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Harnessing Complexity
Recent advances in the study of complexity have given scientists profound new insights into how natural innovation occurs and how its power can be exploited. Now two pioneers in the field, Robert Axelrod and Michael D. Cohen, provide leaders in business and government with a guide to complexity that will help them make effective decisions in a world of rapid change. Building on evolutionary biology, computer science, and social design, Axelrod and Cohen have constructed a unique framework for improving the way people work together. Their approach to management is based on the concept of the Complex Adaptive System, which can describe everything from rain forests to the human gene pool, and from automated software agents to multinational companies. The authors' framework reveals three qualities that all kinds of managers must cultivate in their "Variation" What is the best way to manage the development of software? Should the problem be broken up into small pieces for programmers working independently, thus enhancing variation, or should there be a centralized hierarchy of programmers ruled by a chain of command? The authors show how the decentralized creation of variation combined with the centralized maintenance of standards was the key to the success of the Linux "open source software" project, which brought together thousands of volunteers in cyberspace to produce an operating system that can outperform Microsoft's. "Interaction" Why did northern Italy prosper while southern Italy remained poor? Recognizing the internal interactions of a Complex Adaptive System -- be it a national region, a company, or a nonprofit group -- reveals vitalnetworks of trust. Axelrod and Cohen explain that in successful adaptive systems, rich networks of horizontal linkages foster cooperation and provide an advantage over other less cooperatively networked groups. In the case of Italy, voluntary associations created networks of trust in the Middle Ages that became northern Italy's critical advantage over the south. "Selection" Is a Pulitzer Prize better than a National Book Award? How can foundations and corporations design competitions that have a positive effect on the evolution of excellence? The authors' framework makes clear that the worst selection processes are mired in orthodox standards that have not adapted to a new environment. The best selection processes, on the other hand, are created and run by leaders who understand how the standards they use can transform their organization and its environment. This simple, paradigm-shifting analysis of how people work together will transform the way we think about getting things done in a group. "Harnessing Complexity" is the essential guide to creating wealth, power, and knowledge in the 21st century.
207 pages, Paperback
First published May 12, 2000
About the author
Robert Axelrod
13 books107 followersFrom wikipedia:
Robert Axelrod (born 1943) is a Professor of Political Science and Public Policy at the University of Michigan. He has appointments in the Department of Political Science and the Gerald R. Ford School of Public Policy. Prior to moving to Michigan, he taught at the University of California, Berkeley (1968-1974). He holds a BA in mathematics from the University of Chicago (1964) and a PhD in political science from Yale University (1969).
He is best known for his interdisciplinary work on the evolution of cooperation, which has been cited in numerous articles. His current research interests include complexity theory (especially agent-based modeling), and international security. Among his honors and awards are membership in the National Academy of Sciences, a five-year MacArthur Prize Fellowship, the Newcomb Cleveland Prize of the American Association for the Advancement of Sciences for an outstanding contribution to science, and the National Academy of Sciences Award for "Behavioral Research Relevant to the Prevention of Nuclear War".
Recently Axelrod has consulted and lectured on promoting cooperation and harnessing complexity for the United Nations, the World Bank, the U.S. Department of Defense, and various organizations serving health care professionals, business leaders, and K-12 educators.
Axelrod was the President of the American Political Science Association (APSA) for the 2006-2007 term. He focused his term on the theme of interdisciplinarity.
In May 2006, Axelrod was awarded an honorary degree by Georgetown University.
Robert Axelrod (born 1943) is a Professor of Political Science and Public Policy at the University of Michigan. He has appointments in the Department of Political Science and the Gerald R. Ford School of Public Policy. Prior to moving to Michigan, he taught at the University of California, Berkeley (1968-1974). He holds a BA in mathematics from the University of Chicago (1964) and a PhD in political science from Yale University (1969).
