Swarm Intelligence

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

This book is fantastic!It consists of two parts. In the first part, the main ideas behind Evolutionary Computation and social behavior are tangibly described. A brief review of the most known evolutionary computation algorithms is provided and social behavior modeling issues are reported to prepare the reader for the second part. The second part is devoted to the Particle Swarm Optimization (PSO) algorithm and its applications. Both binary and real variants of PSO are considered and several theoretical aspects are investigated. The book closes reporting several applications and insightful conclusions.Perhaps the best book on collective intelligence and PSO.

I concur with the other postive reviews of this book as a very interesting application of multiple disciplines to the field of evolutionary computing and would also add that it provides some very palatable explanations of other concepts like classic genetic algorithms, including supporting maths (which, as someone without a terribly strong background in math, I really appreciated) as well as some good heuristics for use in real systems.Where other books might treat you to a cursory introduction and then start speaking to you as if you were a research peer (which *can* stimulate the reader to higher knowledge, but often alienates as well), this one ramps up to it's more interesting ideas, ensuring you are not left to have to research elsewhere simply to understand it's contents and implications. Even if you are experienced in any of the fields covered by this book, I doubt the introductory material will bore you (or it's easy enough to skim). Certainly the challenging conclusions will not!Good work, Mr. Kennedy!

Besides its excellent presentation and highly methodological structure, this book describes the anti-individualistic point of view of "intelligence". The point is about showing how problem solving and evolution can be thought as mainly driven by the way components interact, not through some notion of an individual's "intelligence" that would be the property of the person (or any "entity") which is solving a problem, and not the result of the contacts with his (its) environment.If you like books providing a different point of view of AI this is the book you are looking for...in addition it is entertaining and easily readable.

The concepts of intelligence and thought have been the source of speculation and wonder since the dawn of mankind (or is it personkind?). With the advent of modern computers, computational systems were developed that were capable of some degree of artificial intelligence. However, the conceptual frameworks were difficult to understand and were even harder to implement. In this book, the authors lead us through a wonderful journey of the foundations of our thoughts, intelligence and psychology all the while taking us on a tour of the new field of evolutionary computing and its newest member - Swarm Intelligence. The authors begin with an excellent overview of the text that helps set the tone for the reader. This is probably one of the few times where reading the introduction actually enhances the enjoyment of the book. In the first several chapters, we are introduced to models and concepts of life, intelligent thought and computational intelligence. In so doing, great care has been taken to represent the diverse and divergent opinions on these subjects. The second section of the book is dedicated to explaining the concepts involved with the particle swarm and collective intelligence. Included in this section is a discussion of the partical swarm in relation to other techniques of evolutionary computing. Several "real-world" applications have been included and help clarify the utility of particle swarm in evolutionary computing.Overall, the book is well written, comprehensive and fun for anyone interested in intelligence or evolutionary computing. The variety of viewpoints only serves to make the book more engaging and superb reading; even for those who have little programming background. I HIGHLY RECOMMEND IT!!