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Complexity: A Guided Tour explained Complexity: A Guided Tour, review Complexity: A Guided Tour, trailer Complexity: A Guided Tour, box office Complexity: A Guided Tour, analysis Complexity: A Guided Tour, Complexity: A Guided Tour d583 What Enables Individually Simple Insects Like Ants To Act With Such Precision And Purpose As A Group How Do Trillions Of Neurons Produce Something As Extraordinarily Complex As Consciousness In This Remarkably Clear And Companionable Book, Leading Complex Systems Scientist Melanie Mitchell Provides An Intimate Tour Of The Sciences Of Complexity, A Broad Set Of Efforts That Seek To Explain How Large Scale Complex, Organized, And Adaptive Behavior Can Emerge From Simple Interactions Among Myriad Individuals Based On Her Work At The Santa Fe Institute And Drawing On Its Interdisciplinary Strategies, Mitchell Brings Clarity To The Workings Of Complexity Across A Broad Range Of Biological, Technological, And Social Phenomena, Seeking Out The General Principles Or Laws That Apply To All Of Them Richly Illustrated, Complexity A Guided Tour Winner Of The Phi Beta Kappa Book Award In Science Offers A Wide Ranging Overview Of The Ideas Underlying Complex Systems Science, The Current Research At The Forefront Of This Field, And The Prospects For Its Contribution To Solving Some Of The Most Important Scientific Questions Of Our Time

  • Hardcover
  • 349 pages
  • Complexity: A Guided Tour
  • Melanie Mitchell
  • English
  • 09 March 2017
  • 9780195124415

About the Author: Melanie Mitchell

Melanie Mitchell is a professor of computer science at Portland State University She has worked at the Santa Fe Institute and Los Alamos National Laboratory Her major work has been in the areas of analogical reasoning, complex systems, genetic algorithms and cellular automata, and her publications in those fields are frequently cited.She received her PhD in 1990 from the University o



10 thoughts on “Complexity: A Guided Tour

  1. says:

    A very informative and easy to read book on complexity and complex systems Although I learned a lot about the computer science and biological perspectives to complexity and I enjoyed it, but I think the focus on these perspectives is too much and very detailed which leaves very little space for equally interesting perspectives, such as socio economic approach, or the so called complex adaptive systems approach Therefore, the book on complex adaptive systems by Miller and Page might be complementary to this book, if we share the same concerns .

  2. says:

    Nice introductory book about a number of topics in the emerging field of complexity Complexity is a very broad subject, still under significant theoretical development, that touches upon many scientific fields such as biology, computer sciences, information theory, genetics, network theory etc, so this book occasionally feels a bit disjointed which is unavoidable considering the nature of the subject it must be said however that the author manages to convey, in a clear manner, the main features of this fascinating field of research.Fascinating topics such as chaos theory with a concise but very nice explanation of the logistic map example, which is a classic introductory subject , are competently treated by the author, and with enthusiasm and clarity In particular, the author explains clearly how apparent randomness and chaotic behavior can arise even from very simple deterministic systems Fundamental concepts are also addressed in a lucid way starting from the concept of information, down to the very concept of complexity considered from a computational, entropic, fractal, logical depth, thermodynamical, and statistical perspectives Fascinating examples and studies of complexity and even of life like behavior arising as emergent phenomena in structures as conceptually simple as cellular automata even a simple two state cellular automaton has been demonstrated capable of universal computation , provide real food for thought The technique of genetic algorithms provides amazing results and demonstrate how complex solutions and intelligent behavior can emerge even from the simplest set of rules The relationship between computability and natural structures is also explored, with fascinating insights The idea of life as essentially an information processing phenomenon is quite appealing too.Overall, the author explains very effectively, and convincingly, the great importance of thinking about complex systems in terms of nonlinearity, decentralized control, distributed feedback mechanisms, controlled randomness and statistical representation of information, and that a simplistic reductionist approach according too which the global behavior of a system can be simply deduced from knowledge of the individual components is in many case totally inadequate This is an enjoyable book for anyone who is interested in an introduction to the study of complexity, especially if you have a background in computer sciences.

  3. says:

    I actually brought this book by accident, thinking it was strictly about computation complexity theory Instead, it turned out be about the newish science of Complexity Theory What a happy accident this is currently tied for most informative and interesting book I ve read all year The scope of this book is broad, and covers a plethora of topics evolution, computational complexity, turing machines and definite procedures, molecular genetics, immunology, neurology, graph and network theory, power laws, fractal geometry, information theory and thermodynamics, to give an incomplete list, all as seen through the lens of complexity theory If you re already familiar with most of these topics, you ll still find new information here, and some of the history given for these fields is, by itself, worth the price of purchase If you ve ever seen references to computation and information in physics and biology, but had only the vaguest notion of what they were getting at, this book will explain it for you in a clear and engaging fashion Engaging, easy to read, and consistently mind blowing I can honestly say I ve acquired a new interest, and that I m better informed about a number of topics than when I started, thanks to reading this book.

