Simply Complexity: A Clear Guide to Complexity Theory

by Neil Johnson

What do traffic jams, stock market crashes, and wars have in common? They are all explained using complexity, an unsolved puzzle that many researchers believe is the key to predicting – and ultimately solving—everything from terrorist attacks and pandemic viruses right down to rush hour traffic congestion.

Complexity is considered by many to be the single most important scientific development since general relativity and it promises to make sense of no less than the very heart of the Universe. Using it, scientists can find order emerging from seemingly random interactions of all kinds, from something as simple as flipping coins through to more challenging problems such as the patterns in modern jazz, the growth of cancer tumours, and predicting shopping habits.

Genres: Science, Nonfiction, Economics, Mathematics, Physics, Philosophy, Sociology

256 pages, Paperback

First published May 24, 2007

Reviews

[Alborz Baghipour · Rating 1 out of 5]

متاسفانه ترجمه کتاب روان نیست و در آن بی سلیقگی زیاد شده. از ترجمه اشتباه عنوان کتاب بگیرید تا عدم آشنایی مترجم به برخی اصطلاحات تخصصی
حوزه پیچیدگی در متن، همه وهمه اذیت کننده اند
ناشر در اقدامی عجیب بر روی جلد کتاب از مترجم با نام دکتر رحیم کوشش نام برده و درکنار آن با همان اندازه فونت نوشته: نویسنده نیل جانسون! آخر اگر به مدرک تحصیلی باشد که نیل جانسون هم دکتر است، تازه در هاروارد هم درس خوانده
اما از همه اینها که بگذریم خود کتاب هم حرف زیادی برای گفتن ندارد. تنها می توانید به چشم یک مقدمه ی بسیار ابتدایی در رابطه با علم پیچیدگی به آن نگاه کنید. کتاب پر است از تکرار مکررات و شرح وبسط موضوعات واضح

[Victoria Zabuzova · Rating 2 out of 5]

First 4 Chapters would be really good for those, who genuinely believe in lean social order, simple solutions for complex issues or overusing words like 'everyone' and 'nobody'. As for people with minimal social studies or market research background this book, I believe, will be somewhat trivial.

[Дмитро Булах · Rating 3 out of 5]

The field is interesting, the book is quite trivial. My feeling was that is over-explaining but lacks some deeper view on the math behind the phenomena
You could definitely skip if you already has a some experience on fractal or quantum math

[Samuel · Rating 4 out of 5]

As someone who recently got into Complexity Science, I found this book to be a brilliant introduction.

Neil writes with great simplicity, depicting the intuition behind complex systems well.

One may be annoyed about the lack of mathematical rigour in this book. But he did make it apparent that he wanted the subject to be so understandable, even his own child understood it.

The examples he uses to explain Complex Systems are great as well. He tends to thrive in the explanation of human systems far better than he does in more, technical areas. And at times when he does delve technically, one tends to see the repetition of analogies to Financial markets a bit too frequently.

That said, albeit written a while ago, this book may become the sort of foundational book many students will be reading about in classes of the future.

[Mukesh Jha · Rating 5 out of 5]

Wonderful book.
Gave insight about Complexity and how my research is broadly related to it ;)

[Geert Hofman · Rating 3 out of 5]

In dit boek probeert de auteur zo eenvoudig mogelijk uit te leggen wat complexiteit is, waarom complexiteit zo belangrijk is, welke praktische fenomenen hier allemaal mee te maken hebben en hoe deze fenomenen ook in ons gewone dagelijkse leven opduiken. Het is duidelijk dat de auteur weet waarover hij spreekt, maar de manier waarop hij de dingen probeert te vereenvoudigen komt heel vaak paternalistisch over. Hij neemt je bij het handje zoals je dat zou doen bij een niet al te intelligente student. Tegelijk verwijst hij ook naar actuele publicaties over complexiteitsfenomenen, wat boeiend is, maar opnieuw doet hij dat op zo'n manier dat je het gevoel krijgt dat je dankbaar moet zijn voor het feit dat hij zijn intiemste vrienden, die behoren tot het kruim van de wetenschap, met je wil delen. Vooral het voortdurend gebruik van de voornamen van de onderzoekers in kwestie is behoorlijk vervelend.

