the problem of fractal wrongness
DESCRIPTION
The problem of Fractal Wrongness. Great work built on weak foundation (science) Hope I can learn and help (shake things up ). Fractal wrongness. Emergence Risk. Fractal wrongness. Emergence Risk Sustainability Autocatalysis Global !#%&!?!? Evolution Technology Markets, finance, … - PowerPoint PPT PresentationTRANSCRIPT
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• Great work built on weak foundation (science) • Hope I can learn and help (shake things up)
The problem of Fractal Wrongness
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Fractal wrongness• Emergence• Risk
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Fractal wrongness
Much (most?) of what many (most?) believe is obviously false.
• Emergence• Risk• Sustainability• Autocatalysis• Global !#%&!?!?• Evolution• Technology• Markets, finance, …• …
• Robustness• Efficiency• Scale• Dynamics• Nonlinearity• Nonequlibrium• Open• Feedback• Adaptation• Intractability• …
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• Wrongness everywhere, every scale, “truthiness”• Involving anything “complex”…• Wild success: religion, politics, consumerism, …• Debates focused away from real issues…
• Even if erased, sustainability challenges remain• Hopeless if it persists
• I’ll set aside all of this for now, and “zoom in” on the world of PhD research/academic scientists
• BTW, excellent case study in infectious hijacking
Fractal wrongness
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Fractal wrongness (PhDs only)
Much (most?) of what many (most?) believe is obviously false.
• Emergence• Risk• Sustainability• Autocatalysis• Global !#%&!?!?• Evolution• Technology• Markets, finance, …• …
• Robustness• Efficiency• Scale• Dynamics• Nonlinearity• Nonequlibrium• Open• Feedback• Adaptation• Intractability• …
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…Extinction simulations have already been performed in a variety of network contexts, including the World Wide Web (WWW) [2], metabolic networks [26], protein networks [25],…
[2] R. Albert, H. Jeong, and A.-L. Barabasi. Error and attack tolerance of complex networks. Nature, 406:378{382, 2000.[25] H. Jeong, S. P. Mason, A.-L. Barabasi, and Z. N. Oltvai. Lethality and centrality in protein networks. Nature, 411:41, 2001.[26] H. Jeong, B. Tombor, R. Albert, Z. N. Oltvai, and A.-L. Barabasi. The large-scale organization of metabolic networks. Nature, 407:651{654, 2000.
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• “Wrongness” everywhere, every scale • Involving “complexity”• Wild success: high impact journals, funding
agencies, popular science, policy…• Debates shifted away from real issues…
• Even if erased, huge challenges remain• Hopeless if it persists?
• BTW, excellent case study in infectious hijacking
Fractal wrongness (PhDs only)
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• “Wrongness” everywhere, every scale • Involving “complexity”• Wild success: high impact journals, funding
agencies, popular science, policy…• Debates shifted away from real issues…
• Even if erased, huge challenges remain• Hopeless if it persists?
• I’ll set this aside for now, and “zoom in” to a small spot (within science) with a solid foundation (but a huge spot in math and engineering)
Fractal wrongness (PhDs only)
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Rigorous foundations
• Emergence• Risk• Autocatalysis• Global !#%&!?!?• Evolution• Technology• Markets, finance, …• …
• Robustness• Efficiency• Scale• Dynamics• Nonlinearity• Nonequlibrium• Open• Feedback• Adaptation• Intractability• …
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A source of fractal wrongness we need to remove
Large, thin, nonconvex
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Software
Hardware
DigitalAnalog
“solution sets” (a la Marder, Prinze, etc)
large, thin, nonconvex
All systems
Functional
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Meaning
Syntax
WordsLetters
Layered language?
large, thin, nonconvex
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Letters and words
• 9 letters: adeginorz• 9!= 362,880 sequences of 9 letters• Only “organized” is a word
1 << (# words) << (# non-words) large thin
Meaning
Syntax
WordsLetters
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Language?
Almost all• grammatical sentences are meaningless• sequences of words are ungrammatical• sequences of letters are not words• collections of symbols are not letters
Meaning
Syntax
WordsLetters
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• large, thin, nonconvex• # of order parameters • with tuning, Watson beat
humans at Jeopardy
• What are the protocols and architecture?
Meaning
Syntax
WordsLetters
Almost all• grammatical sentences are meaningless• sequences of words are ungrammatical• sequences of letters are not words• collections of symbols are not letters
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large thin 1 << # toys << # piles
toyspile
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large thin 1 << # toys << # piles
pile
“order for free?”
emergenceedge of chaosself-organized criticalityscale-free???
statistical physicsrandom ensemblesminimally tunedphase transitionsbifurcations
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large thin 1 << # toys << # piles
toyspile
“order for free?”
nonconvex
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Computer programs
• Almost any computer language• Large # of working programs• larger # of non-programs• “Nonconvex” = simple mashups of working
programs don’t work• Need architecture to organize working
programs
1 << (# programs) << (# non-programs) large thin
Software
Hardware
DigitalAnalog
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Computer programs
Software is not an emergent property of hardware
• morphodynamics and “top-down causality” ?