  4. says:

    Through no fault of its own, I did not enjoy Complexity A Guided Tour The field of complexity has long interested me in the abstract, but I found this introductory text to be way over my head with respect to content I was able to follow for the first 100 pages or so but, pun intended, it simply became too complex for me to handle I think if I had a background in computer science or theoretical mathematics I could have found to appreciate, but this is not to say that Melanie Mitchell s writing is obtuse or frustrating, rather it is the concepts that are puzzling I also found the passages which related complexity to genetics and biochemistry most intriguing as they planted the notions in the fertile soil of my background wow, that is just as terrible to read as I thought it would be In any case, this may be a tremendous book, but it is leagues above and beyond my understanding.

  5. says:

    This is handily one of the best, most interesting, and to me at least the most useful popularly written science books I ve yet to come across Most popular science books usually bore me to tears and end up being only pedantic for their historical backgrounds, but this one is very succinct with some interesting viewpoints some of which I agree with and some of which my intuition says are terribly wrong on the overall structure presented For those interested in a general and easily readable high level overview of some of the areas of research I ve been interested in information theory, thermodynamics, entropy, microbiology, evolution, genetics, along with computation, dynamics, chaos, complexity, genetic algorithms, cellular automata, etc for the past two decades, this is really a lovely and thought provoking book At the start I was disappointed that there were almost no equations in the book to speak of and perhaps this is why I had purchased it when it came out and it s subsequently been sitting on my shelf for so long The other factor that prevented me from reading it was the depth and breadth of other technical material I ve read which covers the majority of topics in the book I ultimately found myself not minding so much that there weren t any many supporting equations aside from a few hidden in the notes at the end of the text in most part because Dr Mitchell does a fantastic job of pointing out some great subtleties within the various subjects which comprise the broader concept of complexity which one generally would take several years to come to on one s own and at far greater expense of their time Here she provides a much stronger picture of the overall subjects covered and this far outweighed the lack of specificity I honestly wished I had read the book when it was released and it may have helped me to me specific in my own research Fortunately she does bring up several areas I will need to delve deeply into and raised several questions which will significantly inform my future work.In general, I wish there were references I hadn t read or been aware of yet, but towards the end there were a handful of topics relating to fractals, chaos, computer science, and cellular automata which I have been either ignorant of or which are further down my reading lists and may need to move closer to the top I look forward to delving into many of these shortly As a simple example, I ve seen Zipf s law separately from the perspectives of information theory, linguistics, and even evolution, but this is the first time I ve seen it related to power laws and fractals.I definitely appreciated the fact that Dr Mitchell took the time to point out her own personal feelings on several topics and so that she explicitly pointed them out as her own gut instincts instead of mentioning them passingly as if they were provable science which is what far too many other authors would have likely done There are many viewpoints she takes which I certainly don t agree with, but I suspect that it s because I m coming at things from the viewpoint of an electrical engineer with a stronger background in information theory and microbiology while hers is closer to that of computer science She does mention that her undergraduate background was in mathematics, but I m curious what areas she specifically studied to have a better understanding of her specific viewpoints.Her final chapter looking at some of the pros and cons of the topic s was very welcome, particularly in light of previous philosophic attempts like cybernetics and general systems theory which I also think failed because of their lack of specificity These caveats certainly help to place the scientific philosophy of complexity into a much larger context I will generally heartily agree with her viewpoint and that of others that there needs to be a rigorous mathematical theory underpinning the overall effort I m sure we re all wondering Where is our Newton or to use her clever aphorism that we re waiting for Carnot Sounds like it should be a Tom Stoppard play title, doesn t it I might question her brief inclusion of her own Ph.D thesis work in the text, but it did actually provide a nice specific and self contained example within the broader context and also helped to tie several of the chapters together My one slight criticism of the work would be the lack of better footnoting within the text Though many feel that footnote numbers within the text or inclusion at the bottom of the pages detracts from the flow of the work, I found myself wishing that she had done so here, particularly as I m one of the few who actually cares about the footnotes and wants to know the specific references as I read I hope that Oxford eventually publishes an e book version that includes cross linked footnotes in the future for the benefit of others.I can heartily recommend this book to any fan of science, but I would specifically recommend it to any undergraduate science or engineering major who is unsure of what they d specifically like to study and might need some interesting areas to take a look at I will mention that one of the tough parts of the concept of complexity is that it is so broad and general that it encompasses over a dozen other fields of study each of which one could get a Ph.D in without completely knowing the full depth of just one of them much less the full depth of all of them The book is so well written that I d even recommend it to senior researchers in any of the above mentioned fields as it is certainly sure to provide not only some excellent overview history of each, but it is sure to bring up questions and thoughts that they ll want to include in their future researches in their own specific sub areas of expertise.

  6. says:

    If you have a background in biology or computer science you might find that you already much of the stuff that is discussed in this book, but as it s a guided tour and not the expert s compendium to complexity that s than okay If you want to learn about the investigation of complexity without having too much knowledge about it you will get a great overview that is pretty easy to understand imho For me it was a quick, fun read that put the different topics together quite nicely And seriously, how couldn t I love a book that brings together von Neumann, Szilard, Turing, RA Fisher, Sewall Wright, JBS Haldane, Robert Axelrod and Stephen J Gould lots or evolutionary biology population genetics porn there among many others If not too many of those names ring a bell for you that s a great chance to learn about some of the people whom I d count to the greatest minds of the 20th century.