Verschillende toepassingsdomeinen komen aan bod, zowel op het gebied van menselijke relaties (barbezoek, verkeer, oorlog en andere conflictsituaties) als op het vlak van het positief wetenschappelijk (biologie, scheikunde, fysica). Het mag duidelijk zijn dat hij zelf vooral op deze laatste terreinen zeer bedreven is. Al bij al toch wel een boeiende introductie in het domein van de complexiteit.

Het boek sluit af met een aantal interessante referentie naar websites, andere boeken en gratis downloadbare artikels.

[Massimo Curatella · Rating 4 out of 5]

Although dealing with difficult topics for the non-scientist the author uses a rather affordable style.
There is a richness of examples offering a real effort to make hard topics to be comprehensible and it works most of the times (Quantum theory is still something I have to dig...).
There is a fair amount of redundancy in the writing style and in the repetition of most of the concept exposes. While I usually find it annoying, in this case, up to a certain degree, is helping to learn.
Maybe it's not suitable as an introduction to Complexity Science from scratch but is certainly a useful tool in the hand of who is curious about Systems Thinking, Systems Theory and Complex Networks and wants to learn more.

[Wordwizard · Rating 3 out of 5]

Interesting. Probably a good grounding in complexity. Author cannot punctuate.

[Brandon · Rating 2 out of 5]

I read this book because the author of 1177 BC, a book on the Bronze Age collapse, cited this book / complexity theory as a possible explanation of the Bronze Age collapse. I should have known better, since 1177 BC was at best a mediocre book. I've enjoyed a variety of doorstopper tomes over the years, but this 264-page featherweight was an excruciating read. It took me a few months to claw my way through it. Not because it was technical but because it was bad. Most of the book is filled with the author talking about how "complexity will likely become the science of interest for future generations," "the Science of all Sciences," and citing examples of things that are complex but not explaining anything beyond the depth of an IFLScience article.

First of all, what is complexity theory? "The study of phenomena which emerge from a collection of interacting objects" - typically on the scale of 100-1000 agents. Two features of complex systems are competition between agents for a limited resource (money, time, power, etc), and feedback (the agents can remember their past interactions, which can inform their future behavior). Creating simple models of the dynamics/behavior of many agents means that agent behavior can be summarized through the values of the parameters of the model. The effects these parameters describe are called "emergent phenomena".

I think the most insightful thing that Johnson says is that in complex systems, "anything can happen - and if you wait long enough, it generally will" (including catastrophic failure). I hate the book but, I love this statement. It's an underacknowledged law of nature that sadly has dire consequences for humanity. In terms of the Bronze Age, it honestly probably did guarantee that the intricate network of competing, intertwined states in the Bronze Age Near East was doomed. For our own present day, it means that our world with multiple competing nuclear powers is almost certainly doomed to nuclear catastrophe (unfortunately, Johnson doesn't talk about our society's network of nuclear superpowers, even though it's probably the most consequential complex system in human history). More prosaically, as a roboticist, it is humbling to know that the systems I work on are doomed to (occasional) failure, although maybe it's also a good excuse (at least for myself... not for my bosses). I wish that Johnson had spent more time explaining why this is the case. He mostly just says it's because complex systems are far from equilibria - I guess that random collapses to equilibrium are what characterize system failures. But it's unclear to me what about complex systems guarantees occasional reversions to equilibrium states.

The cringiest part of the book is when Johnson says, "emergent phenomena typically arise in the absence of any sort of 'invisble hand' or central controller." Throughout the book, he refers to Adam Smith's "invisible hand" as a "central controller", which is literally the OPPOSITE of what the invisible hand is. That's why the hand is INVISIBLE. "[A complex system] has no 'invisible hand' such as an orchestral conductor..." "Emergent phenomena can arise without the need for an 'invisible hand'. Instead, the collection of objects is able to self-organize..." He uses "invisible hand" completely incorrectly 14 times, causing me to react with an invisible face palm every time.

