -- and apply it to economic structure and business dynamics. I love how this book harks back to the parable of the blind men trying to explain what an elephant is like.

Needs more details, but a good introduction........2004-07-26

The authors of this book state therein that "mind is not found in covert, private chambers hidden away inside the individual, but exists out in the open; it is a public phenomenon." This would be a very difficult claim to prove from a scientific standpoint, requiring an understanding of neuroscience, consciousness, and psychology that is not yet available. The author's intent though is more modest: they want to use this statement, which they encapsulate as "swarm intelligence", as a guide to finding successful optimization algorithms. They spend many pages discussing the foundations and background behind their approach, perhaps in too much detail given the usual pragmatism exhibited by many who study algorithms. Swarm intelligence is a relatively new paradigm in the field of optimization, but its justification should come from the results it gives in practical optimization problems, not in the broad philosophical language that predominates the first part of the book.

Particle swarm optimization is introduced in the book in both 'binary' and 'real-valued' form. The authors identify three principles behind the workings of particle swarms, namely the tendency to "evaluate"; the use of comparisons to others as a way of measuring individual status or progress; and the use of imitation. These three principles they say allow individuals to adapt to highly complex environments and solve very difficult problems. A binary decision model is used to introduce binary swarm algorithm, which is given in pseudocode, and is tested using a binary-coded version of the De Jong suite of test problems for optimization algorithms. A particle swarm model over the real numbers is then discussed, along with pseudocode, Both the binary and real models of particle swarms illustrate the fact that particle swarm optimization is a consequence of social interaction. The particles or "individuals" in the swarm learn from each other, and move to become more similar to their neighbors based on the knowledge obtained. Particle swarm optimization is dependent on the existence of social structure, the latter of which is determined by the formation of neighborhoods. These neighborhoods can have a different topology, determined solely by the numerical indices assigned to each individual.

The pseudocode given for particle swarm optimization illustrates well the basic workings of the algorithm in terms of the "local" and "global" viewpoint of the particles in the swarm. First the swarm is initialized and the performance of each particle is evaluated using its current position. The performance of each individual is then compared to its best performance so far, and the velocity for each particle changed according to a formula dependent on a system parameter. Each particle is then moved to a new position and the entire process repeated until convergence is attained. When a particle is very far from its best solution previously found, the change in velocity will be greater in order to return the particle toward its best solution. The system parameter will govern how much the particle trajectories oscillate, with smaller values of this parameter ensuring smoother trajectories. The authors give examples with graphs to illustrate this behavior and the influence of the system parameter.

Being aware that particle swarm optimization is typically viewed as a kind of evolutionary algorithm, the author address in some detail the reasons for this classification and its justification. Acknowledging that particle swarm algorithms have been influenced by evolutionary computation, they discuss some of the differences between the two approaches. In evolutionary algorithms individuals survive according to their fitness, whereas in particle swarms every individual will survive. In addition, in particle swarms, it is the velocities that are adjusted, whereas in evolutionary computing it is the positions that are state. The authors express this by saying that it is the "fate" rather than the "state" that is altered in particle swarm optimization.

The authors include an entire chapter on applications in the book, one of them being the use of particle swarms to evolve neural networks. Evolved neural networks have been shown to perform better in some cases than ones designed from scratch. After discussing some of the approaches to evolving neural networks, the authors point out, correctly, that hardly any of the studies in evolving neural networks are quantitative studies of how well they perform relative to other approaches Performance metrics are hardly ever given, which would allow interested parties to make objective and intelligent decisions on which approach is the most viable. The author's approach of using particle swarms to evolve neural networks also, interestingly, involves evolving the transfer functions of the neural networks, and they test their approach by using the Iris Data Set, a frequent benchmark for classification algorithms. Preliminary results indicate that their approach is a viable one and that it shows promise, but they admit that further experiments are needed in order to form valid conclusions.

