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How Nature Works: The Science of Self-organized Criticality
Self-organized criticality, the spontaneous development of systems to a critical state, is the first general theory of complex systems with a firm mathematical basis. This theory describes how many seemingly desperate aspects of the world, from stock market crashes to mass extinctions, avalanches to solar flares, all share a set of simple, easily described properties.
"...a'must read'...Bak writes with such ease and lucidity, and his ideas are so intriguing...essential reading for those interested in complex systems...it will reward a sufficiently skeptical reader." -NATURE
"...presents the theory (self-organized criticality) in a form easily absorbed by the non-mathematically inclined reader." -BOSTON BOOK REVIEW
"I picture Bak as a kind of scientific musketeer; flamboyant, touchy, full of swagger and ready to join every fray... His book is written with panache. The style is brisk, the content stimulating. I recommend it as a bracing experience." -NEW SCIENTIST
"...a'must read'...Bak writes with such ease and lucidity, and his ideas are so intriguing...essential reading for those interested in complex systems...it will reward a sufficiently skeptical reader." -NATURE
"...presents the theory (self-organized criticality) in a form easily absorbed by the non-mathematically inclined reader." -BOSTON BOOK REVIEW
"I picture Bak as a kind of scientific musketeer; flamboyant, touchy, full of swagger and ready to join every fray... His book is written with panache. The style is brisk, the content stimulating. I recommend it as a bracing experience." -NEW SCIENTIST
225 pages, Hardcover
First published August 29, 1996
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January 4, 2009Pretty good and light pop intro to self organized criticality. Not sure if i will finish it, cause I pretty much get the gist and there are no equations to look forward to. The first part of the book explained the concept of self organized criticality and then it was just like: and here's a power law and here's a power law and this is self organized critical and this is self organized critical. Not that I don't get excited about a power law: check this out: if you take a sample of language-- today's newspaper or Ulysses-- and count up the number of times each word is used and plot this against the popularity rank of the word on a log log plot, it is a straight line with a slope of 1. Can you explain that to me? If you can, you should let me know- because i just think it is nature magic.
August 25, 2020
Fart noise. Everything about the title is deceiving. Rather than “How Nature Works”, it could be called “Limited Observations and Irresponsible Extrapolations of Incredibly Oversimplified Mathematical and Computer Models.”
There is no investigation, let alone proof, that a critical system is organized “by itself.”
Entertaining moments in the book are the personal stories of conversations and collaborations with colleagues. But the author seems to use these as a thinly veiled excuse to complain about how the work doesn’t receive the funding the author believes it deserves.
Reading this might have been a waste of my time, but I learned from this book that even deeply high level researchers and scientists are still basing so much of their work on trillions of assumptions, all stacked like turtles holding up the earth. So, discovering that fact was worth the time.
There is no investigation, let alone proof, that a critical system is organized “by itself.”
Entertaining moments in the book are the personal stories of conversations and collaborations with colleagues. But the author seems to use these as a thinly veiled excuse to complain about how the work doesn’t receive the funding the author believes it deserves.
Reading this might have been a waste of my time, but I learned from this book that even deeply high level researchers and scientists are still basing so much of their work on trillions of assumptions, all stacked like turtles holding up the earth. So, discovering that fact was worth the time.
Want to read
February 17, 2010recommended by Murray Gel-Man
April 5, 2019
An equilibrium of sensationalist overreach and hubris, punctuated by bursts of interesting ideas.
October 9, 2020
Poorly written, ugly cover, great content.
January 11, 2011
Già il titolo megalomane potrebbe mettere in guardia molti.
