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Universal laws (and architectures): networks, bugs, brains, dance, art, music, literature, fashion John Doyle John G Braun Professor Control and Dynamical.

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Presentation on theme: "Universal laws (and architectures): networks, bugs, brains, dance, art, music, literature, fashion John Doyle John G Braun Professor Control and Dynamical."— Presentation transcript:

1 Universal laws (and architectures): networks, bugs, brains, dance, art, music, literature, fashion John Doyle John G Braun Professor Control and Dynamical Systems, EE, & BioE C a # l t e c h and zombies

2 accessible accountable accurate adaptable administrable affordable auditable autonomy available credible process capable compatible composable configurable correctness customizable debugable degradable determinable demonstrable dependable deployable discoverable distributable durable effective efficient evolvable extensible fail transparent fast fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant reliable repeatable reproducible resilient responsive reusable robust safety scalable seamless self-sustainable serviceable supportable securable simplicity stable standards compliant survivable sustainable tailorable testable timely traceable ubiquitous understandable upgradable usable Requirements on systems and architectures

3 accessible accountable accurate adaptable administrable affordable auditable autonomy available credible process capable compatible composable configurable correctness customizable debugable degradable determinable demonstrable dependable deployable discoverable distributable durable effective efficient evolvable extensible fail transparent fast fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant reliable repeatable reproducible resilient responsive reusable robust safety scalable seamless self-sustainable serviceable supportable securable simplicity stable standards compliant survivable sustainable tailorable testable timely traceable ubiquitous understandable upgradable usable Requirements on systems and architectures When concepts fail, words arise. Mephistopheles, Faust, Goethe Mephistopheles. …Enter the templed hall of Certainty. Student. Yet in each word some concept there must be. Mephistopheles. Quite true! But don't torment yourself too anxiously; For at the point where concepts fail, At the right time a word is thrust in there… Mephistopheles. …Enter the templed hall of Certainty. Student. Yet in each word some concept there must be. Mephistopheles. Quite true! But don't torment yourself too anxiously; For at the point where concepts fail, At the right time a word is thrust in there…

4 When concepts fail, words arise. Mephistopheles, Faust, Goethe Mephistopheles. …Enter the templed hall of Certainty. Student. Yet in each word some concept there must be. Mephistopheles. Quite true! But don't torment yourself too anxiously; For at the point where concepts fail, At the right time a word is thrust in there… Concrete case studies Theorems

5 Neuroscience Tech nets Cell biology Medical physiology Smartgrid, cyber-phys Wildfire ecology Earthquakes Lots of aerospace Physics: –turbulence, –stat mech (QM?) “Toy”: –Lego –clothing, fashion Buildings, cities Synesthesia Case studies

6 Neuroscience Tech nets Cell biology Medical physiology Smartgrid, cyber-phys Wildfire ecology Earthquakes Lots of aerospace Physics: –turbulence, –stat mech (QM?) “Toy”: –Lego –clothing, fashion Buildings, cities Synesthesia Case studies

7 Cloth Thread Fiber Diverse Garments Xform Diverse outfits Constraints that deconstrain Protocols The layered architecture of clothing

8 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 Most accessible No math

9 Architecture case studies comparison BacteriaInternetBrain Understood? By scientists? Live demos?!? Who cares? Design quality?    Math? 

10 Fast Slow Flexible Inflexible VOR d = hand - vision d = head e=d-u Act u slow delay VOR fast vision Speed and flexibility tradeoffs Vestibular Ocular Reflex (VOR)

11 A handwaving explanation illustrating fundamental tradeoffs eye headhand vision eye Head and hand motion Compensating eye movement

12 eye head hand vision eye EasyHard Why? StillMove StillEasy MoveHardHardest Head Hand Accident or necessity?

13 d = disturbance = hand - vision error=d-u Act u u = eye position eye vision hand eye

14 d = hand - vision e=d-u Act u slow delay eye hand vision slow eye Hard

15 - vision d = head e=d-u Act u eye head vision eye

16 - vision d = head e=d-u Act u VOR fast Easy eye head vision eye fast

17 - d = head e=d-u Act u VOR fast Easy eye head eye fast Doesn’t depend on vision Works in the dark

18 - vision d = head e=d-u Act u VOR fast Easy eye head vision eye fast

19 d = hand - vision d = head e=d-u Act u slow delay VOR fast eye headhand vision eye slow fast

20 Standing and seeing 2 legs1 leg eyes openEasiestHarder eyes shutEasyHardest Why? Vision is important in balance?

21 eyes2 legs1 leg openEasiestHarder shutEasyHardest Fast Slow Flexible Inflexible VOR vision Better at low frequencies Better at high frequencies

22 Laws and architectures: lessons from VOR and vision Robust control –nested, diverse feedbacks –hidden, automatic, unconscious Speed vs flexibility tradeoffs (laws?) Good architectures manage tradeoffs Evolution: necessity vs accident? Universal?