So are the optimization algorithms based on swarm intelligence better than those that are based on, for example, on evolutionary algorithms? Are they better than those that are purely randomized algorithms? The authors are not shy about discussing how swarm intelligence optimization algorithms compare with other optimization algorithms, particularly randomized algorithms and the now famous "free-lunch" theorems of David Wolpert and William Macready. They discuss the free-lunch theorems via a very interesting example dealing with finding one's way out of a room. Using this example, they are convincing in their claim that even though no algorithm can be said to be better than any other when averaged over all cost functions, this averaging is done over processes or tasks that might be deemed absurd in the context of many problems of practical interest. Thus for "real" problems, one algorithm might indeed be "better" than another.

Mind is Social.......2003-02-01

My original motivation for reading Swarm Intelligence was a desire to learn about the Particle Swarm Optimization (PSO) algorithm -- in particular, to learn how to implement it in a Java program. To the credit of its authors, what I found in Swarm Intelligence was far more than that. The authors have taken on the rather daunting task of presenting a new paradigm -- a new way of thinking about mind and intelligence -- and they have succeeded.

PSO, itself, is deceptively simple. The heart of the algorithm can be written in a single line of code. Understanding the basis for its approach to intelligence isn't difficult, either. The authors begin their explanation using the old parable about the blind men and the elephant. You are most likely familiar with the story. In summary form, it is about a group of blind men standing around an elephant each declaring "what an elephant is like" based upon which part of the elephant they are touching -- and elephant is like: a wall (side); a tree trunk (leg); a hose (trunk); a fan (ear); and so on.

What is wrong with this story, the authors point out, is its implicit assumption that these blind men are also deaf. If not, as they each announced their impressions the individuals, as a group, would discover much more about what an elephant is. The significance here is easily missed. The capabilities of a group emerge from the individuals immersed in it. The group can do more (see more, discover more, experiment more) than the individuals from which it emerges and, by virtue of their immersion in it, the individuals benefit (and in turn, the group then benefits as it now emerges from these "benefited" individuals).

The authors view this emergent/immergent "cycle" as the driving force behind mind and intelligence. In contrast to the normal (phenomenological) view of mind as an internal, private "thing that thinks," the authors assert that mind is something requiring sociality. To put it bluntly (and the authors do), in the absence of social immersion there is no mind; mind is social. The majority of the book is focused on this: why it's true, how it's true and how it is implemented in the PSO algorithm.

It is easy to see how the book might have ended up a long philosophical argument. It isn't. Instead, the authors present a nicely written history of efforts to achieve "computational intelligence" (a much better phrase than the more familiar "artificial intelligence") including great summaries of evolutionary approaches, fuzzy logic, neural nets and artificial life. Along the way they point out recent advances in psychology and sociology. The net effect is that they don't need to argue their point. By the end of this part of the book the importance of sociality has become rather obvious. If you are interested in sociology, psychology, engineering and/or computer science you will enjoy this part of the book immensely, learn a lot and find a wealth of references to additional sources of information.

The second part of the book presents the PSO algorithm, compares its performance with other methodologies (in addition to being simpler to understand and implement, it's an order of magnitude faster when applied to certain problems -- training neural nets, for example), demonstrates how it is applied to some "real life" problems and discusses some implications of (and speculations about) the approach. As with the first part of the book, the presentation is clear, concise and informative. There is, though, indications here that the PSO approach is rather new (young). There isn't enough experience with PSO yet to give this part of the book the same feeling of depth one gets from the first part.

It's worth noting that the presentation (and description) of the PSO algorithm is done in mathematical terms. I would have much preferred a programming approach (using pseudo code) not because the math is too difficult (it's not) but because I haven't been "immersed in a mathematically minded social group" for many years. The almost exclusive use of Greek letters for symbols (variables) made reading difficult. Not only are they visually unfamiliar, I don't know their pronunciations (to illustrate the difficulty by way of analogy, consider the difference between reading "y equals b times x plus z" and "xgt equals kqj times yxf plus ktv"). I ended up rewriting the formulas in more familiar terms (using the text to figure out what the symbols represent when necessary) before I felt that I understood them.