Per Bak è uno degli scopritori della "self-organized criticality". Si tratta della condizione di alcuni sistemi dinamici che, sotto costante sollecitazione esterna, raggiungono uno stato critico, cioè in cui esistono correlazioni tra eventi a tutte le scale incluse nel sistema, in particolare cascate di eventi che assumono talvolta le proporzioni di vere catastrofi. La cosa che distingue questo stato critico dagli stati critici già noti dalla meccanica statistica (i.e. quelli attorno alle transizioni di fase) è che si tratta di uno stato autoorganizzato, cioè che non viene posto in essere da uno specifico parametro di controllo (come e.g. la temperatura), ma dipende dalla struttura e dalle proprietà stesse del sistema.
La scoperta è originale e certamente interessante, risale al 1988, ed ebbe al momento dell'apparizione una grossa risonanza, tanto che il paper originale fu il più citato dell'anno in ambito fisico. Questo meritò all'autore la chiamata al Santa Fe Institute, dove venne a contatto con scienziati di molteplici discipline. E maturò l'idea, in sostanza, che avesse scoperto un principio onnipresente e sostanziale della realtà, non solo fisica ma anche economica, biologica, neuronale, geologica, astrofisica e chi più ne ha più ne metta.
Da cosa nacque il sospetto di aver invero scoperto il segreto della natura? Dalla constatazione che il modello della SOC produce distribuzioni di eventi scale-free; e queste distribuzioni caratterizzano molti fenomeni ancora poco ben spiegati, come la frequenza e la magnitudo dei terremoti, gli equilibri puntuati in teoria dell'evoluzione, le fluttuazioni economiche e del traffico, automi cellulari, le caratteristiche del cervello e molto altro ancora.
Orbene, se l'autore si fosse limitato a ipotizzare che la sua amata SOC potesse eventualmente essere alla base di alcuni, se non tutti, questi fenomeni, avrebbe creato qualcosa di interessante, come chiunque con modestia getta proposte innovative e unificanti nella ricerca. Del resto, le introspezioni proposte da outsiders sono sovente molto prolifiche e benefiche per arricchire i panorami di ogni disciplina. Purtroppo, in più di un passo e fin dall'inizio l'autore ci fa capire che non c'è dubbio che la SOC è alla base della dinamica della natura, in possibilmente tutte le sue manifestazioni!
Queste affermazioni sono quasi sempre supportate da labili evidenze, che di solito si riducono al dimostrare che il semplice modello SOC di un certo fenomeno produce una distribuzione esponenziale con esponente simile, se non uguale, a quella del fenomeno reale. Oltretutto, i modelli sono spesso soltanto simulati numericamente. Vale il commento che Maynard Smith fece dell'opera di Kauffman: non si può fare scienza solo con le simulazioni.
Come se ciò non bastasse, la SOC risulta essere soltanto (come dice Cosma Shalizi) uno dei tanti modi che possono determinare, fatto salvo giustificare, l'apparizione di distribuzioni esponenziali.
In sostanza, il libro si riduce a questo:
1) Molti fenomeni in natura presentano distribuzioni di eventi esponenziali, in particolare rumore 1/f e frattali;
2) distribuzioni esponenziali sono sintomo di stati critici;
2) Noi abbiamo scoperto un semplice metodo che da luogo a queste distribuzioni;
3) dunque il nostro metodo spiega tutti i fenomeni che presentano queste distribuzioni!
OpPERBAKko! Il passo da 1) o 2) è già labilissimo. Da 3) a 4) è proprio un salto nel buio! Forse deve aver contribuito a questa conclusione tentatrice anche la carenza - allora come tuttora - di modelli fisici semplici con simili pretese di onnicomprensione.
Siccome questa grossa falla, come detto, emerge quasi subito leggendo il testo, il libro, per quanto carino e a tratti interessante - ci sono spunti carini sul valore di modelli semplici in fisica, sulla definizione di complessità - ne risente molto. Ogni volta che si inizia uno dei capitoli si pensa: e ora che cosa altro sarà in grado di spiegare la SOC?
Fosse stato meno mitomane e più scettico, sarebbe stato un buon testo.