23 efficient Fast Slow Flexible Inflexible Global Local (Overly) Simple dichotomous tradeoff pairs

24 accessible accountable accurate adaptable administrable affordable auditable autonomy available compatible composable configurable correctness customizable debugable degradable determinable demonstrable dependable deployable discoverable distributable durable effective evolvable extensible fail transparent fast fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant reliable repeatable reproducible resilient responsive reusable safety scalable seamless self-sustainable serviceable supportable securable simple stable standards survivable tailorable testable timely traceable ubiquitous understandable upgradable usable efficient robust sustainable Fast Slow Flexible Inflexible Global Local Simple dichotomous tradeoff pairs PCA  Principal Concept Analysis

25 Formalize architecture as constraints Good architecture = “constraints that deconstrain” (G&K) Most effective architectures are layered Constraints on system and components –System level function and uncertainty –Component level capability and uncertainty Laws, hard limits, tradeoffs Protocols (are the essence of constraints that deconstrain)

26 Slow Fast Flexible Inflexible Impossible Architecture Architecture (constraints that deconstrain) General Special Want fast, flexible, and general

27 Fast Slow Flexible Inflexible Speed and flexibility tradeoffs both vision VOR Combining controls

28 Fast Slow Flexible Inflexible both laws? (constraints) Speed and flexibility tradeoffs Accident or necessity? vision VOR

29 Sensing fast and slow Applies to vision and hearing? For action (fast, luminance) For “perception” (slow, includes color)

30 Stare at the intersection

31

32 This is pretty good.

33

34 Universal tradeoffs? Fast Slow Flexible Inflexible Learning Evolution

35 SensoryMotor Prefrontal Striatum Slow Flexible Slow Flexible Learning Ashby & Crossley Slow Reflex (Fastest, Least Flexible)

36 SensoryMotor Prefrontal Striatum Fast Inflexible Fast Inflexible Slow Flexible Slow Flexible Learning Reflex (Fastest, Least Flexible) Ashby & Crossley Learning can be very slow.

37 Sense Universal tradeoffs? Fast Slow Flexible Inflexible Motor Prefrontal Fast Learn Reflex Evolve Learning can be very slow. Evolution is even slower.

38 Sense Universal architectures Motor Prefrontal Fast Reflex Evolution on long timescales Learn Evolve Evolution on long timescales

39 accessible accountable accurate administrable affordable auditable autonomy available credible process capable compatible composable configurable correctness customizable debugable degradable determinable demonstrable dependable deployable discoverable distributable durable effective efficient extensible fail transparent fault-tolerant fidelity inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant repeatable reproducible responsive reusable safety scalable seamless self-sustainable serviceable supportable securable simplicity standards compliant survivable sustainable tailorable testable timely traceable ubiquitous understandable upgradable usable Many more dimensions robust resilient stable adaptable evolvable reliable flexible fast

40 Universal laws (constraints) Well known from physics and chemistry: Classical: gravity, energy, carbon,… Modern: speed of light, “Heisenberg”, … Not so much: Robustness –Critical to study of complex systems –Unknown outside narrow technical disciplines –Theorems, not mere metaphors

41 Modern Turing tradeoffs: PC, smartphone, router, etc Apps OS HW Digital Lumped Distrib. OS HW Digital Lumped Distrib. Digital Lumped Distrib. Lumped Distrib. Fast Slow Flexible Inflexible Accident or necessity? General Special

42 SensoryMotor Prefrontal Striatum Reflex Learning Catabolism AA RN A transl. Proteins xRNA transc. Precursors Nucl. AA DNA Repl. Gene ATP Ribosome RNAp DNAp Software Hardware Digital Analog Flexible/ Adaptable/ Evolvable Horizontal Gene Transfer Horizontal App Transfer Horizontal Meme Transfer Depends crucially on layered architecture

43 Catabolism AA RN A transl. Proteins xRNA transc. Precursors Nucl. AA DNA Repl. Gene ATP Ribosome RNAp DNAp Horizontal Gene Transfer Sequence ~100 E Coli (not chosen randomly) ~ 4K genes per cell ~20K different genes in total ~ 1K universally shared genes ~ 300 essential (minimal) genes See slides on bacterial biosphere

44 Mechanisms in molecular biology Think of this as a “protocol stack” 0.HGT (Horizontal Gene Transfer) 1.DNA replication 2.DNA repair 3.Mutation 4.Transcription 5.Translation 6.Metabolism 7.Signal transduction 8.…

45 Think of this as a “protocol stack” 0.HGT 1.DNA replication 2.DNA repair 3.Mutation 4.Transcription 5.Translation 6.Metabolism 7.Signal transduction 8.… Highly controlled Control 1.0

46 Think of this as a “protocol stack” 0.HGT 1.DNA replication 2.DNA repair 3.Mutation 4.Transcription 5.Translation 6.Metabolism 7.Signal transduction 8.… Highly controlled Highly controlled ?!? Control 2.0

47 Apps OS HW Digital Lumped Distrib. OS HW Digital Lumped Distrib. Digital Lumped Distrib. Lumped Distrib. Fast Costly Slow Cheap Flexible Inflexible General Special HGT DNA replication DNA repair Mutation Transcription Translation Metabolism Signal…

