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Emergence of Organization and Markets

Emergence of Organization and Markets. Lloyd Demetrius June 2014. Claim The Origin and Evolution of Organizational Structures. Can be analytically explained in terms of a theory of autocatalytic networks. Classes of Networks Social Networks: cooperation between individuals in a community

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Emergence of Organization and Markets

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  1. Emergence of Organization and Markets Lloyd Demetrius June 2014

  2. ClaimThe Origin and Evolution of Organizational Structures Can be analytically explained in terms of a theory of autocatalytic networks. Classes of Networks Social Networks: cooperation between individuals in a community Economic Networks: transformation and production of economic commodities Linguistic Networks: production and generation of symbols

  3. Autocatalytic Networks Chemical Reaction Networks A + C D D + B E E 2C ProductCcatalyses ist ownsynthesisfromprecursorsA and B BiochemicalExamples Glycolysis: 2 ATP 2) OxidativePhosphorylation 36 ATP

  4. Problem Towhatextentistheconceptualframeworkofautocatalyticnetworks an appropriate model fortheanalyticstudyoftheorigin and evolutionof socio-economicnetworks?

  5. Origin and Evolution in Three Classes of Networks Metabolic Networks: Energy production Social Networks: Evolution of cooperation Demographic Networks: Evolution of life history

  6. Metabolic Networks Origin and Evolution of Energy Production in Cells • Glycolytic Networks Oxidative Phosphorylation • Cancer cells: Predominantly Glycolysis • Normal cells: PredominantlyOcidativePhosphorylation • Problem • The Evolutionary Basis for Glycolysis and OcidativePhosphorylation

  7. Social Networks Origin and Evolution of Cooperation Random Interaction Origin Structured Interaction 3 3 1 Evolution 1 1 2 1 2 2 3 2 3 Egalitarian Network Stratified Network

  8. Non-Autocatalytic Networks Aggregates of Interacting Molecules Solid Liquid Gas Problem Explain the stability of these states

  9. Thermodynamic Entropy Measure of Complexity in Material Aggregates W =numberofwaysthatthemoleculesof a systemcanbearrangedtoachievethe same total energy Solid:lowentropy Gas:highentropy • Second Law of Thermodynamics: • Thermodynamicentropyincreases 11 11 11

  10. Demographic Networks Origin and Evolution of Iteroparity 1 2 3 d PerennialPlants Annual Plants Problem: The evolutionary rationale forthediversity in lifehistory

  11. Organismic Evolution • Variation: individuals within a species vary in terms of their physiology and behavior • Heredity: there exists a positive correlation between the behavioral and physiological traits of parents and their offspring • Selection: individuals differ in their capacity to appropriate resources from the external environment and to convert their resources into offspring

  12. Prerequisites for an Analytical Model of Network Evolution • A mathematical description of network complexity • A formal description of the network-environment interaction • An analytic description of natural selection • A description of the rules of inheritance

  13. Demographic Networks Network Complexity W =numberofdistinctpathwaysofenergyflow in thenetwork PerennialPlants W>1, S>0 Annual Plants W=1, S=0 Network-Environment Resourceabundance, resourcecomposition Laws ofInheritance Mendelian 15

  14. Evolution of Demographic Networks Evolutionary Changes in Network Complexity • Variation:Changes in the topology and interaction intensity of the network – changes in life history • Selection:Competition between variant and ancestral network for the resources X = ancestral type X*= variant type

  15. Principles of Demographic Evolution • The outcome of selection is predicted by evolutionary entropy and is contingent on the external resource constraints: • (I) Resources constant in abundance and • diverse in composition • Evolutionary entropy increases(selection for iteroparity) • (II) Resources variable in abundance, • singular in composition • Evolutionary entropy decreases (selection for semelparity)

  16. From Demographic Networks to SocialNetworks

  17. Evolutionary Entropy Measure of Network Complexity W =numberofdistinctpathwaysofenergyflowwithin a network 1 2 3 Fewpathways = lowentropy Severaldistinctpathways = highentropy 1 2 3 19 19

  18. Applications of the Entropic Principles of Network Evolution

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