Per Bak è uno degli scopritori della "self-organized criticality". Si tratta della condizione di alcuni sistemi dinamici che, sotto costante sollecitazione esterna, raggiungono uno stato critico, cioè in cui esistono correlazioni tra eventi a tutte le scale incluse nel sistema, in particolare cascate di eventi che assumono talvolta le proporzioni di vere catastrofi. La cosa che distingue questo stato critico dagli stati critici già noti dalla meccanica statistica (i.e. quelli attorno alle transizioni di fase) è che si tratta di uno stato autoorganizzato, cioè che non viene posto in essere da uno specifico parametro di controllo (come e.g. la temperatura), ma dipende dalla struttura e dalle proprietà stesse del sistema.
La scoperta è originale e certamente interessante, risale al 1988, ed ebbe al momento dell'apparizione una grossa risonanza, tanto che il paper originale fu il più citato dell'anno in ambito fisico. Questo meritò all'autore la chiamata al Santa Fe Institute, dove venne a contatto con scienziati di molteplici discipline. E maturò l'idea, in sostanza, che avesse scoperto un principio onnipresente e sostanziale della realtà, non solo fisica ma anche economica, biologica, neuronale, geologica, astrofisica e chi più ne ha più ne metta.
Da cosa nacque il sospetto di aver invero scoperto il segreto della natura? Dalla constatazione che il modello della SOC produce distribuzioni di eventi scale-free; e queste distribuzioni caratterizzano molti fenomeni ancora poco ben spiegati, come la frequenza e la magnitudo dei terremoti, gli equilibri puntuati in teoria dell'evoluzione, le fluttuazioni economiche e del traffico, automi cellulari, le caratteristiche del cervello e molto altro ancora.
Orbene, se l'autore si fosse limitato a ipotizzare che la sua amata SOC potesse eventualmente essere alla base di alcuni, se non tutti, questi fenomeni, avrebbe creato qualcosa di interessante, come chiunque con modestia getta proposte innovative e unificanti nella ricerca. Del resto, le introspezioni proposte da outsiders sono sovente molto prolifiche e benefiche per arricchire i panorami di ogni disciplina. Purtroppo, in più di un passo e fin dall'inizio l'autore ci fa capire che non c'è dubbio che la SOC è alla base della dinamica della natura, in possibilmente tutte le sue manifestazioni!
Queste affermazioni sono quasi sempre supportate da labili evidenze, che di solito si riducono al dimostrare che il semplice modello SOC di un certo fenomeno produce una distribuzione esponenziale con esponente simile, se non uguale, a quella del fenomeno reale. Oltretutto, i modelli sono spesso soltanto simulati numericamente. Vale il commento che Maynard Smith fece dell'opera di Kauffman: non si può fare scienza solo con le simulazioni.
Come se ciò non bastasse, la SOC risulta essere soltanto (come dice Cosma Shalizi) uno dei tanti modi che possono determinare, fatto salvo giustificare, l'apparizione di distribuzioni esponenziali.
In sostanza, il libro si riduce a questo:
1) Molti fenomeni in natura presentano distribuzioni di eventi esponenziali, in particolare rumore 1/f e frattali;
2) distribuzioni esponenziali sono sintomo di stati critici;
2) Noi abbiamo scoperto un semplice metodo che da luogo a queste distribuzioni;
3) dunque il nostro metodo spiega tutti i fenomeni che presentano queste distribuzioni!
OpPERBAKko! Il passo da 1) o 2) è già labilissimo. Da 3) a 4) è proprio un salto nel buio! Forse deve aver contribuito a questa conclusione tentatrice anche la carenza - allora come tuttora - di modelli fisici semplici con simili pretese di onnicomprensione.
Siccome questa grossa falla, come detto, emerge quasi subito leggendo il testo, il libro, per quanto carino e a tratti interessante - ci sono spunti carini sul valore di modelli semplici in fisica, sulla definizione di complessità - ne risente molto. Ogni volta che si inizia uno dei capitoli si pensa: e ora che cosa altro sarà in grado di spiegare la SOC?
