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Complexity

Complexity. Sorin Solomon, Racah Institute of Physics HUJ Israel Complex Multi-Agent Systems Division, ISI Turin. Lagrange Interdisciplinary Lab for Excellence In Complexity.

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Complexity

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  1. Complexity Sorin Solomon, Racah Institute of Physics HUJ Israel Complex Multi-Agent Systems Division, ISI Turin Lagrange Interdisciplinary Lab for Excellence In Complexity MORE IS DIFFERENT (Anderson 72)(more is more than more)Complex“Macroscopic” properties may be the collective effect of many simple “microscopic” components (and independent on their details) Phil Anderson “Real world is controlled … • by the exceptional, not the mean; • by the catastrophe, not the steady drip; • by the very rich, not the ‘middle class’. we need to free ourselves from ‘average’ thinking.”

  2. Extrapolation? ? 1cm The breaking of macroscopic linear extrapolation 1Kg 1Kg 101 97 99 1cm 1Kg 950C

  3. Semiotics and Ontology SocialScience Biology WordsMeaning ChemicalsCells IndividualsSociety Phase Transitions, clusters, scaling Computers BusinessAdministration BitsInformation items AtomsDrops CustomerMarket Economicsand Finance Statistical Physics Cognition NeuronsBrain TradersHerds

  4. Instead of temperature: • Exchange rate/interest rate • Value At Risk / liquid funds • Equity Price / Dividends • Equity Price / fundamental value • Political Activity • Education … 97 99 101 95

  5. CONCEPTUAL AND DISCIPLINARY JUMPS of the MORE IS DIFFERENT type Systems, Organisms health, perception self-non-self recognition Cells chemotaxis, metabolism DNA chains, proteins reproduction,evolution,synthesis Chemicals almost free particles

  6. The Multi-Agent Complex Systems Paradigm MICRO - the relevant microscopic degrees of freedom INTER - their fundamental interactions MACRO - the macroscopic emerging collective objects • Intrinsically (3x) interdisciplinary: • MICRO belongs to one science • MACRO to another science • Mechanisms: statistical mechanics (?) phase transitions, scale invariance, The challenge :transcend traditional disciplinary researchComplexity Research: More than a juxtaposition of expertises: a new grammar with new interrogative forms allowing the formulation of new questions. Grow a new generation of bi- or multi-lingual scientists.

  7. Microscopic Links, Macroscopic NetworksMICRO – Nodes, connections INTERACTIONS - Local changes (node / link (dis-) appearance)MACRO- Global connectivity, percolation, topology links site browse links Transitive link Copied site /gene New generation of network studies:Instead of study generic properties that are not specific to any particular system, Study specific macroscopic collective properties implied by specific elementary interactions.. site

  8. - Microscopic Immune Cells and Macroscopic HealthMICRO - Cells, Enzimes, Antigens, AntibodiesINTER -producing, destroying, changing state of cells/enzymesMACRO - immunity, health, infection, sickness, inflamation. REALITY Agents SIMULATION Losing All Battles and Wining the War; HIV time hierarchy: U Hershberg, Y Louzoun, H Atlan and S Solomon Physica A: 289 (1-2) (2001) pp.178-190 ; Antigen-receptor degeneracy and immunological paradigms Irun R. Cohen,, Uri Hershberg, Sorin SolomonMolecular Immunology 40 (2004) 993–996 Acute Phase T-cells HIV

  9. - Microscopic seeds and Macroscopic Oases MICRO –individual plants     INTER –growth, water fixation, MACRO – bushes, vegetation patches N.M. Shnerb, P. Sarah, H. Lavee, and S. Solomon Reactive glass and vegetation patterns Phys. Rev. Lett. 90, 38101 (2003) Semi-arid; patchy Desert;uniform Mediterranean; uniform

  10. - Microscopic Investors and Macroscopic CrashesMICRO - Investors, individual capital ,shares         INTER - sell/buy orders, gain/loss          MACRO - social wealth distribution, market price fluctuations (cycles, crushes, booms, stabilization by noise) “Levy, Solomon and Levy'sMicroscopic Simulation of Financial Markets points us towards the future of financial economics. If we restrict ourselves to models which can be solved analytically, we will be modeling for our mutual entertainment, not to maximize explanatory or predictive power."HARRY M. MARKOWITZ, Nobel Laureate in Economics

  11. Realistic macroscopic simulations require a new causal framework: discrete / delayed/ conditional / nested causalityinstead of the usual Markov infinitesimal one New mathematical concept: Markov Webs