• teleodynamics?
Software
Hardware
DigitalAnalog
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Meaning
Syntax
WordsLetters
Software
Hardware
DigitalAnalog
Analog
digital
All “code”
functional software
large, thin, nonconvex
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This paper aims to bridge progress in neuroscience involving sophisticated quantitative analysis of behavior, including the use of robust control, with other relevant conceptual and theoretical frameworks from systems engineering, systems biology, and mathematics.
Doyle, Csete, Proc Nat Acad Sci USA, JULY 25 2011
Trivial examples
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Universal “laws” (constraints)• Some constraints on bio & tech rise “bottom up”
from physics/chemistry– Gravity– Speed of light– Energy– Carbon– Other small moieties (e.g. redox, …)… more later?
• Emergence?
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Components
Physical laws as constraints on components
• Gravity• Speed of light• Energy• Carbon• Other small moieties (e.g. redox, …)… more later
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Components
Emergent phenomena?
Biology & technology not emergent in any useful sense
• Dissipation, friction• Liquids, gases, fluid dynamics• Phase transitions, homogeneous turbulence, etc• etc etc
Huge gap
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Components
Emergent phenomena?
Biology & technology not emergent in any useful sense
Huge gap• Dissipation, friction• Liquids, gases, fluid dynamics• Phase transitions• etc etc
Risk not emergent in any useful sense?
Gap?
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Components
Emergent phenomena?
Biology & technology not emergent in any useful sense
Huge gap• Dissipation, friction• Liquids, gases, fluid dynamics• Phase transitions• etc etc
Risk not emergent in any useful sense?
Gap?
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Components
Emergent phenomena?
Big gap
HUGE gap
Top down causality (Juarrero)Morphodynamics (Deacon)
Teleodynamics (Deacon)
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wasteful
fragile
Laminar
Turbulentefficient
robust
Laminar
Turbulent
?Needs active
ActivePassive
ClassicalQuantum
LumpedDistributePassive
Lossless
coherent story here, but haven’t figured out best way to explain… working on it…
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Emergence?
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“New sciences” of “complexity” and “networks”? worse
• Edge of chaos• Self-organized criticality• Scale-free “networks”• Creation “science”• Intelligent design• Financial engineering• Risk management• “Merchants of doubt”• …
Science as • Pure fashion• Ideology• Political• Evangelical• Nontech trumps tech
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simple enzyme
Fragility
Enzyme amount
complex enzyme
ln z pz p
2 20
1 ln lnz z pS j dz z p
Theorem!
z and p functions of enzyme complexity
and amount
Savageaumics
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Fragilityhard limits
simple
Overhead, waste
complex
• General• Rigorous• First principle
• Domain specific• Ad hoc• Phenomenological
Plugging in domain details
?
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Control Comms
Physics
Wiener
BodeKalman
Heisenberg
Carnot
Boltzmann
robust control
• Fundamental multiscale physics• Foundations, origins of
– noise – dissipation– amplification– catalysis
• General• Rigorous• First principle
?
Shannon
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What I’m not going to talk much about
• It’s true that most “really smart scientists” think almost everything in these talks is nonsense
• Why they think this• Why they are wrong
• Time (not space) is our problem, as usual• Don’t have enough time for what is true, so have
to limit discussion of what isn’t• No one ever changes a made up mind (almost)• But here’s the overall landscape
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Stat physics
Complex networks
PhysicsHeisenberg
Carnot
Boltzmann
Control Comms
Compute
“New sciences” of complexity and networksedge of chaos, self-organized
criticality, scale-free,…
Wildly “successful”
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D. Alderson, NPS 37
Popular but wrong
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Complex systems?Fragile
• Scale• Dynamics• Nonlinearity• Nonequlibrium• Open• Feedback• Adaptation• Intractability• Emergence• …
Even small amounts can create bewildering complexity
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Complex systems?Fragile
• Scale• Dynamics• Nonlinearity• Nonequlibrium• Open• Feedback• Adaptation• Intractability• Emergence• …
• Scale• Dynamics• Nonlinearity• Nonequlibrium• Open• Feedback• Adaptation• Intractability• Emergence• …
Robust
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Complex systems?