I learned a few interesting things from the book. One feature of complex systems is that they can shift between order (equilibrium) and disorder (out of equilibrium) via their own internal dynamics, such as how traffic networks can go from free flowing (disordered) to jammed (ordered), and how stock markets can go from normal (disordered) to crashing (ordered). Another interesting thing is that the behavior of complex systems often exhibits fractal-like behavior. For example, if you label days the stock market goes up with a 1 and down with a 0, the sequence of 1s and 0s is a fractal that can be described with a fractional dimension (how much order/disorder the fractal displays). Lastly, Johnson talks about some research on a simple system that shows how it's possible for the agents of complex systems to converge to polarized/divergent policies (crowds and anticrowds) - for example, stock traders who participate in a bull run versus those who sit it out. In such situations, there is often very little middle ground between the two that makes sense to the agents' best interests. And now that you've read this last paragraph, you probably don't need to read this book anymore.

[Gordon · Rating 4 out of 5]

written 8/9/2012 on a different space....
Disclaimer: This is as expected, incomplete and loosely written – but written none-the-less. I struggle with the obvious plagiarism in certain snippets – but wonder, who is this for anyway? Consider it my personal collection of quotes and ideas that are meaningful to me, and thoughts of my own.
Overview
What is complexity? I have been saying to myself and anyone else who would listen that I am primarily interested in solving, or at least working on complex problems. (trivial, mundane, or repetitive tasks are not my bowl of soup). Things that stir my interest are global issues in environmental sustainability, political, economic, social, human behavior and interaction, aiming to achieving a peaceful, tolerant, and sustainable world order. Issues where there are many people or system actors involved, making decisions based on either incomplete or imperfect information, sometimes with opposing goals, or at best not fully understood relationships, outcomes, nor consequences. How do we move an amorphous blob of Jello from point A to point B as efficiently as possible without killing each other? This problem inspires an understanding and respect for a view that we have to expect a degree of disorder, and sometimes seeming chaos as long as, on average, we can measure progress in the direction toward the goal sought.

Needless to say, my personal view of complexity is pretty broad and imprecise, perhaps as it should be.

Neil Johnson’s book obviously should provide a considerably stronger definition and structure to our concept of complexity. And it does. Neil starts by suggesting a distinction between what is complex as opposed to simply complicated. To condense what takes several chapters in Simply Complexity to describe a formal definition of complexity, I offer the following snippets:

Complexity Science: The study of phenomena that emerge from a collection of interacting objects (a crowd) often competing for a limited resource. Such phenomena, often surprising, sometimes catastrophic, emerge in the absence of any central controller or coordinator. The goal of Complexity Science is to answer whether these systems and their behavior are predictable and controllable so as to manage to avoid the catastrophes and optimize the desired outcomes.

Key components of Complexity:
The system contains a collection of many interacting objects.
These objects’ behavior is affected by memory, or feedback
The objects can adapt their strategies according to their history
The system is typically open – to external inputs and influences by is environment
The system appears to be alive – evolving in non-trivial ways
The system exhibits emerging phenomena that are generally surprising and sometimes extreme
The emergent phenomena arise in the absence of any invisible hand or central controller
The system exhibits a complicated mix of ordered and disordered behavior.

One key attribute of complex systems: In opposition to the second law of thermodynamics, Entropy – the tendency for all matter to move toward dis-order, rather than order, is that in a complex system order may arise out of disorder without central control.

A system with a collection of interacting agents (people or objects) (a crowd) that make decisions based on feedback (memory and information), often competing for some limited resource, resulting in emergent behavior that may be observed within a range of disorder and order.

Snippets:
P28. Collections of objects in the absence of any feedback tend to become increasingly disordered.
P28. The amount of disorder in a closed system increases over time
P28. Fortunately truly closed systems are very rare. In fact the Universe is the only truly closed system we know of.