48 Prosen- cephalon Telen- cephalon Rhinencephalon, Amygdala, Hippocampus, Neocortex, Basal ganglia, Lateral ventricles Dien- cephalon Epithalamus, Thalamus, Hypothalamus, Subthalamus, Pituitary gland, Pineal gland, Third ventricle Brain stem Mesen- cephalon Tectum, Cerebral peduncle, Pretectum, Mesencephalic duct Rhomb- encephalon Meten- cephalon Pons, Cerebellum Myelen- cephalon Medulla oblongata Spinal cord CNS HW “stack” Brain

49 Slow Fast Flexible Inflexible Undecidable Universal Turing Machine Architecture (constraints that deconstrain) General Special Laws and architectures (Turing, 1936) Turing

50 Fast Slow Flexible/ General Inflexible/ Specific UndecidableNPP hard limits Really slow Computational complexity Decidable

51 Flexible/ General Inflexible/ Specific NP P Decidable Computational complexity PSPACE  NP  P  NL PSPACE ≠ NL NL PSPACE Space is powerful and/or cheap.

52 Fast Slow Flexible/ General Inflexible/ Specific UndecidableNPP hard limits Really slow These are hard limits on the intrinsic computational complexity of problems. Decidable Must still seek algorithms that achieve the limits, and architectures that support this process.

53 Control, OR CommsCompute Physics Shannon Bode Turing Gödel Einstein Heisenberg Carnot Boltzmann Theory? Deep, but fragmented, incoherent, incomplete Nash Von Neumann

54 Control, OR CommunicateCompute Physics Shannon Bode Turing Einstein Heisenberg Carnot Boltzmann Delay and risk are most important Delay and risk are least important

55 Control, OR Compute Bode Turing Delay and risk are most important Worst-case (risk) Time complexity (delay) Worst-case (risk) Delay severely degrades robust performance

56 Communicate Physics Shannon Einstein Heisenberg Carnot Boltzmann Delay and risk are least important Average case (risk neutral) Random ensembles Asymptotic (infinite delay) Space complexity

57 Control, OR CommunicateCompute Physics Shannon Bode Turing Delay and risk are most important Delay and risk are least important New progress!

58 Slow Fast Flexible Inflexible Impossible Architecture Architecture (constraints that deconstrain) General Special How general is this picture?

59 simple tech complex tech How general is this picture? wasteful fragile efficient robust Implications for human evolution? Cognition? Technology? Basic sciences?

60 Chandra, Buzi, and Doyle UG biochem, math, control theory Most important paper so far.

61 simple enzyme Fragility Enzyme amount complex enzyme Theorem! z and p functions of enzyme complexity and amount Savageaumics

62 Simple, but too fragile complex No tradeoff Hard tradeoff in glycolysis is robustness vs efficiency absent without autocatalysis too fragile with simple control plausibly robust with complex control expensive fragile

63 hard harder hardest! Easy to prove using simple models. What is sensed matters. Why?

64 This is a cartoon, but can be made precise. Fragility change length L change sense down

65 I recently found this paper, a rare example of exploring an explicit tradeoff between robustness and efficiency. This seems like an important paper but it is rarely cited.

66 1m1m Bacteria Phage

67 Multiply Survive Phage lifecycle Infect Lyse

68 slow fragile fast robust Survive Multiply thin small Good architectures? Hard limits? thick big Capsid Genome

69 Universal architectures What can go wrong?

70 Horizontal Bad Gene Transfer Horizontal Bad App Transfer Horizontal Bad Meme Transfer Parasites & Hijacking Fragility? Exploiting layered architecture Virus

71 Unfortunately, not intelligent design Ouch.

72 Why? left recurrent laryngeal nerve

73 Why? Building humans from fish parts. Fish parts

74 It could be worse.

75 Original design challenge? TCP/ IP Deconstrained (Hardware) Deconstrained (Applications) Constrained Expensive mainframes Trusted end systems Homogeneous Sender centric Unreliable comms Facilitated wild evolution Created whole new ecosystem completely opposite Networked OS

76 App IPC Global and direct access to physical address! DNS IP addresses interfaces (not nodes) caltech.edu?

77 App IPC Global and direct access to physical address! Robust? Secure Scalable Verifiable Evolvable Maintainable Designable … DNS IP addresses interfaces (not nodes)

78 Naming and addressing need to have scope and resolved within layer translated between layers not exposed outside of layer Related “issues” VPNs NATS Firewalls Multihoming Mobility Routing table size Overlays …

79 ? Deconstrained (Hardware) Deconstrained (Applications) Next layered architectures Constrained Control, share, virtualize, and manage resources Comms Memory, storage Latency Processing Cyber-physical Few global variables Don’t cross layers

80 Every layer has different diverse graphs. Architecture is least graph topology. Architecture facilitates arbitrary graphs. Persistent errors and confusion (“network science”) Physical IP TCP Application

81


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