He is best known for his interdisciplinary work on the evolution of cooperation, which has been cited in numerous articles. His current research interests include complexity theory (especially agent-based modeling), and international security. Among his honors and awards are membership in the National Academy of Sciences, a five-year MacArthur Prize Fellowship, the Newcomb Cleveland Prize of the American Association for the Advancement of Sciences for an outstanding contribution to science, and the National Academy of Sciences Award for "Behavioral Research Relevant to the Prevention of Nuclear War".
Recently Axelrod has consulted and lectured on promoting cooperation and harnessing complexity for the United Nations, the World Bank, the U.S. Department of Defense, and various organizations serving health care professionals, business leaders, and K-12 educators.
Axelrod was the President of the American Political Science Association (APSA) for the 2006-2007 term. He focused his term on the theme of interdisciplinarity.
In May 2006, Axelrod was awarded an honorary degree by Georgetown University.
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Displaying 1 - 15 of 15 reviews
April 15, 2016
Harnessing Complexity by Robert Axelrod & Michael D. Cohen is a book offering insight into solving hard problems arising in domains spanning from economy and politics, through company management and ending on the military.
The problems that are discussed in the book fall under the domain of Complex Adaptive Systems. Complex Adaptive Systems are systems of many participants and even many types of participants. They are systems where the participants interact in many intricate ways. New interactions may appear, and old interactions might vanish. New participants might arise and old ones disappear. Complex Adaptive Systems exhibit emergent behavior; small changes might produce large perturbations; and large changes might change nothing.
Yet Complex Adaptive Systems aren't chaotic nor are they random - Complex Adaptive Systems are Complex not because they are random but because they exhibit patterns and non-randomness in ways that are hard to define or to predict. They are adaptive because the participants of the system adapt to each other (and to the system at large).
The framework which allows managing those problems borrows ideas from evolutionary biology, optimization and artificial intelligence. The key concepts are are: Variation, Interaction and Selection. They are explained thoroughly in their own chapters.
Variation is how strategies or participants in the system change to adapt. Variation is closely related to the exploration versus exploitation trade-off known from optimization. Too little variation means less exploration, too much variation means that we might not explore the search space. Both mean that agents (participants) might not find the optimal solution.
Interaction defines patterns of behavior of and how they might influence agent's behavior. Examples range form location (physical or conceptional) inhibiting influence of distant agents, barriers (physical like walls or conceptual ones like secretaries guarding the access to key people in the company), copying the behavior of other agents so on and so forth.
Finally, Selection describes the way that strategies and agents are preserved in the system; how, when and why create or delete agents or strategies; how to "credit" agents/strategies for their performance and the problems and intricacies thereof.
The biggest problem of the book is its presentation. The book offers profound knowledge but sometimes very interesting observations are almost smuggled in as offhand comments and the non-important minutia seem to drag on for a couple of pages. Even though I'm pretty familiar with concepts of artificial life and optimization (which forms the basis of the framework of Harnessing Complexity) I had a problem picking through relevant and non-relevant topics and had a few "so what?" moments. As it is the book needs re-reading and probably a closer study with a hands-on project to get everything out of it.
N.B the book also contains a few of a few typos and ungrammatical sentences which coupled with the subject matter certainly doesn't help comprehension.
Harnessing Complexity is an interesting book with some very deep ideas. If it wasn't for the presentation it easily could have been one of my favorites.
The problems that are discussed in the book fall under the domain of Complex Adaptive Systems. Complex Adaptive Systems are systems of many participants and even many types of participants. They are systems where the participants interact in many intricate ways. New interactions may appear, and old interactions might vanish. New participants might arise and old ones disappear. Complex Adaptive Systems exhibit emergent behavior; small changes might produce large perturbations; and large changes might change nothing.
Yet Complex Adaptive Systems aren't chaotic nor are they random - Complex Adaptive Systems are Complex not because they are random but because they exhibit patterns and non-randomness in ways that are hard to define or to predict. They are adaptive because the participants of the system adapt to each other (and to the system at large).
The framework which allows managing those problems borrows ideas from evolutionary biology, optimization and artificial intelligence. The key concepts are are: Variation, Interaction and Selection. They are explained thoroughly in their own chapters.