Mentioning my problem with the math is not meant to criticize but to suggest that the book could have been made accessible to more people had it also contained a more readable (and retainable) form of the algorithm, perhaps in an appendix. A good analogy of the PSO approach (more detailed than the "blind men" story) would also have been helpful. The only real criticism I have of the book's content is a minor one. Being as it is focused on the social requirements for mind, it tends to overlook the degree of individuality required to make PSO work. The algorithm, itself, has variables which control the expression of individuality and without which it could not work (at least not well), but this flipside to the social nature of the algorithm is never discussed as such. PSO works well precisely because it maintains the rather chaotic balance between the effects of sociality and individuality. The book presents a rather one-sided view of this balance.

An aside for programmers: There is a companion site (of sorts) on the web for the book through which you can download Visual Basic and C source code of PSO implementations. There is also a Java applet which demonstrates PSO applied to a number of test functions but the source code for it is not available. There will also be an open source Java implementation as soon as I can make one available.

Fundamentals of Computational Swarm Intelligence

Average customer rating:

Fundamentals of Computational Swarm Intelligence
Andries P. Engelbrecht
Manufacturer: Wiley
ProductGroup: Book
Binding: Hardcover

General | Science | Subjects | Books

General | Arts & Photography | Subjects | Books

Look Inside Art Books | Trip | Specialty Stores | Books

Look Inside Computer Books | Trip | Specialty Stores | Books

Look Inside Science Books | Trip | Specialty Stores | Books

Qualifying Textbooks - Spring 2007 | Stores | Books
Similar Items:

Swarm Intelligence (The Morgan Kaufmann Series in Artificial Intelligence)
Ant Colony Optimization (Bradford Books)
Particle Swarm Optimization
Swarm Intelligence: From Natural to Artificial Systems (Santa Fe Institute Studies in the Sciences of Complexity Proceedings)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)

ASIN: 0470091916

Book Description

Fundamentals of Computational Swarm Intelligence provides a comprehensive introduction to the new computational paradigm of Swarm Intelligence (SI), a field that emerged from biological research, and is now picking up momentum within the computational research community. Bio-inspired systems are becoming increasingly important research areas for computer scientists, engineers, economists, bioinformaticians, operational researchers, and many other disciplines. This book introduces the reader to the mathematical models of social insects collective behaviour, and shows how they can be used in solving optimization problems.

Focusing on the algorithmic implementation of models of swarm behavior, this book:

Examines how social network structures are used to exchange information among individuals, and how the aggregate behaviour of these individuals forms a powerful organism.
Introduces a compact summary of the formal theory of optimisation.
Outlines paradigms with relations to SI, including genetic algorithms, evolutionary programming, evolutionary strategies, cultural algorithms and co-evolution.
Looks at the choreographic movements of birds in a flock as a basis for the Particle Swarm Optimization (PSO) models, and provides an extensive treatment of different classes of PSO models.
Shows how the behaviour of ants can be used to implement Ant Colony Optimization (ACO) algorithms to solve real-world problems including routing optimization, structure optimization, data mining and data clustering.
Considers different classes of optimization problems, including multi-objective optimization, dynamic environments, discrete and continuous search spaces, constrained optimization, and niching.

Includes an accompanying website containing Java classes and implementations of the different algorithms that can be used to test PSO and ACO algorithms: http://si.cs.up.ac.za

The interdisciplinary nature of this field will make Fundamentals of Computational Swarm Intelligence an essential resource for readers with diverse backgrounds. In addition, it will be an excellent reference for computer scientists, practitioners in business or industry and researchers involved in the analysis, design and simulation of multibody systems. Advanced undergraduates and graduate students in artificial intelligence, collective intelligence and engineering will also find this book an invaluable tool.