Chaos, Complexity and Fractals.
Probably the most interesting, novel, concept to me in this read is a closer understanding of Chaos and fractals that I haven’t previously digested. In my own summary, it seems Chaos may be observed in a complex system whose output time series merely appears random for the moment, yet is based on the structure and dynamics of the complex system. A complex system can exhibit both ordered and chaotic behavior and anything between and the transition between order and chaos is itself complex.

Fractal: Well, more interesting is that chaos is really a periodic pattern in the time series output of a complex system in which the period is so long it seems to never repeat. Between linear, ordered systems and chaos is a family of dynamics called fractals that again are simply periodic patterns with, well, less than infintite period… The book does a nice job showing the broken pattern of resultant output numbers that can occur, illustrating that in certain fractal outputs the available numbers in the output series are elements of broken line segments, with an infinite number of possible valid values, and an infinite number of gaps, not to be observed in the output time-series. A nice paragraph to steal: “scientists refer to a point as zero dimensional, a line as being one-dimensional, and a flat sheet, or plane as two-dimensional. The fine dust of points which looks like a solid line but isn’t, is effectively between a point and a line – hence it is between a zero and a one-dimensional object. As we know a number between zero and one is a fraction – hence the fine dust of points has a fractional dimension. For this reason, scientists call an object such as this fine dust of points a fractal.”

The emergence of fractals is a common occurrence in complex systems.

As I skim the book for quotable gems, I recognize, as usual, that a re-read wouldn’t hurt. There always seems to be more in it and to it than the first pass digests. But alas, I am always in a rush to get onto the next project… and can only afford some final impressions.

The book provides numerous interesting and varied examples of research that has modeled complex systems and can demonstrate similar dynamics in their outputs as found in real world systems. Observations range from the shapes of coast lines, mountain ranges, biological growth and decay, and financial market price performance. I do recognize that there is value in modeling such dynamics and the ability in using these models to predict potential future behavior, though I am skeptical in several cases that, without taking real world input into consideration in the model, such as real, time based externalities of a global market events, while the model can predict the near term possible outcomes, it seems impossible to predict the Actual outcomes with a high degree of confidence. Modeling dynamics is not the same as modeling true value and actual expected behavior.

On System modeling – as I read this, I am imagining how I would model certain of these systems. Thinking these would be modeled as large collections of individual objects with certain attributes, relationships and behaviors. I’d write a event-time driven simulation to generate the time series output of the collective behaviors of interest. In reading the book, however, I get a different sense that the current research is resorting to aggregate models of the collective behaviors rather than individual objects. Again, it is likely appropriate and valuable, but assumes, which I think they justify, that such complex systems can be modeled as normally distributed agents.
Conclusion / Final Verdict / Recommendation:
In his introduction, Neil outlines 6 plus goals he wishes to accomplish with the book.I think he accomplishes all of his wishes to a fair degree. I certainly have come away with a comfortable sense of complexity theory and my mind is sowed with new seeds to be nurtured and hopefully harvested in future thoughts.
While accessible to the general reader and enlightening in the varieties of problems Complexity theory can contribute to, I think the book has a couple minor setbacks: redundancy, or seeming repetitiveness, and a little too superficial in seeming to use this book to promote the works of the various researchers. Both of these criticisms are probably too harsh, or should I say, really need to be considered very minor. The redundancy between topics and research areas is probably both very natural, and intentional in the structure of the book to show the commonality and inter-relatedness between vastly different problems, similarly modeled as complex systems. My criticism toward the survey of research and researchers too is probably slightly unfair as I recognize the value in giving due credit and respect to the contributors in the field, as well as the need to use such an approach in an introductory survey. I’m just saying it seemed to me these two issues created some drag in the flow and progress of the read

[Jung]

So, you’ve just learned how to simplify your life: from reducing the time you spend online to ways in which you can untangle your mind. But what of complexity? Just because you learn to simplify your personal relationship with the world, that doesn’t mean complex phenomena will just go away.