Variation is how strategies or participants in the system change to adapt. Variation is closely related to the exploration versus exploitation trade-off known from optimization. Too little variation means less exploration, too much variation means that we might not explore the search space. Both mean that agents (participants) might not find the optimal solution.
Interaction defines patterns of behavior of and how they might influence agent's behavior. Examples range form location (physical or conceptional) inhibiting influence of distant agents, barriers (physical like walls or conceptual ones like secretaries guarding the access to key people in the company), copying the behavior of other agents so on and so forth.
Finally, Selection describes the way that strategies and agents are preserved in the system; how, when and why create or delete agents or strategies; how to "credit" agents/strategies for their performance and the problems and intricacies thereof.
The biggest problem of the book is its presentation. The book offers profound knowledge but sometimes very interesting observations are almost smuggled in as offhand comments and the non-important minutia seem to drag on for a couple of pages. Even though I'm pretty familiar with concepts of artificial life and optimization (which forms the basis of the framework of Harnessing Complexity) I had a problem picking through relevant and non-relevant topics and had a few "so what?" moments. As it is the book needs re-reading and probably a closer study with a hands-on project to get everything out of it.
N.B the book also contains a few of a few typos and ungrammatical sentences which coupled with the subject matter certainly doesn't help comprehension.
Harnessing Complexity is an interesting book with some very deep ideas. If it wasn't for the presentation it easily could have been one of my favorites.
February 11, 2022
This could be 4 stars, but as it wasn't what I was looking for, 3 it is.
First of all, what this is not: this is not a quantitative description or investigation of complex systems, a book about agent-based modeling, etc. That is more what I was looking for and -for me- earned a -1 on the stars.
As far as what the book is: a qualitative description and partial categorization of complex systems and related ideas (e.g. the 4 to alter behaviors/agent choice/rewards in a complex system.) In this way, it is still a good book (and deserving of maybe 3.5 stars, but Goodreads.) If you wanted to start out building quantitative descriptions yourself, these are the qualitative descriptions you would start with.
First of all, what this is not: this is not a quantitative description or investigation of complex systems, a book about agent-based modeling, etc. That is more what I was looking for and -for me- earned a -1 on the stars.
As far as what the book is: a qualitative description and partial categorization of complex systems and related ideas (e.g. the 4 to alter behaviors/agent choice/rewards in a complex system.) In this way, it is still a good book (and deserving of maybe 3.5 stars, but Goodreads.) If you wanted to start out building quantitative descriptions yourself, these are the qualitative descriptions you would start with.
September 29, 2017
Harnessing Complexity is a gentle introduction to "complex systems": populations of heterogeneous agents that interact, learn, evolves, etc. Such systems exhibit unexpected behaviours, with sudden changes of regime, cycles, oscillations or tipping points to name a few. The text focuses on three key aspects, namely variation, interaction, and selection. Variation mainly results in multiple species whose agents apply different strategies; interaction refers to the alternative interaction, be it in a physical universe (e.g., natural landscape) or in a conceptual one (e.g., a company hierarchy), whereas selection covers which agents survive.
I found the book very easy to read compared for instance to "Complex Adaptive Systems: An Introduction to Computational Models of Social Life" by J. H. Miller. Yet, having read other books on the subject including several texts from J. Holland, I did not get much more beyond what I already knew. While I would certainly recommend it as an introduction, I would rather orient complex systems "connoisseurs" towards more specific text, on chaos theory or on learning classifier systems for instance.
I found the book very easy to read compared for instance to "Complex Adaptive Systems: An Introduction to Computational Models of Social Life" by J. H. Miller. Yet, having read other books on the subject including several texts from J. Holland, I did not get much more beyond what I already knew. While I would certainly recommend it as an introduction, I would rather orient complex systems "connoisseurs" towards more specific text, on chaos theory or on learning classifier systems for instance.