Fosse stato meno mitomane e più scettico, sarebbe stato un buon testo.
PS: Bak è morto qualche tempo fa. Sarebbe interessante vedere come viene considerata oggi la SOC dagli specialisti.
August 4, 2021
Reading this book as a layman is like watching sand dry, so to speak. I feel bad about giving the book two stars because I’m not in a position to comment on the science itself, but from my perspective I was disappointed by the book’s inaccessibility to non-specialists. It was like reading an expanded scientific paper with a few dry academic anecdotes about discussions in the Faculty Club thrown in.
The core idea of self-organised criticality is very interesting and the author does show how this has broad applicability in fields such as neuroscience and economics, but most of his emphasis is on proving that self-organised criticality exists in these fields rather than expanding on what the implications actually are.
In short, non-specialist readers would be better advised to read an article on the subject rather than this book. Or at least wait until the film adaptation comes out.
The core idea of self-organised criticality is very interesting and the author does show how this has broad applicability in fields such as neuroscience and economics, but most of his emphasis is on proving that self-organised criticality exists in these fields rather than expanding on what the implications actually are.
In short, non-specialist readers would be better advised to read an article on the subject rather than this book. Or at least wait until the film adaptation comes out.
March 23, 2009
Explores the area between chaos and equilibrium-- the
domain of living things.
Proposes "Self organized criticallity" as the process that
results in a signature type of statistics, the power laws.
Earthquakes, traffic flow, evolution, fingerprint formation,
are all examples.
This book goes well with Order Out of Chaos by Prigogene.
Some ambiguous examples, graphs and explanations, this is mostly
a hand waving book with little mathematical content, but lots
of computer simulations.
domain of living things.
Proposes "Self organized criticallity" as the process that
results in a signature type of statistics, the power laws.
Earthquakes, traffic flow, evolution, fingerprint formation,
are all examples.
This book goes well with Order Out of Chaos by Prigogene.
Some ambiguous examples, graphs and explanations, this is mostly
a hand waving book with little mathematical content, but lots
of computer simulations.
July 28, 2019
Not impressed. Cast of thousands who we don’t know & have never heard of (and will never hear of again). The breaking point for me was reading how disappointed Mr Bak was that his colleague in Venice had a nicer office. SOC is an important concept & needs a wider audience. This ain’t the guy or the book. Told my granddaughter to not waste her time reading it.
October 26, 2012
A lot of great ideas and very well-written.
September 25, 2016
In its own terminology, I think this book is a huge and rare avalanche in the dynamics of scientific authorship.
Read
February 5, 2022What I got out of it
Self-organized criticality stems from simple rules with no “blind watchmaker” and can lead to very complex outcomes. Exhibits criticality through occasional punctuated equilibria and emergent, non-linear properties (such as earthquakes)
Fluctuations should be expected and are healthy! They are the most efficient way to run a dynamic system. Complexity can arise out of simple laws with no outside help and is seen all over nature. Chaos is not complexity
Summary
Self-organized criticality (SOC) is a new way of viewing nature – perpetually out of balance but in a poised state, a critical state, where anything can happen within well-defined statistical laws. The aim of the science of SOC is to yield insight into the fundamental question of why nature is complex, not simple, as the laws of physics imply
Key Takeaways
Manifestations of SOC – regularity of catastrophic events, fractals, 1/f noise, Zipf’s laws
So similar that they can be expressed as straight lines on a double logarithmic plot – are they all manifestations of a single principle?
