Multi-Agent Complex Systems - wide range of ideas, techniques and applications in - Health (disease spread), - Biology (immune system) - Culture (economic value of cultural environment), Governance … Desert Reclaim, Economic Sustainability, Financial Stability Real Estate Policy, Immigration effects, Social Policy… - cannot be even enumerated in a short talk. This talk limited to: specific examples of theoretical scientific concepts (even rigorous theorems) leading to concrete applications of interest to policy makers (most of the present audience)

Theoretical abstract: - the emergence of resilient collective objects with adaptive behavior that have fractal / scaling / singular geometry and lead to intermittent (Levy) fluctuations of the global system Multi-Agent Logistic systems display - the spontaneous emergence of spatio-temporal localized phases that break spontaneously the translational space time symmetry and This is proven both numerically and theoretically

Application abstract: The Multi-Agent Complex Systems approach identifies -singular local elements of growth (even at early stages where, as whole, the system seems in regress). - spatio-temporal patterns of resources and - socio-economic / human interactive causal mechanisms leading to growth (e.g. education / cultural level / tradition). In the concrete case of post-liberalization Poland. - identifies emergence of resilient, sustainable, developing patterns likely to support sustainable global growth - prediction of (space-time) singular fluctuation patterns that may lead to widening social inequality and economic instability (but also to novelty emergence). The classical paradigms fail in predicting emergence of novelty / development. - Propose extension of study to other regions (Piemonte…)

Solution:  < 0 “almost all the social phenomena … obey the logistic growth” Elliot W Montroll I would urge… logistic equation early in the education … in the everyday world of politics and economics Lord Robert May Size - Nonlinear Terms (Competion/Saturation)  Growth ~  Size Logistic Equation (Mathus-Verhulst-Lotka-Volterra-Eigen-Schuster

Multi-Agent Complex Systems Paradigm: In reality, in Growth ~  Size,  is the result of many spatio-temporal distributed discrete individual contributions rather then totally uniform and static

Instead: emergence of singular spatio-temporal localized collective islands with adaptive self-serving behavior => resilience and sustainability even for << 0 ! Multi-Agent Complex Systems (MACS) Implications: one can prove rigorously that the DE prediction (uniform spatial and temporal decay): Logistic Differential Equation  < 0 Is ALWAYS wrong ! Logistic MACS     prediction

ECONOMIC Clustering Development after economic liberalization of Poland: year 0 Andrzej Nowak lab Poland Post-Liberalization Social-Economic-Political Development: MACS wins over DE Seemingly similar regions before liberalization

ECONOMIC Clustering Development after economic liberalization of Poland: year 1 MACS DE Nowak Emerges island of growth Large region of decay First year: Global Decay; - MACS predicts Future Growth - DE predicts continuous decay (based on the same Logistsic parameters !)

ECONOMIC Clustering Development after economic liberalization of Poland: year Yr2:Globally, the situation seems getting worse and worse Most regions are devastated But MACS sees already nuclei of growth

ECONOMIC Clustering Development after economic liberalization of Poland: year MACS DE MACS wins over DE (for the same Logistic parameters) Development spreads from the nuclei to the rest of the country

What were the A’s ?

EDUCATION (‘88) (partial answer) What were the A’s ? Nowak

Economic Growth is in turn “A’s” for Political Transformation Voting for Reformist Parties Nowak

fractal space-time distribution Prediction of campaign success (15/17) Goldenberg

Desertification / Reclaim patterns ( patchy organic matter distribution ) Mediterranean; uniform 500mm Semi-arid; patchy Desert;uniform 200mm Lavee+Sarah

Piemonte Belarus Piemonte Romania

Infinite Competition Range =Globalization (efficient but unstable fluctuations) Intermediate Range Zero Range=Local Consumption Economy (inefficient but very stable (if population is stable))

Distribution of individual wealth ~ (by Prediction) Distribution of market fluctuations Social equity is good for the financial stability ! Levy

Other Crucial real Fact: Scaling; Power laws Zipfplot of thewealthsof the investors in the Forbes 400 of 2003 vs. their ranks. The corresponding model results are shown in the inset. Dell Buffet 20 ALLEN GATES WALMART 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 real world is controlled by the ‘tails’ of distributions… by the exceptional, not the mean; by the catastrophe, not the steady by the very rich, not the ‘middle class’. We need to free ourselves from ‘average’ thinking Phil W Anderson

Logistic systems=> Pareto Laws Theorem : Multi-Agent Complex The 100 year old Pareto puzzle is solved by combining the 100 year old logistic Lotka-Volterra equation with the 100 year old Boltzmann Statistical Mechanics Experimental Confirmation Nr of Species vs individuals size Nr of Species vs number of specimens Nr of Species vs their life time Nr of Languages vs number of speakers Nr of countries vs population / size Nr of towns vs. population Nr of product types vs. number of units sold Nr of treatments vs number of patients treated Nr of patients vs cost of treatment Nr of moon craters vs their size Nr of earthquakes vs their strenth Nr of meteorites vs their size Nr of voids in universe vs their size Nr of galaxies vs their size Nr of rives vs the size of their basin

Conclusions The organic connection between a few classical complexity features Pareto-Zipf scaling laws / Levy-stable fat-tail fluctuations, Fractal-Intermittent singular spatio-temporal Growth patterns, Logistic Malthus-Verhulst-Lotka-Volterra-Eigen-Schuster system Percolation, phase transitions, Emergence of adaptive objects is explained within a comprehensive coherent framework. Its applications in monitoring and inducing stable growth and sustainable development is demonstrated.