July 22, 2021
Kitabı ilk olarak TTC Complexity serisinin son dersinde Scott Page'ten duydum. Complexity unsurlarını inceledikten sonra nasıl bir sistemi modelleyebileceğimizi tartışırken kitaptan alıntılar yaptı. Ben de büyük bir hevesle, sadece complex sistemlerden örneklemeler yapmayan fakat böylesi bir sistemi elementlerine ayırıp msıfırdan modellemeler yapılmasını mümkün kılacak bir yol gösterici olacağı hevesiyle aldım ancak dili çok sıkıcı olan ve araya örnekler sıkıştırılarak yazılmış bir ansiklopedik kitap gibi okuması her geçen sayfada biraz daha biraz daha zorlaştı. Evet bir karmaşık sistemin elemanlarından bahsediyor ama sadece sözel olarak az örnekle. Kafamda modelleyemediğim bir aksiyomlar bütünü olarak kitabı yarıda bırakarak (80. sayfada) rafa kaldıracaktım ki hızlı hızlı okumaya devam etme kararı aldım. Kitabın hiçbir kısmını okumadan sadece conclusion kısmının okunması dahi aslında yeterliymiş. Dizge kesinlikle sondan başa doğru yapılmalıymış. Tam olarak görmek ve duymak istediğim bilgiler beklediğim yeterlilikte conclusion bölümünde yer alıyordu. Bu sebeple kitap bir başucu kitabı hükmü kazandı. Belirtilen noktalara dikkat etmeden bir karmaşık sistem modeli kurmanın imkansızlığı gözlerimin önüne serildi.
Okuma için modeli kurmadan evvel son bölüme bakılmaalı ardından kitap içinde ilgili bölümle alakalı olan başlık okunup incelenmeli.
İkinci el bir kitap olduğundan ötürü bir önceki ya da birkaç önceki sahibinin çokça doğru noktaların altını çizdiğini ve bunun da aslında odağımı korumamı mümkün kıldığını belirtmeliyim.
*BACH ekibi güzel kuramlar oluştursalar da bunu yazıya dökme işinde biraz ketumlar.
**Kitabın decision making in a complex environment üzerinde de oldukça fazla durduğunu hatta meselesinin de bu olduğunu belirtmeliyim. Cynefin Framework bilinerek okunursa daha faydalı olacaktır.
***Çokça yerde kitabın ne anlatmak istediğini yakalayamadım ya da çok önemli bulduğum bir nokta alelade bir meseleymiş gibi geçilmişti. Bu açıdan vurgu ile ilgili problemi olduğunu da belirtmeliyim.
Okuma için modeli kurmadan evvel son bölüme bakılmaalı ardından kitap içinde ilgili bölümle alakalı olan başlık okunup incelenmeli.
İkinci el bir kitap olduğundan ötürü bir önceki ya da birkaç önceki sahibinin çokça doğru noktaların altını çizdiğini ve bunun da aslında odağımı korumamı mümkün kıldığını belirtmeliyim.
*BACH ekibi güzel kuramlar oluştursalar da bunu yazıya dökme işinde biraz ketumlar.
**Kitabın decision making in a complex environment üzerinde de oldukça fazla durduğunu hatta meselesinin de bu olduğunu belirtmeliyim. Cynefin Framework bilinerek okunursa daha faydalı olacaktır.
***Çokça yerde kitabın ne anlatmak istediğini yakalayamadım ya da çok önemli bulduğum bir nokta alelade bir meseleymiş gibi geçilmişti. Bu açıdan vurgu ile ilgili problemi olduğunu da belirtmeliyim.
July 18, 2020
A good contribution that straddles theory and practice adequately
It is always a challenge to write for both academics and practitioners. This book does an adequate job, but could go further into both.
As a guide for practitioners it remains a little abstract and good benefit from more prescriptive guidance. It could also benefit from using the Minto Pyramid Principle: Provide the framework first (conclusion as introduction) and then go into detail into the how with the chapters that follow.
As such, practitioners may benefit from reading the conclusion first.