Read more at https://blas.com/how-nature-works/
Self-organized criticality stems from simple rules with no “blind watchmaker” and can lead to very complex outcomes. Exhibits criticality through occasional punctuated equilibria and emergent, non-linear properties (such as earthquakes)
Fluctuations should be expected and are healthy! They are the most efficient way to run a dynamic system. Complexity can arise out of simple laws with no outside help and is seen all over nature. Chaos is not complexity
Summary
Self-organized criticality (SOC) is a new way of viewing nature – perpetually out of balance but in a poised state, a critical state, where anything can happen within well-defined statistical laws. The aim of the science of SOC is to yield insight into the fundamental question of why nature is complex, not simple, as the laws of physics imply
Key Takeaways
Manifestations of SOC – regularity of catastrophic events, fractals, 1/f noise, Zipf’s laws
So similar that they can be expressed as straight lines on a double logarithmic plot – are they all manifestations of a single principle?
Read more at https://blas.com/how-nature-works/
May 21, 2018
Interesting preliminary dive into complexity science--cool how many disparate fields of the natural and social sciences it straddles. I was especially interested by the conclusions the author was able to arrive at, namely that a self-organized critical system (like traffic, macroevolution, or the economy) is not the best possible state of affairs but the best possible state of affairs that is dynamically achievable. This has some serious implications for our understanding of economics, at first glance along a libertarian vein. But that is not to say that an economy gives the best results when totally left to its own devices (because empirically we know that this is not true). I interpret this as meaning that the free market as opposed to a centrally-planned economy gives the best results, but that institutions (and in particular, impartial and responsive institutions) are important in setting the rules of how the agents in the free market interact. Much like how a self-organized critical system can be "tuned" with different rules of the game for different (better?) results.
February 12, 2020
For those interested in mathematics about random events this is one book not to miss. Everything in nature seems random. Even "law of physics" seems random in everyday observation and also in laboratories.
The central idea of the book is that the chance of happening small event is large and vice versa. It can be seen in various fields from sand-pile, earthquake prediction, astrophysics , economics , society, etc. The system thus remain in critical state, i.e. small imbalance can trigger an avalanche. This means extinction of dinosaurs could be possible without any external agent (asteroid) or the collapse of soviet could be possible without American intervention.
While reading, sometimes it becomes annoying due to repetition of same concept in every field and you want to scan instead of reading full text. Also author forgot to discuss the cons of this thought process.
Radio interview with the author at:
youtube.com/watch?v=ydt99BXi3YU
mathematical formulation at:
youtube.com/watch?v=N1y_90y0V2k
The central idea of the book is that the chance of happening small event is large and vice versa. It can be seen in various fields from sand-pile, earthquake prediction, astrophysics , economics , society, etc. The system thus remain in critical state, i.e. small imbalance can trigger an avalanche. This means extinction of dinosaurs could be possible without any external agent (asteroid) or the collapse of soviet could be possible without American intervention.
While reading, sometimes it becomes annoying due to repetition of same concept in every field and you want to scan instead of reading full text. Also author forgot to discuss the cons of this thought process.
Radio interview with the author at:
youtube.com/watch?v=ydt99BXi3YU
mathematical formulation at:
youtube.com/watch?v=N1y_90y0V2k
May 8, 2017
Interesting romp across different areas of application of self-organised criticality, following the development of the field over the course of its early phase. There is also an interesting perspective that comes from a scientist that is working on the problem and describes how they handle the problems and the opportunities that you would not get from a third party.
However, the book's title overclaims, SOC cannot fully explain how nature works, and in some ways, I get the sense we don't completely understand how SOC works, which are similar classes of phenomena and which are different. Also, the book is not entirely clear, I don't feel like I learned so much about SOC compared to what I knew from Wikipedia. But there were experiments and domains I was not aware of that made the book interesting and worthwhile.
However, the book's title overclaims, SOC cannot fully explain how nature works, and in some ways, I get the sense we don't completely understand how SOC works, which are similar classes of phenomena and which are different. Also, the book is not entirely clear, I don't feel like I learned so much about SOC compared to what I knew from Wikipedia. But there were experiments and domains I was not aware of that made the book interesting and worthwhile.