Average customer rating:

Particle Swarm Optimization
Maurice Clerc
Manufacturer: ISTE Publishing Company
ProductGroup: Book
Binding: Hardcover

General | Engineering | Professional & Technical | Subjects | Books

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

General | Arts & Photography | Subjects | Books

Look Inside Art Books | Trip | Specialty Stores | Books

Look Inside Science Books | Trip | Specialty Stores | Books
Similar Items:

Fundamentals of Computational Swarm Intelligence
Swarm Intelligence (The Morgan Kaufmann Series in Artificial Intelligence)
Ant Colony Optimization (Bradford Books)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Multi-Objective Optimization Using Evolutionary Algorithms

ASIN: 1905209045

Book Description

Particles, information link, memory, and cooperation are discussed in this introduction to particle swarm optimization. Starting with a simple but efficient parametric version, this manual shows how to adapt the basic principles for an enhanced, fully adaptive version. All source programs are either included or available for free download.

Emergence: The Connected Lives of Ants, Brains, Cities, and Software

Average customer rating:

finger food for the mind
Emergence - a guide for the future
Go To the Ant Thou Sluggard!
Provides a decent primer to an increasingly important concept
Exciting and provoking

Emergence: The Connected Lives of Ants, Brains, Cities, and Software
Steven Johnson
Manufacturer: Scribner
ProductGroup: Book
Binding: Hardcover

Chaos & Systems | Physics | Science | Subjects | Books

Acoustics & Sound | Physics | Science | Subjects | Books

System Theory | Physics | Science | Subjects | Books

General | Science | Subjects | Books

General & Reference | Technology | Science | Subjects | Books

Systems Analysis & Design | Computer Science | Computers & Internet | Subjects | Books

General | Computer Science | Computers & Internet | Subjects | Books

Information Theory | Computer Science | Computers & Internet | Subjects | Books

General | Computers & Internet | Subjects | Books
Similar Items:

Linked: How Everything Is Connected to Everything Else and What It Means
Sync: The Emerging Science of Spontaneous Order
Mind Wide Open: Your Brain and the Neuroscience of Everyday Life
Smart Mobs: The Next Social Revolution
Hidden Order: How Adaptation Builds Complexity (Helix Books)

ASIN: 068486875X

Amazon.com's Best of 2001

An individual ant, like an individual neuron, is just about as dumb as can be. Connect enough of them together properly, though, and you get spontaneous intelligence. Web pundit Steven Johnson explains what we know about this phenomenon with a rare lucidity in Emergence: The Connected Lives of Ants, Brains, Cities, and Software. Starting with the weird behavior of the semi-colonial organisms we call slime molds, Johnson details the development of increasingly complex and familiar behavior among simple components: cells, insects, and software developers all find their place in greater schemes.

Most game players, alas, live on something close to day-trader time, at least when they're in the middle of a game--thinking more about their next move than their next meal, and usually blissfully oblivious to the ten- or twenty-year trajectory of software development. No one wants to play with a toy that's going to be fun after a few decades of tinkering--the toys have to be engaging now, or kids will find other toys.

Johnson has a knack for explaining complicated and counterintuitive ideas cleverly without stealing the scene. Though we're far from fully understanding how complex behavior manifests from simple units and rules, our awareness that such emergence is possible is guiding research across disciplines. Readers unfamiliar with the sciences of complexity will find Emergence an excellent starting point, while those who were chaotic before it was cool will appreciate its updates and wider scope. --Rob Lightner

Book Description

This book is about the mystery of why the whole is sometimes smarter than the sum of its parts.

Emergence is what happens when an interconnected system of relatively simple elements self-organizes to form more intelligent, more adaptive higher-level behavior. It's a bottom-up model; rather than being engineered by a general or a master planner, emergence begins at the ground level. Systems that at first glance seem vastly different -- ant colonies, human brains, cities, immune systems -- all turn out to follow the rules of emergence. In each of these systems, agents residing on one scale start producing behavior that lies a scale above them: ants create colonies, urbanites create neighborhoods.

In the tradition of Being Digital and The Tipping Point, Steven Johnson, acclaimed as a "cultural critic with a poet's heart" (The Village Voice), takes readers on an eye-opening intellectual journey from the discovery of emergence to its applications. He introduces us to our everyday surroundings, offering suprising examples of feedback, self-organization, and adaptive learning. How does a lively neighborhood evolve out of a disconnected association of shopkeepers, bartenders, and real estate developers? How does a media event take on a life of its own? How will new software programs create an intelligent World Wide Web?