  12. “Stock market shock explainedPhysicists model recent trading frenzy”1 October 2002 Realistic Continuous Time Simulation Platform

  13. - Microscopic Draws and Macroscopic Drawings MICRO - local line / motion features, mental states, mental eventsINTER - line breaks and mind events vs line/mind inertia.MACRO - drawing shapes, emergence of meaning Emergence of Representation in Drawing: The Relation Between Kinematic andReferential Aspects E Adi-Japha, I Levin and S. Solomon, Cognitive Development 13 (1998) 25 EMPTY SHELLS “looking for representational content” Breaks are correlated with a posteriori representation

  14. -Microscopic Concepts and Macroscopic Ideas MICRO - concepts, connections between conceptsINTER - creating/deleting connections between conceptsMACRO–Novel products, creative ideas, real-life problem solving Creative Sparks, J Goldenberg, D Mazursky, and S SolomonScience 285: 1495-1496, 1999; Templates of original innovation: Projecting original incremental innovations from intrinsic informationGoldenberg J. Mazursky D. Solomon S., (1999) Technological Forecasting and Social Change, May, Vol. 61/1 P. 1-12. Communication at the speed of sound

  15. Individual Losers and Collective Winners MICRO – individuals with arbitrary high death rateINTER – arbitrary low birth rate; arbitrary low density of catalisersMACRO –always resilient collective patches (THEOREM) The importance of being discrete: Life always wins on the surface N M. Shnerb, Y Louzoun, E Bettelheim, and S Solomon Proc. Natl. Acad. Sci. USA, 97/ 19, 10322-10324, Sep 12, 2000 http://xxx.lanl.gov/abs/adap-org/9912005 Proliferation and Competition in Discrete Biological Systems Y LouzounS Solomon, H Atlan and I R. Cohend Bulletin of Mathematical Biology Volume 65, Issue 3 , May 2003, P 375-396 SAME SYSTEM continuumdensity distributions - uniformdistribution- population extinction discrete individuals- self-organize in - localized adaptive patches- survival anddevelopment

  16. Logistic Multi-Agent Prediction <a>< 0 Prediction by Logistic Differential Equation a<0 1990 1991 1989 1992 Economy (89-92) vs.EDUCATION (‘88)note complete correspondence to educationAFTER (‘92) but NOT BEFORE(‘89) liberalization Nowak 1989

  17. Fractal Wealth Distribution: Scaling; Power laws No one however, has yet exhibited a stable social order, ancient or modern, which has not followed the Pareto pattern…Davis; Cowles Commission for Research in Economics Pareto’s curve … great generalizations of human knowledge.Snyder 1939 WALMART GATES Buffet ALLEN 20 Dell Zipf plot of the wealths of the investors in the Forbes 400 of 2003 vs. their ranks. The corresponding model results are shown in the in set.

  18. Distributionof individual wealth ~(by MACS Prediction) Distribution of globalfinancialfluctuations Levy Social equityis good for the financial stability!

  19. - Microscopic Customers and Macroscopic SalesMICRO– Customers, products / ideas / informationINTER– purchase, inform, learn, hear-sayMACRO– global trends, waves of sales (e.g. Tamaguchi), hits, flops, market fluctuations, anomalous diffusion Percolation transition From non-sales at all to a lot of salesSocial Percolators and Self-Organized CriticalityGerard Weisbuch , Sorin Solomon in: Economics with heterogeneous interacting agents, page 43.eds A.Kirman and J.B. Zimmermann, Lecture Notes in Economics and Mathematics, Springer, 2001 Theorem 60% 55% potential buyers 55% 0%sales 60% potential buyers 59.3

  20. 60% 55%

  21. fractal space distribution Prediction of campaign success (15/17) Goldenberg Air-view of a sub-urban neighborhood; crosses on the roofs indicate air-conditioner purchase

  22. Sales extrapolation formula vs microscopic representation CAR SALES in USA 1895-1930 Extrapolation • New Generation of Models:Take into account negative reaction to the propagation: • Negative word-of-mouth: unsatisfied customers influence their contacts in non-buying: anti-percolation. • anti-viruses propagating on “almost” the same network: role of additional links: antivirus arrives first. • Timing of transmission: not all contacts are always active

  23. Conclusions Complexity No Doctrina May be Unifying Language Simple “Microscopic Agents” Dynamics=> Macroscopic Complexity

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