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Universal laws and architectures: Theory and lessons from brains, bugs, nets, grids, docs, planes, fire, fashion, art, turbulence, music, buildings, cities, earthquakes, bodies, running, throwing, Synesthesia, spacecraft, statistical mechanics John Doyle 道陽 Jean-Lou Chameau Professor Control and Dynamical Systems, EE, & BioE Ca#1tech • Neuroscience + People care +Live demos! 1. 2. 3. 4. experiments data theory universals 8 Fragility 4 p l0 l z p2 ln z p 1 eye l0 l 1 Slow Act .1 fast slow delay vision .1s .05 vision .2 .5 Length Slow(meters) 1 Universal Fast laws VOR Inflexible Flexible thin small 1 Fast fragile Survive robust 10 fragile too fragile Flexible z p Inflexible z p complex Laws cheap Multiply thick big costly No tradeoff 0 10 -1 10 k 0 10 1 10 expensive Universal laws and architectures: Theory and lessons from brains, bugs, nets, grids, docs, planes, fire, fashion, art, turbulence, music, buildings, cities, earthquakes, bodies, running, throwing, Synesthesia, spacecraft, statistical mechanics Slow Fast Flexible General Inflexible Special Which blue line is longer? Which blue line is longer? Which blue line is longer? Which blue line is longer? Which blue line is longer? Slowest 3D + motion eye vision fast Act Slow color vision slow delay vision VOR Fast Flexible Inflexible See Marge Livingstone Stare at thegood. intersection This is pretty Layered Architecture DNA New Gene gene RNA Transcription Other Control RNAp mRNA Amino Acids Ribosomes Translation Slow Proteins Other HGT Cheap Control DNA repair Products Metabolism Mutation ATP DNA replication control feedbackSignal transduction Transcription Translation Metabolism Signal… Fast Costly Inflexible Flexible General Special vision Prefrontal Slow Fast Motor Fast Sense HGT DNA repair VOR Mutation DNA replication Apps Transcription Reflex OS OS Translation HW HW Metabolism Dig. Dig. Digital Signal Lump. Lump. Lump. Lumped Distrib. Distrib. Distrib. Distrib. Distrib. Inflexible Flexible Special General Compute Comms Gödel Shannon Turing Von Neumann Theory? Deep, but fragmented, incoherent, incomplete Nash Carnot Boltzmann Bode Heisenberg Control, OR Einstein Physics Compute Turing Delay and risk are most important Bode Control, OR • Worst-case (“risk”) • Time complexity (delay) Computation for control • Off-line design • On-line implementation • Learning and adaptation • Worst-case (“risk”) • Delay severely degrades robust performance Compute Communicate Turing Shannon Delay and risk are most important Delay and risk are least important Carnot Bode Control, OR Boltzmann Heisenberg Einstein Physics Communicate • Space complexity Shannon • Average case (risk neutral) • Random ensembles • Asymptotic (infinite delay) Dominates “high impact science” literature Carnot Boltzmann Heisenberg Einstein Physics Compute Communicate Turing Delay and risk are most important Shannon New progress! Delay and risk are least important Bode Control, OR Physics .2 m 2 s/m 1 Axon size and speed C delay sec/m .1 20 m Aα .01 .008 s/m .1 .01 1 1 diam(m) 10 area 100 1 C delay sec/m .1 Aγ Aδ Aβ .01 .1 .01 1 1 Aα diam(m) 10 area 100 Axon size and speed unmyelinated 1 delay sec/m .1 myelinated .01 .1 .01 1 1 diam(m) 10 area 100 .1 m 1 delay sec/m 10 m .1 myelinated myelin 1 m .01 .1 .01 1 1 diam(m) 10 area m 2 100 Why such extreme diversity in delay and size? Other myelinated 1 delay sec/m Retinal ganglion axons? .1 Why no diversity in VOR? VOR .01 .1 .01 1 1 diam(m) 10 area 100 Fractal wrongness • • • • 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 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. Trivial examples Doyle, Csete, Proc Nat Acad Sci USA, JULY 25 2011 “New sciences” of “complexity” and “networks”? Science as • Pure fashion • Ideology • Political • Evangelical • Nontech trumps tech worse • Edge of chaos • Self-organized criticality • Scale-free “networks” • Creation “science” • Intelligent design • Financial engineering • Risk management • “Merchants of doubt” •… Complex systems? Fragile Even small amounts can create bewildering complexity • • • • • • • • • • Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Complex systems? Robust • • • • • • • • • • Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Fragile • • • • • • • • • • Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Complex systems? Robust complexity • • • • • • • • • • Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … • • • • • • • Resources Controlled Organized Structured Extreme Architected … • 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) Fragile complexity • • • • • • • • • • Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … New words Emergulent Emergulence at the edge of chaocritiplexity Fragile complexity • • • • • • • • • • Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Things we won’t get to Attention/Awareness (Graziano) Compassion Consciousness Free will Me vs We Us vs Them Things we won’t get to Things we won’t get to Good/Evil Things we won’t get to Things we won’t get to