January 6, 2021
I recently read Unknown Market Wizzards which is about highly effective stock market traders, these individuals make serious money in a challenging market one of them said he was inspired by Per Bak so I read the book with curiosity. The book describes criticality and describes pure scientific research into manifold scenarios from sand piles to the brain but ending in economics and traffic jams.
February 15, 2024
Introduction to self-organised criticality (SOC) -- phenomena that obey size-frequency power laws. Bak does not really try to give a mechanistic explanation for why we should expect these, even for the simple sandpile model that is his trademark.
The search for "general" theories of power laws in a wide variety of fields was the rage for a while, and led to a number of high-profile papers that have, largely, led to little. Researchers, largely physicists, really wanted power laws -- straight lines with negative slope on log event size-log event frequency plots -- to be true. Why, I don't know. A log-log plot compresses a lot of time and energy, so why must there be a straight line there for the patterns to be interesting? To me the fact that such events might follow power laws suggests more about the permissiveness of the methods of analysis than whatever causes the phenomena under study.
Bak (who died in 2002) portrays the hunt for models that (only in the vaguest sense) resemble processes in the fields under study. While simple models can be very useful, that doesn't mean that *any* simple model is useful so long as it displays your feature of interest (negative linear slope on a log-log plot). One glaring omission from the book is discussing exponents of power laws: what they mean, that small differences in exponents mean big differences in behaviour, and the potentially very large impact of errors in their estimations.
It gets really annoying that in many places, Bak wonders why biologist/geologists/economists/pick-a-field don't want to find general models that explain everything -- "don't want to" -- because that's what he claims to be doing. That is, he claims early on, is what physics does -- a "hard" science, his word, along with chemistry and molecular biology. All other sciences are "soft." And so is some physics -- physicists who do work Bak doesn't think is ambitious enough. Bak's conclusion is that the soft sciences don't look for general phenomena like he pursues because there are social constraints within the sciences not to. We truly cannot trust Bak here. He meets Stephen Jay Gould, insults his work, and makes nothing of the opportunity because he had a plane to catch. Fortunately the book is short. I hope there is a better, more nuanced, more mechanistic, less egotistical treatment of power laws out there.
The evolutionary models, for example, that Bak studied are essentially useless, and the phenomenon they proport to study, the feature that Bak says they must capture -- punctuated equilibrium -- is not a thing. Stephen Jay Gould claimed PE was a general trend, as do people outside evolutionary biology including physicists, who follow Gould's rhetoric in claiming Darwin was nothing but a gradualist. But biologists do not find PE to be useful, beginning with Darwin who was in no way a thorough-going gradualist. Bak continues the oft-misunderstood notion that micro- and macroevolution are fundamentally different processes, not true. This is something SJG kept pushing because of PE, but it just isn't true: some new things come into play during incipient speciation, but it is still all happening via microevolution.
Bak goes on to claim that we biologists don't have general evolutionary theories because our models don't accommodate mass extinctions like the Great Dying, the K-T boundary, and so on. How, exactly, are our biological models supposed to capture those? Biology can predict responses to those events, can track the reassembly of biota, but predict the events themselves? Bak so insists on his model that he claims that the meteor at the K-T boundary was probably not the main cause of the dinosaur extinction (!!), because the dinosaurs were probably on the way out already (!!). His "general" (simple, but wrong) model of evolution (speciation and extinction) produces catastrophic extinctions without outside catastrophes occurring. So, he insists that K-T (and other external causes of extinction) must be largely incidental because *his* models don't need them to show catastrophic extinctions. It is a *big* problem to wave away the K-T meteor so that his toy model can be true.