Drawing upon evolutionary theory, urban studies, neuroscience, and computer games, Emergence is a guidebook to one of the key components of twenty-first-century culture. Until recently, Johnson explains, the disparate philosophers of emergence have worked to interpret the world. But today they are starting to change it. This book is the riveting story of that change and what it means for the future. If you've searched for information on the Web, played a recent video game, or accepted a collect call using voice recognition software, you've already encountered the new world of artificial emergence. Provocative, engaging, and sophisticated, Emergence puts you on the front lines of a sweeping revolution in science and thought.

Customer Reviews:

finger food for the mind.......2006-12-14

This is a pretty good read - it moves quickly and doesn't get you bogged down in the dna of the concept of emergence. go to wikipedia, read it. then pick up a copy of this and it will provide more context and usefulness. while this may not be the 'grand slam' of books...and to some degree it may be viewed as a popular fad topic...this book is better written than many that end up in the waste bend after page 47. if highlighter markings and cryptic notes in the margin are an indicator for me then it is safe to say that i got my money's worth...and...it contributed to my ongoing pondering of this and many other esoteric terms from the science realm.

Emergence - a guide for the future.......2006-11-10

This book is well written and provides an insight to the science of emerergence and how it can help exlain the fundamental texture of everything from ant colonies to cafe-society. It is one of those rare books that readers will benefit from reading many times. For those with a scientific appreciation it fully satisfies while those readers with a more cultural focus will still find it very readable.

The subject matter is highly important and may help create models of better societies in the economically and environmentally challenging years ahead. This book undoubtedly helps us to see a way.

Go To the Ant Thou Sluggard!.......2006-09-24

Uncommon insights into the origin and development of important things. The author shows us how there are lessons all around us if we are clever enough to be watching when they reveal themselves! Shows us that there are patterns in nature and in the human experience that, when uncovered and examined, can prove to be templates for success in our lives.

Provides a decent primer to an increasingly important concept.......2006-09-06

I liked this book. It provides a decent overview of emergent properties in general, and particularly the notion of "intelligence" as an emergent property (e.g., one ant is dumb, many ants togther are smart).

However, this book will disappoint any reader who expects a rigorous or mathematical explanation of these phenomena. All of the various anecdotes are interesting, but they appear held together by only their loose similarity of concept (i.e., they all somehow or other manifest this notion "emergence").

Although this book reads like a collection of similarly themed magazine articles, this is part and parcel with its appeal. Although it may have skimped on the "research" into the fascinating field of emergent properties, it was nevertheless well-written, readable, and interesting.

Although the notion of "Emergent Intelligence" has already been siezed upon by popular culture (e.g., Matrix, video games, internet, and on and on), the diversity and importance of this topic is far from its peak. Therefore, the more people with an understanding of it the better -- even if that understanding falls somewhere short of the Ph.d. level

Exciting and provoking.......2006-08-06

I was stunned to see so many critical reviews of this book here. Even more stunned by the criticisms. This is not a scientific treatise, and never pretends to be. This is not an introduction into the more abstract and obscure aspects of Emergence, nor is it a dry and tedious mathematical paper.

This is an interesting, graspable, exciting and intelligently written book about a phenomenon which is absolutely, positively crucial to understand. To some people Emergence is a particular abstract in a particular field - those people were disappointed and found this "light reading" - which is really too bad, because they are the ones who NEED this book the most. Alas, we can expect it to be a while before these "scientist" can look outside their own shallow mud-puddles of their over-specialties to see how applicable emergent theory is to the world we are immersed in, both natural and man-made.

If you didn't find this book exciting, you didn't read it. Sit down and read it without distraction and prejudice. Let Johnson do what he does best; take you on a journey of ideas and concepts. Sure, some of it is simplified for the lay-reader, but anybody who isn't a total couch-potato is going to find the content interesting enough to set-out and search for details on their own. It isn't Johnson's goal to elaborate on some trivial and fragmentary specialty that only people with masters degrees and secured positions in academia could possibly enjoy or tolerate.