Complexity surrounds us: from traffic jams to the unpredictable mood-swings of the financial markets. In response, scientists are developing a new branch of science called complexity theory, which teaches us to recognize the patterns in these different situations. In this book, Neil Johnson elucidates all of the main points of this emerging discipline. So what better way to get up to speed than with the book Simply Complexity.

---

We must be selective about the knowledge we consume.

The next time you use the internet, check your browser. How many tabs do you have open? Chances are, it’ll be more than one. And it’s likely that many of those tabs will be half-absorbed news stories or opinion pieces saved for a later date.

All across the world, we’re consuming more information than we can usefully store in our heads. We’re becoming engorged on the stuff. So much so, that social scientists have started using a new word to describe the state: infobesity. In fact, overloading the working memory like this can contribute to mental decline.

Pretty worrying, right? So what can we do?

When it comes to consuming news online, one thing is crucial: it’s important to use reliable sources to avoid wasting time with outright falsehoods and conspiracies. Simple enough, right? So, take your favorite news website. Does it have a history of mostly getting things right? Or is its past littered with exaggerations and lies? If it’s the latter, you can cut it from your “information diet.”

Curating your sources is a good habit in general. You should aim to create a kind of Knowledge Dashboard where you keep your most trusted and relevant sources. That way, you can quickly get up to date with opinions you trust without becoming lost on the internet.

As with news, you can curate the way you consume other types of content online. Perhaps you have a favorite fashion magazine? Or a preferred market analysis website? Or even a good place to check the weather?

In addition to prioritizing quality information, it’s good to remember that not everything is about cramming our heads with facts. In reality, we neglect other important, non-online skills in our daily internet binges. These are “soft skills,” like the power to negotiate, to empathize, or to mediate between people. In other words: social skills.

Although we live in what’s known as a “knowledge economy,” we should make sure that we can still hold a conversation well and connect with others on an emotional level. So, rather than skimming inattentively through cyberspace for hours, let’s check that we can still function like – well – human beings!

[Serendipity Marie · Rating 5 out of 5]

Sitting down to my sad worktime lunch of yesterday's uneaten dinner, I decide to read this Neil Johnson book which I received for free from an agent based modeling event. Simply Complexity is meant to break down Complexity Theory for the layman or so it's author states. With such a setup I ask "How long until the author of this book says 'butterfly effect'?" Since it is a sad worktime lunch, I end up answering myself "Well, if it's anywhere in the first 5 pages I'm closing the book."

To my pleasant surprise, I do not encounter the words "butterfly effect" anywhere. Instead, I am taken on a tour of all that is considered complexity studies...introductory language on how phenomena emerge from individual interactions, to the importance of feedback. Johnson presents these complex concepts in a straightforward fashion with simple examples that he carries through the book. The (dare I say it) complexity of what he presents increases to a point that it could serve as an introductory textbook on the topic in a college level course.

Some of the later material in the book - concepts such as Power Laws can't really be written in a way that those adverse to equations will want to read. But for those who are willing to stick them out the explanation Johnson provides is one of the easiest to understand that I've found.

Considering the original publication date of this book was 2007 and the material regularly considers financial examples. It's a shame it wasn't read more widely in its original format. According to the author's own description, the types of market phenomena would have been accessibly predicted. That said, predicting a crash isn't necessarily the same as effectively avoiding one. Ten years on, the book continues to serve as an effective entry point into complexity studies.

[Jessada Karnjana · Rating 4 out of 5]