• Resources• Controlled• Organized• Structured• Extreme• Architected• …
Robust complexity
• Scale• Dynamics• Nonlinearity• Nonequlibrium• Open• Feedback• Adaptation• Intractability• Emergence• …
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• These words have lost much of their original meaning, and have become essentially meaningless synonyms• e.g. nonlinear ≠ not linear
• Can we recover these words?
• Idea: make up a new word to mean “I’m confused but don’t want to say that” • Then hopefully we can take these words back (e.g. nonlinear = not linear)
• Scale• Dynamics• Nonlinearity• Nonequlibrium• Open• Feedback• Adaptation• Intractability• Emergence• …
Fragile complexity
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New words Fragile
complexity
Emergulent
Emergulence at the edge of
chaocritiplexity
• Scale• Dynamics• Nonlinearity• Nonequlibrium• Open• Feedback• Adaptation• Intractability• Emergence• …
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doesn’t work
Stat physics
Complex networks
Alderson & Doyle, Contrasting Views of
Complexity and Their Implications for
Network-Centric Infrastructure,
IEEE TRANS ON SMC,
JULY 2010
“New sciences” of complexity and networksedge of chaos, self-organized
criticality, scale-free,…
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Stat physics
Complex networks
PhysicsHeisenberg
Carnot
Boltzmann
Control Comms
Compute
Complex systems?
Jean Carlson, UCSB Physics
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Stat physics
Complex networks
PhysicsHeisenberg
Carnot
Boltzmann
Control
Alderson &Doyle, Contrasting Views of Complexity and Their
Implications for Network-Centric Infrastructure,
IEEE TRANS ON SMC, JULY 2010
Sandberg, Delvenne, & Doyle, On Lossless Approximations, the Fluctuation-Dissipation Theorem, and Limitations of Measurement,IEEE TRANS ON AC, FEBRUARY, 2011
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Stat physics,
Complex networks
PhysicsHeisenberg
Carnot
Boltzmann
fluids, QM
“orthophysics”From prediction
to mechanism to control
Fundamentals!
Sandberg, Delvenne, & Doyle, On Lossless Approximations, the Fluctuation-Dissipation Theorem, and Limitations of Measurement,IEEE TRANS ON AC, FEBRUARY, 2011
“The last 70 years of the 20th century will be viewed as the dark ages of theoretical physics.” (Carver Mead)
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accessibleaccountableaccurateadaptableadministrable
auditableautonomyavailablecompatiblecomposable configurablecorrectnesscustomizabledebugable
determinabledemonstrable
dependabledeployablediscoverable distributabledurableeffective
evolvableextensiblefailure transparentfault-tolerantfidelityflexibleinspectableinstallableIntegrityinterchangeableinteroperable learnablemaintainable
manageablemobilemodifiablemodularnomadicoperable
portableprecisionpredictableproducible
recoverablerelevantreliablerepeatablereproducibleresilientresponsive
safety scalable
serviceablesupportablesecurable
stable
survivable
tailorabletestabletimelytraceable
upgradable
Lumping requirements into simple groups
robust
A system can be efficient
using a resource
or producingwaste
But can be
inefficientfor differentresources
orwaste
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Efficiency tradeoffs
efficientwith
resource 1
wasteful with
resource 1
efficientwith
resource 2
wasteful with
resource 2
Ideally
AchievableNot
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Efficiency tradeoffs
efficient wasteful
efficient
wasteful
Not?
Distance running
digesting raw vegs
humans
cattle
chimpspronghorn?
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accessibleaccountableaccurateadaptableadministrable
auditableautonomyavailablecompatiblecomposable configurablecorrectnesscustomizabledebugable
determinabledemonstrable
dependabledeployablediscoverable distributabledurableeffective
evolvableextensiblefailure transparentfault-tolerantfidelityflexibleinspectableinstallableIntegrityinterchangeableinteroperable learnablemaintainable
manageablemobilemodifiablemodularnomadicoperable
portableprecisionpredictableproducible
recoverablerelevantreliablerepeatablereproducibleresilientresponsive
safety scalable
serviceablesupportablesecurable
stable
survivable
tailorabletestabletimelytraceable
upgradable
Lumping requirements into simple groups
robust
A system can be robust
for a property
and aperturbation
But can be fragile
for a differentproperty
orperturbation
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Robustness tradeoffs
robustto 1
fragileto 1
robustto 2
fragileto 2
Ideally
Achievable
Not
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Robustness tradeoffs
robust
fragile
fast
slow
Not
Sprinting
Tree climbing
humans
chimps
cheetahs
leopards
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Robustness/efficiency tradeoffs
robust
fragile
efficient Inefficient
Not
Distance running
Tree climbing humans
chimps
kangeroos
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Robustness tradeoffs
robustto 1
fragileto 1
robustto 2
fragileto 2
Ideally
Achievable
Not