His goal is to show what emergence IS and why it is SO important, how vast the concepts are in their potential application in every imaginable field, and how elegant, simple, complex, chaotic, and BEAUTIFUL emergence IS !

And he does exactly this quite well. If you read this book and are not excited, you didn't get it. Read it again. And again. Look up the examples of emergence, and try to actually find your own examples of emergence in YOUR world, in YOUR daily experience. The enrichment you'll gain from it will be worth a lot more than any silly over-specialty in an obscure field of research that nobody has ever heard

Average customer rating:

Evolutionary Computer Music

Manufacturer: Springer
ProductGroup: Book
Binding: Paperback

General | Computers & Internet | Subjects | Books

General | Evolution | Science | Subjects | Books

Look Inside Computer Books | Trip | Specialty Stores | Books
ASIN: 1846285992

Book Description

The evolutionary computation approach to music is an exciting new development for composers and musicologists alike. For composers, it provides an innovative and natural means for generating musical ideas from a specifiable set of primitive components and processes. For musicologists, these techniques are used to model the cultural transmission and change of a population's body of musical ideas over time. In both cases, musical evolution can be guided by a variety of constraints and tendencies built into the system, such as realistic psychological factors that influence the way music is expressed, experienced, learned, stored, modified, and passed on among individuals.

This book discusses not only the applications of evolutionary computation to music, but also the tools needed to create and study such systems. These tools are drawn in part from research into the origins and evolution of biological organisms, ecologies, and cultural systems on the one hand, and from computer simulation methodologies on the other. They can be combined to create surrogate artificial worlds populated by interacting simulated organisms in which complex musical experiments can be performed that would otherwise be impossible.

This authoritative book, with contributions from experts from around the globe, demonstrates that evolutionary systems can be used to create and to study musical compositions and cultures in ways that have never before been achieved.

Eduardo Reck Miranda is a Professor in Computer Music at the University of Plymouth, UK, where he heads the Interdisciplinary Centre for Computer Music Research (ICCMR). He has recently been appointed the Edgard Varèse Guest Professor of Computer Music at the Technical University of Berlin.

Al Biles is a Professor and the Undergraduate Program Coordinator in the Department of Information Technology at the Rochester Institute of Technology in Rochester, New York. Between performances with GenJam over the last thirteen years, he has been active in helping establish information technology as a recognized academic discipline.

Ant Colony Optimization and Swarm Intelligence: 5th International Workshop, ANTS 2006, Brussels, Belgium, September 4-7, 2006, Proceedings (Lecture Notes in Computer Science)

Average customer rating:

Ant Colony Optimization and Swarm Intelligence: 5th International Workshop, ANTS 2006, Brussels, Belgium, September 4-7, 2006, Proceedings (Lecture Notes in Computer Science)

Manufacturer: Springer
ProductGroup: Book
Binding: Paperback

General | Computers & Internet | Subjects | Books

Look Inside Computer Books | Trip | Specialty Stores | Books

All Amazon Upgrade | Amazon Upgrade | Stores | Books

Computers & Internet | Amazon Upgrade | Stores | Books

Science | Amazon Upgrade | Stores | Books
ASIN: 3540384820

Book Description

This book constitutes the refereed proceedings of the 5th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2006, held in Brussels, Belgium, in September 2006.

The 27 revised full papers, 23 revised short papers, and 12 extended abstracts presented were carefully reviewed and selected from 115 submissions. The papers are devoted to theoretical and foundational aspects of ant algorithms, evolutionary optimization, ant colony optimization, and swarm intelligence and deal with a broad variety of optimization applications in networking, operations research, multiagent systems, robot systems, networking, etc.