เหมาะสำหรับผู้ที่กำลังมองหาหนังสือแนะนำเกี่ยวกับ Complexity, Complex System, Complexity Science หนังสือแบ่งออกเป็น 2 ภาค ภาคแรกตอบคำถามว่า Complexity Science คืออะไร ถึงแม้นิยามในเรื่องนี้ยังไม่ชัดเจนนัก แต่ผู้เขียนก็ชี้ให้เห็น key components ของสิ่งที่เรียกว่า Complexity ต้องมีอะไรบ้าง อาทิ เป็นระบบที่กลุ่มของ agent หลาย ๆ ตัวมีปฏิสัมพันธ์กัน, agent สามารถปรับตัวหรือปรับกลยุทธ์ตามประสบการณ์ของมันได้, ระบบเช่นนี้เป็นระบบเปิด, ระบบแสดงออกถึงสมบัติราวกับ "มีชีวิต" มีการแสดงออกถึงปรากฎการณ์ที่ emergent ออกมาจากกลุ่มที่ชวนให้ประหลาดใจโดยไม่จำเป็นต้องมีผู้ควบคุมหลักหรือ "invisible hand", ระบบจะเคลื่อนไหลไปมาระหว่างพฤติกรรมมีระเบียบและไร้ระเบียบ (ใครที่เคยได้ยินทฤษฎี chaos ก็จะได้ทราบว่า chaos เป็นผลลัพธ์รูปแบบหนึ่งของ Complex System) ในภาคแรกนี้ผู้เขียนยังบรรยายให้เห็นถึงประโยชน์ของความไร้ระเบียบ (เช่น เราต้องขอบคุณความไร้ระเบียบที่ทำให้การสูดอากาศเข้าปอดครั้งต่อไปของเรายังมีออกซิเจนอยู่ในนั้น) และด้วยความที่ระบบเคลื่อนไหวไปมาระหว่างความมีระเบียบและไร้ระเบียบทำให้บางช่วงขณะ ระบบเป็นระบบที่สามารถทำนายได้

ภาคที่สอง เป็นการยกตัวอย่าง Complex System ในชีวิตประจำวัน 6 เรื่อง ได้แก่ ตลาดหุ้น, การจราจร, การหาคู่ครอง, สงครามและการก่อการร้าย, การแพร่กระจายของโรคติดต่อ และควอนตัมฟิสิกส์ ดูเหมือนแต่ละเรื่องจะเป็นเรื่องใหญ่ ๆ ยาก ๆ แต่ตามชื่อหนังสือนั่นแหละครับ simply ผู้เขียนเน้นอธิบายง่าย ๆ และไม่ลงลึกในรายละเอียดมาก ตัวอย่างก็��ป็นการเปรียบเทียบเสียมากกว่า เป็นหนังสือที่ใครก็อ่านได้ และไม่ต้องการความรู้พื้นฐานเรื่องใด ๆ ทั้งสิ้น สำหรับผู้อ่านที่พอมีพื้นฐานบ้าง อาจรู้สึกว่าหนังสือน่าเบื่อไปสักนิด เพราะพูดซ้ำย้ำแนวความคิดเดิม ๆ ในบริบทที่แตกต่างออกไป กระนั้นก็มีจุดกระดุ้นความสนใจอยากรู้อยากเห็นเป็นระยะ ๆ

[Michael Lugo · Rating 2 out of 5]

This book is about a very interesting topic, but the delivery was lacking tremendously. A better editor is in order. That said, the author is very knowledgeable, and the overall task he intended to complete with this book was enormous and difficult to execute.

I personally think that by restraining the content of the book, it could've been a much better one. For instance, complexity is a very difficult subject to tackle for most people, so the author opted to provide many examples for applications to make this clear. He spoke about financial markets, cancer, organization, terrorism, quantum computing, dating, traffic, etc. This was too much to handle and resulted in the author touching each application very lightly to the point where he shows how interesting complexity is, but stops talking right when it gets the most exciting. Had the author chosen 2 applications, and gone in good detail on each out would've been a much better book.

Also, as much as the author tried to write a book for the general public, you can still see he's an academic. This isn't bad in and of itself. The issue here is that part 2 becomes repetitive and a bit boring. A more colorful organization of the book and use of language could've brought the book to the next level.

[Evan Micheals · Rating 2 out of 5]

After finishing Poor Charlie’s Almanack I felt the need to brush up on my understanding of Complexity Theory, as I had taken Scott E Page’s course Understanding Complexity and thought it had a lot to it in guiding my thinking.