For a model of evolution, it may be that external catastrophes that affect speciation and extinction rates arrive with magnitudes and frequencies that follow a power law, whether they be meteors, volcanic events, anthropogenic sources, and so on. That's probably all the need we have for a power law affecting the outcomes of evolutionary models: to provide perturbations. There is no need for extinction catastrophes to arise endogenously within evolution models, and I would seriously question any model in which they do. "Mutational meltdowns" might occur during population contraction through Muller's-ratchet processes, when deleterious alleles fix again and again rather than purge, but if this occurs it would affect particular populations under particular conditions, mostly environmental degredation. Such conditions might arise simultaneously among many populations as a result of a common catastrophe, but on this scale it would be happening because of the catastrophe, not as a result of endogeneous processes. And it affects populations, not species; species-wide, it might facilitate speciation rather than extinction.
I would love a good book on power laws or log-log phenomena, but this is not it.
The search for "general" theories of power laws in a wide variety of fields was the rage for a while, and led to a number of high-profile papers that have, largely, led to little. Researchers, largely physicists, really wanted power laws -- straight lines with negative slope on log event size-log event frequency plots -- to be true. Why, I don't know. A log-log plot compresses a lot of time and energy, so why must there be a straight line there for the patterns to be interesting? To me the fact that such events might follow power laws suggests more about the permissiveness of the methods of analysis than whatever causes the phenomena under study.
Bak (who died in 2002) portrays the hunt for models that (only in the vaguest sense) resemble processes in the fields under study. While simple models can be very useful, that doesn't mean that *any* simple model is useful so long as it displays your feature of interest (negative linear slope on a log-log plot). One glaring omission from the book is discussing exponents of power laws: what they mean, that small differences in exponents mean big differences in behaviour, and the potentially very large impact of errors in their estimations.
It gets really annoying that in many places, Bak wonders why biologist/geologists/economists/pick-a-field don't want to find general models that explain everything -- "don't want to" -- because that's what he claims to be doing. That is, he claims early on, is what physics does -- a "hard" science, his word, along with chemistry and molecular biology. All other sciences are "soft." And so is some physics -- physicists who do work Bak doesn't think is ambitious enough. Bak's conclusion is that the soft sciences don't look for general phenomena like he pursues because there are social constraints within the sciences not to. We truly cannot trust Bak here. He meets Stephen Jay Gould, insults his work, and makes nothing of the opportunity because he had a plane to catch. Fortunately the book is short. I hope there is a better, more nuanced, more mechanistic, less egotistical treatment of power laws out there.
The evolutionary models, for example, that Bak studied are essentially useless, and the phenomenon they proport to study, the feature that Bak says they must capture -- punctuated equilibrium -- is not a thing. Stephen Jay Gould claimed PE was a general trend, as do people outside evolutionary biology including physicists, who follow Gould's rhetoric in claiming Darwin was nothing but a gradualist. But biologists do not find PE to be useful, beginning with Darwin who was in no way a thorough-going gradualist. Bak continues the oft-misunderstood notion that micro- and macroevolution are fundamentally different processes, not true. This is something SJG kept pushing because of PE, but it just isn't true: some new things come into play during incipient speciation, but it is still all happening via microevolution.
Bak goes on to claim that we biologists don't have general evolutionary theories because our models don't accommodate mass extinctions like the Great Dying, the K-T boundary, and so on. How, exactly, are our biological models supposed to capture those? Biology can predict responses to those events, can track the reassembly of biota, but predict the events themselves? Bak so insists on his model that he claims that the meteor at the K-T boundary was probably not the main cause of the dinosaur extinction (!!), because the dinosaurs were probably on the way out already (!!). His "general" (simple, but wrong) model of evolution (speciation and extinction) produces catastrophic extinctions without outside catastrophes occurring. So, he insists that K-T (and other external causes of extinction) must be largely incidental because *his* models don't need them to show catastrophic extinctions. It is a *big* problem to wave away the K-T meteor so that his toy model can be true.