  7. says:

    Maybe I should not blame the messenger for delivering the news that measuring or even defining complexity is complex, and there are multiple conflicting ways to try and do that So the issues I hoped would be addressed, such as a discussion of emergent properties that goes beyond vague hand waving, were not addressed, perhaps because they can t be There are some worthwhile chapters giving examples on the emergence of complex adaptive behaviour from a large number of simple but connected components We learn about ant colonies, evolution, the immune system and the human brain We can see what happens, but I guess the why, the underlying principles, are only there in a shadowy form at present.Given the background of the author, I should not be surprised that the book quickly moved on to artificial intelligence rather than what was advertised in the title We even get an entire chapter devoted to her thesis It was all reasonably interesting, but it felt to me like a bit of a bait and switch.Even in the bait section, the chapter on entropy replicates the popular confusion on this topic We get the entropy as disorder interpretation, complete with the messy room analogy, then the Boltzmann definition as the set of all possible microstates, then back to disorder In the middle of it all, she really annoyed me with this throwaway line The relationship between information and physics became clear only in the twentieth century, beginning with the discovery that the observer plays a key role in quantum mechanics No, that is not a discovery it is a hotly contested metaphysical assumption.I have to wonder how much I should trust all the other information from outside her field, such as the immune system or the brain, when she can t coherently explain basic physics.Generally, I thought the book was an interesting and pleasant read To be fair, the title only promised a guided tour, and that is what we got.

  8. says:

    Very nice introduction to complex systems research complexity in general.This book made me flash back to my Computer Science studies, but in a very good way It touches on theoretical foundations Turing Machines, decidability, halting problem, genetic algorithms, fractals, laws of thermodynamics, but the writing is very fluent and approachable.The author introduced me to the field of Network Theory, a science that builds on graph theory It leads to interesting questions and answers like Why is the world wide web so resilient or How can we structure an organization to become resilient Good stuff What I really like about the book is the way the author links all these topics Before reading this, I never thought about the similarities between, say, the way the immune system works, how ant colonies forage for food and how a genetic algorithm looks for an optimal solution.If you re not afraid of a bit of math in your books and want an overview on topics like What is complexity How do we measure and or compare complexity How does nature compute Can we extract common principles from complex systems as different as ant colonies and the global economy Then this book is for you

  9. says:

    Complexity is an emerging multidisciplinary branch of science The origins of this new branch of science is in the realm of biologic ecosystems such as ant colonies in which a network of relatively simply programmed building block agents i.e ants seems in net to exhibit a certain level of environmental ecosystem cognition i.e complexity This cognition supports adaptation, and hence the term Complex Adaptive Systems is often used inclusive at the apex of human brain and global internet systems The author Melanie Mitchell has a background in computer science, which is indicative of the multidisciplinary underpinnings of complexity science The academic focus for complexity science comes from the Santa Fe Institute which was created by researchers from nearby Los Alamos Labs to foster muiltidisciplinary connections, primarily among academics.The author uses a broad brush that is successful in presenting what can be difficult concepts to a broad audience At the same time this is an overview which progresses in later chapters towards the cutting edge topic of network thinking Network thinking extends and broadens the concept of ecosystem beyond what most people think of as an ecosystem which is biologic, to for example physics where there is an ecosystem of networked subatomic particles making up matter This brings us to the 800 pound gorilla in the science room, i.e the recent inferences of mysterious dark matter and dark energy which make up some 95.1% of the universe and are dark because they cannot be observed The 800 pound gorilla in the science room wrestles with the age old scientific paradigm of making predictions and verifying with observation Thus progress on dark matter and dark energy will likely come from a physics that has a strong dose of network thinking supporting inference, and this book is a good place to start.

  10. says:

    How does an ant colony organize itself How does the immune system work What is the similarity between the world wide web and your brain If you have pondered any of these questions, Complexity A Guided Tour is just the book for you.1Any computer scientist who graduated in the last ten or so years would have covered some of the topics in Melanie Mitchell s Complexity A Guided Tour , and would have probably wished that they had Ms Mitchell as a lecturer Ms Mitchell is clearly passionate about her subject Her book covers a number of topics in the emerging field of Complexity such as emergent behaviour, computer science, genetic algorithms, network theory, etc Ms Mitchell does not get too technical, but still manages to convey the key ideas with clarity Her explanation of Turing s universal computer and the Halting Problem are great examples of explaining a complex topic in an approachable manner I enjoyed the chapters on genetic algorithms, computability and cellular automata I wish she had gone into a bit detail on Network theory.This is an enjoyable book for anyone who is interested in computer science or is mathematically inclined Those without a background in computer science may find it a bit of a slog Ms Mitchell also provides generous notes and references for further study I enjoyed this book very much.

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