I found this book somewhat useful, but generally though it had too much physics and not enough real world implications or metaphors that help to guide thinking about complexity. I accept that it is useful (by reading the book), so for me the arguments need not have been made. He also hinted, but did not investigate what I found useful in Page’s work.

I would not recommend this book to lay people wanting to understand Complexity Theory unless you have a specific interest in the Physics and maths. Anyhow on the plus side it is only 180 pages and written well enough to make it easy to get through. I would start with the work of Scott E page (as I did).

[Daniel Cooney · Rating 3 out of 5]

Hmmm. It was good to have finally read this. I felt like the beginning was well thought out, but it got progressively looser in its explanatory power as it went on. The author started just describing some cool stuff being done with complexity investigation without bothering to explain the underlying mechanism as they did at the start of the book. And while I enjoyed the quantum entanglement topic, it felt slapped on, like it was a parallel interest for the author (and other physicists) so it was included, but the connection between the rest of the book and this was super loose. Again, it was interesting and lead me down other paths of investigation, but I would have preferred a wrap up of just the complexity side of things, instead of a separate topic that was only partially gone into.

[Sunrise (Brit) · Rating 1 out of 5]

35% = 1 Star

Well, it was okay, but it almost feels like a pre-book, if such things exist. It argues for the future of complex systems as a science and way of resolving and understanding problems.

Much time is spent qualifying what chaos and complexity are. I liked some parts, didn't like others. The author covers networks (such as social networks), systems, markets, dating, war

I liked that it was pointed out that what people take for being simple, two-sided or predictable situations, are actually immensely complex.

BUT, this book is missing something, some fascinating hook.

[Daniel Wieser · Rating 3 out of 5]

This book is actually quite confusing, but not because of the subject matter, but because of the way it is written. It jumps from one chapter to another, mentions people without giving any sources (For example, I would have liked to have more info on Pak Ming Hui), then comes back to a previous chapter... Just give me the nitty gritty of each concept without giving endless examples!

tl;dr: It is an OK book. There are probably better books on the subject.

[Mike Sanders · Rating 4 out of 5]

A decent introduction, if the mathematics is breezed past. The first part of the book is where the maths makes it far less of an introductory book than the author claims, but that is not essential to the understanding of the subject on the overall scale. The rest of the books does this well across examples. A good read to set the bases and what would be needed for future exploration

[John Cumming · Rating 2 out of 5]

This seemed like it might be a good book on complexity, but I was a bit bored with it by the end. The only real insight I got from it was the tendency for the rational actor model to break down in complex systems.

[Jamie Bowen · Rating 2 out of 5]

Not quite the book I envisaged.

[Scott Eggerding · Rating 4 out of 5]

As someone who does not study complexity theory I was very much engaged in the way the theory was explained and applied to a number of situations. A good first step for the uninitiated.

[Emilio Águila Escalante · Rating 4 out of 5]

Un libro de divulgación científica bastante interesante y bien explicado.

[Alex Klibisz · Rating 3 out of 5]

Interesting topic but explanations were shallow and verbose

[Safae · Rating 5 out of 5]

Topped

[Marije · Rating 4 out of 5]

3.5 stars

[Andrew Grabowski · Rating 4 out of 5]

I’ve been trying to read more in complexity and I think this gives a good intro, but I think it missed a lot of opportunity to really engage the reader.

[MARIA NJ · Rating 3 out of 5]

While the title says 'clear' and there were plenty of explanations, a 'practical' approach would have been more helpful.

[Seriusz · Rating 2 out of 5]

It's fine but I wish it went more in depth in most chapters.

[J. · Rating 4 out of 5]

This book is a great read regarding getting a primer into the World of Complexity Theory. There is still math involved, but compared to other books I have read on this Science, its Mathematical edge is more dull for those want more words and less math, there are also graphics given to demonstrate certain points in the book. The Book is well organized and provides further resources at the end for those who are truly interested in learning more. My only compliant was that I thought it could have expand more on certain sections of the book even more but it makes up for this by being clear from the beginning what a Complex System is defined as.