For a model of evolution, it may be that external catastrophes that affect speciation and extinction rates arrive with magnitudes and frequencies that follow a power law, whether they be meteors, volcanic events, anthropogenic sources, and so on. That's probably all the need we have for a power law affecting the outcomes of evolutionary models: to provide perturbations. There is no need for extinction catastrophes to arise endogenously within evolution models, and I would seriously question any model in which they do. "Mutational meltdowns" might occur during population contraction through Muller's-ratchet processes, when deleterious alleles fix again and again rather than purge, but if this occurs it would affect particular populations under particular conditions, mostly environmental degredation. Such conditions might arise simultaneously among many populations as a result of a common catastrophe, but on this scale it would be happening because of the catastrophe, not as a result of endogeneous processes. And it affects populations, not species; species-wide, it might facilitate speciation rather than extinction.
I would love a good book on power laws or log-log phenomena, but this is not it.
March 22, 2019
Very clear exposition of complex ideas. I especially enjoyed the last chapter where he presents his sales model. This is a book about power laws, where they are in nature and society, I can't imagine somebody being more open to wide audiences without being pedantic. Great read.
April 9, 2020
This is a great introduction to self organized criticality, even though the book was written a while ago. Some of the math went over my head, but the author provided plenty of different examples from various fields to drill down the idea. Now I'm looking for SOC everywhere.
October 3, 2017
Great book by a deep thinker. He has a childlike wonder at self organizing processes. Very much worth the read.
November 18, 2019
Showcases a nature principle that can be applied to many different systems (like the economy)
December 13, 2020
If you interest in complexity this is a great reading to connect the dots in your mind.
October 29, 2016
Per Bak wrote a very approachable book considering that self-organized criticality (SOC) is not a familiar concept. The way he presented the text is fun, intuitive and enrapturing. However, I feel that Bak "whined" a bit too much on how the scientists are disregarding his work and how traditional science is brushing SOC aside. I believe that SOC itself is an interesting lens to look at phenomena we fail to understand before, but that kind of whining narrative kind of tone down the importance of the message quite a bit.
Nonetheless, a great book to dive into for scientists. The text will make the paper references much easier to understand.
Nonetheless, a great book to dive into for scientists. The text will make the paper references much easier to understand.
March 4, 2014
A major question on "why self-organized criticality?" was unanswered in this book (or maybe it was mentioned and I missed it). For me, this book was not a fun and yet informative book; I found it very limited to a narrow subject without expanding on the implications. I admit that the last page of the book was spectacular: for me it was worth the whole book; the few paragraphs in that single page answered many of my questions! (or maybe I wouldn't have enjoyed that last page of the book if I had not read the whole book)
April 23, 2013
The author used excellent analogies, which enables readers to understand several concepts related to self-organized criticality (SOC). SOC impressed me in that this simple concept can be applied to a wide array of phenomena including landslides, volcanoes, evolution, brain activity, economic systems, and traffic jams. However, the author seems to have written the latter part of this book with less sincerity and devotion than the former part.
March 11, 2011
Even though the author reveals much more of his personality, warts and all (beginning with that humble title), than you find in most science books, I found this book pretty boring. Even though the idea of self-organized criticality is interesting, I wasn't so intrigued by the examples used to illustrate this concept, especially the sand piles.
February 27, 2016
Good read, although i'd gone to a better publisher. The central idea is great, although a bit over-drilled. It didn't need a book, and a few personal stories could've been lefy out.
All round, i liked it, and will serve me well in continuing my complexity ready moving on to Kauffman and Holland and Arthur, but a whole books was not necessary for the point to be made.
All round, i liked it, and will serve me well in continuing my complexity ready moving on to Kauffman and Holland and Arthur, but a whole books was not necessary for the point to be made.
Want to read
April 5, 2007lip-lover recommendation
May 9, 2012
The concept of self-organized criticality is very interesting, but ultimately this was a book about sand piles. Sand piles get boring after awhile.
July 7, 2013
An amazing work which shows the fractal nature of a VERY wide array of natural phenomena.
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