From an academic perspective the authors would contribute more if they stressed how their approach changes the paradigm of complexity research.
In terms of the paradigm, the authors could focus more on the importance of different resolutions / levels within a complex adaptive system and the importance of the level at which abstraction is appropriate for the analysis in question.
It is always a challenge to write for both academics and practitioners. This book does an adequate job, but could go further into both.
As a guide for practitioners it remains a little abstract and good benefit from more prescriptive guidance. It could also benefit from using the Minto Pyramid Principle: Provide the framework first (conclusion as introduction) and then go into detail into the how with the chapters that follow.
As such, practitioners may benefit from reading the conclusion first.
From an academic perspective the authors would contribute more if they stressed how their approach changes the paradigm of complexity research.
In terms of the paradigm, the authors could focus more on the importance of different resolutions / levels within a complex adaptive system and the importance of the level at which abstraction is appropriate for the analysis in question.
June 16, 2021
If you want an excellent overview of how to manage complex systems (yes it can be done - but perhaps not in the way you’re familiar with) then this book is a must read. Lots of it is very familiar if you’ve spent time learning and using Cynefin, but there are still many parts of this book that will enhance understanding and practical approaches. I particularly liked the discussion on the nature of interactions and can clearly see how this will enhance exploration of constraints and modulation of those constraints as options for moving to adjacent possibilities within the system.
September 13, 2019
If you want to make change in business, politics, or any other complex system, read this book (and many others on CAS) to understand what we know about complex systems and what levers we have to manipulate them. This book's subject matter is super high signal. Really liked it.
July 5, 2021
Succinct book that advances a theory on Complex Adaptive Systems. The framework they offer is quite helpful for dealing with complex systems (markets, software design, ecosystems) and the case studies help make the abstract concrete!
February 14, 2019
Unless you’re interested in the theoretical frameworks surrounding ‘complexity,’ I would not recommend Harnessing Complexity. More of a textbook or scholarly article than a book for general consumption, Harnessing Complexity is filled with dry, abstract ideas but lacks any real practical application. The highlights are the case studies and experiments the used to explain the application of theoretical principles. Unless you are interested in the theoretical underpinnings of complexity, I’d recommend skipping this book or reading a short summary of the key principles rather than wading through all 160 pages
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April 18, 2014Axelrod (and in this case, working with co-author Michael D. Cohen) does a great job of describing complexity. It's an very lucid description of the organization properties inherent in complex systems. I'm glad I started here when I first decided that I needed to understand complexity theory. His, 'The Complexity of Cooperation is also part of the the foundation of complexity theory and its usefulness.
August 15, 2010
I was somewhat disappointed with this book because The Evolution of Cooperation was so great. I think this is a decent introduction to complex social systems providing the reader with a basic vocabulary and some some moderately insightful discussion of social systems. There doesn't seem to be any unique contributions here. I thought the discussion about variation was the best part of the book.
August 24, 2013
Usually, you would think that complexity is a negative phenomenon to be controlled and if possible, if you are lucky eliminated..... The authors look at the flip side of this argument where the complexity is "harnessed" in order to explore as well exploit different nodes in a decision tree in order to determine the best methods....
March 24, 2012
Content: Incredible
Readability: Difficult
This is a book I read for a class, and it was honestly torturous to get through. The science is compelling, but it just doesn't make for a great read.
Readability: Difficult
This is a book I read for a class, and it was honestly torturous to get through. The science is compelling, but it just doesn't make for a great read.
December 29, 2013
Important systematic description of what agent-based modeling is all about in studying complex systems.
May 2, 2017
This book focuses on defining agents, populations, interactions, strategies, and other terms useful for understanding a complex adaptive system, and then goes about exploring how one might succeed in one based on encouraging variety or uniformity and how to shape interactions. The last chapter (summary) does a great job explaining the details, but it is very useful to have read the book in its entirety first, to understand the highly condensed context.
Displaying 1 - 15 of 15 reviews