Swarm Robotics: SAB 2004 International Workshop, Santa Monica, CA, USA, July 17, 2004, Revised Selected Papers (Lecture Notes in Computer Science)

Average customer rating:

Swarm Robotics: SAB 2004 International Workshop, Santa Monica, CA, USA, July 17, 2004, Revised Selected Papers (Lecture Notes in Computer Science)

Manufacturer: Springer
ProductGroup: Book
Binding: Paperback

General | Computers & Internet | Subjects | Books

Look Inside Computer Books | Trip | Specialty Stores | Books

All Amazon Upgrade | Amazon Upgrade | Stores | Books

Computers & Internet | Amazon Upgrade | Stores | Books

Engineering | Amazon Upgrade | Stores | Books

Professional & Technical | Amazon Upgrade | Stores | Books
Similar Items:

Multi-Robot Systems. From Swarms to Intelligent Automata, Volume III: Proceedings from the 2005 International Workshop on Multi-Robot Systems
Advanced Lectures on Machine Learning: Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures (Lecture Notes in Computer Science)
Leonardo's Lost Robots

ASIN: 3540242961

Book Description

Swarm robotics can be defined as the study of how a swarm of relatively simple physically embodied agents can be constructed to collectively accomplish tasks that are beyond the capabilities of a single one. Unlike other studies on multi-robot systems, swarm robotics emphasizes self-organization and emergence, while keeping in mind the issues of scalability and robustness. These emphases promote the use of relatively simple robots, equipped with localized sensing ability, scalable communication mechanisms, and the exploration of decentralized control strategies.

This state-of-the-art survey is the first book devoted to swarm robotics. It is based on the First International Workshop on Swarm Robotics held in Santa Monica, CA, USA in July 2004 as part of SAB 2004

Swarm Intelligence: From Natural to Artificial Systems (Santa Fe Institute Studies in the Sciences of Complexity Proceedings)

Average customer rating:

Impressively good, but not an introduction
A first milestone in the study of Swarm Intelligence
Algorithms inspired by social insects

Swarm Intelligence: From Natural to Artificial Systems (Santa Fe Institute Studies in the Sciences of Complexity Proceedings)
Eric Bonabeau , Marco Dorigo , and Guy Theraulaz
Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Paperback

Culture | Business & Culture | Computers & Internet | Subjects | Books

General | Computers & Internet | Subjects | Books

Look Inside Outdoors & Nature Books | Trip | Specialty Stores | Books

Qualifying Textbooks - Spring 2007 | Stores | Books
Similar Items:

Swarm Intelligence (The Morgan Kaufmann Series in Artificial Intelligence)
Ant Colony Optimization (Bradford Books)
Self-Organization in Biological Systems: (Princeton Studies in Complexity)
Fundamentals of Computational Swarm Intelligence
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence

ASIN: 0195131592

Book Description

Social insects--ants, bees, termites, and wasps--provide us with a powerful metaphor for creating decentralized problem-solving systems composed of simple interacting, and often mobile, agents. The emergent collective intelligence of social insects, swarm intelligence, lies not in complex individual capabilities but rather in networks of interactions among individuals and between individuals and their environment. The daily problems solved by a social insect colony--finding food, dividing labor among nestmates, building nests, responding to external challenges--have important counterparts in engineering and computer science. The collective behavior of social insects is not only decentralized, it is also flexible and robust: flexibility allows adaptation to changing environments, while robustness endows the colony with the ability to function even though some individuals may fail to perform their tasks. Swarm-intelligent artificial systems exhibit the same features and provide a useful approach to the tremendous increases in the amount of information and in the complexity of computer software. These systems replace an emphasis on control, preprogramming, and centralization with designs featuring autonomy, emergence, and distributed functioning. This unique book surveys several examples of swarm intelligence in social insects and describes how to design distributed algorithms, multiagent systems, and groups of robots modeled on social insects.

Customer Reviews:

Impressively good, but not an introduction.......2003-06-02

Compared to "Swarm intelligence" by James Kennedy, this one is not introductive but gets quite deep into the working of applying the "swarm" paradigm to optimization problems. I would rather recommmend for a person not used to meta-heuristics and optimization to first go to the book by Kennedy. Only if one is interested in using swarm for solving real optimization problems reading this one is a good idea.

This book illustrates several features of swarm behavior that can be leveraged for optimization. The authors writing style is equivalent to technical papers, so be prepared...this is no easy book.

A first milestone in the study of Swarm Intelligence.......2000-04-26

The book of Bonabeau, Dorigo, and Theraulaz is an excellent example of synergetic work between a physicist, an engineer, and a biologist. The Swarm Intelligence principles are first described and understood through models in natural systems and then translated in optimization algorithms, distributed algorithms for robotic control, and so on. Even if the book does not completely succeed in linking all three disciplines together - computer science, engineering, and biology - under a sound, common formalism, it represents an extremely up to date collection of work carried out worldwide in the field of Swarm Intelligence. I strongly believe in the future of this field and of its applications to problems hard to tackle with classical techniques. This book summarizes in an very equilibrated way the early, promising steps of Swarm Intelligence.

Algorithms inspired by social insects.......2000-02-14

A good synthesis of studies on swarm intelligence. It is fascinating to see how complex intelligent behavior can emerge from simple rules and numerous interactions without any plan or centralized coordination. Algorithms inspired by social insects can be applied in many disciplines. It is a book easy to understand but difficult to read through for those who don't love algorithms. It includes a very neat introduction to the subject with many clear examples. Everyone should read that part and at least throw a glance at the rest of the book.

Multi-Robot Systems. From Swarms to Intelligent Automata, Volume III: Proceedings from the 2005 International Workshop on Multi-Robot Systems

Average customer rating:

Multi-Robot Systems. From Swarms to Intelligent Automata, Volume III: Proceedings from the 2005 International Workshop on Multi-Robot Systems

Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

General | Engineering | Professional & Technical | Subjects | Books

General | Science | Subjects | Books

General | Arts & Photography | Subjects | Books

All Amazon Upgrade | Amazon Upgrade | Stores | Books

Arts & Photography | Amazon Upgrade | Stores | Books

Computers & Internet | Amazon Upgrade | Stores | Books

Engineering | Amazon Upgrade | Stores | Books

Professional & Technical | Amazon Upgrade | Stores | Books

Science | Amazon Upgrade | Stores | Books

Qualifying Textbooks - Spring 2007 | Stores | Books
Similar Items:

Swarm Robotics: SAB 2004 International Workshop, Santa Monica, CA, USA, July 17, 2004, Revised Selected Papers (Lecture Notes in Computer Science)

ASIN: 1402033885

Book Description

This proceedings volume documents recent cutting-edge developments in multi-robot systems research. This volume is the result of the Third International workshop on Multi-Robot Systems that was held in March 2005 at the Naval Research Laboratory in Washington, D.C. This workshop brought together top researchers working in areas relevant to designing teams of autonomous vehicles, including robots and unmanned ground, air, surface, and undersea vehicles.

The workshop focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. A broad range of applications of this technology are presented in this volume, including UCAVS (Unmanned Combat Air Vehicles), micro-air vehicles, UUVs (Unmanned Underwater Vehicles), UGVs (Unmanned Ground vehicles), planetary exploration, assembly in space, clean-up, and urban search and rescue.

This proceedings volume represents the contributions of the top researchers in this field and serves as a valuable tool for professionals in this interdisciplinary field.

Swarm Intelligence in Data Mining (Studies in Computational Intelligence)

Average customer rating:

Swarm Intelligence in Data Mining (Studies in Computational Intelligence)

Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

General | Computers & Internet | Subjects | Books

General | Engineering | Professional & Technical | Subjects | Books

General | Mathematics | Science | Subjects | Books
ASIN: 3540349553

Book Description

Swarm Intelligence is an innovative distributed intelligent paradigm for solving optimization problems that originally took its inspiration from the biological examples by swarming, flocking and herding phenomena in vertebrates. Data Mining is an analytic process designed to explore large amounts of data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data.

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. This volume comprises of 11 chapters including an introductory chapter giving the fundamental definitions and some important research challenges.

Important features include the detailed overview of the various swarm intelligence and data mining paradigms, excellent coverage of timely, advanced data mining topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field. Academics, scientists as well as engineers engaged in research, development and application of optimization techniques and data mining will find the comprehensive coverage of this book invaluable.

Books:

Books