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Emergence of Organization and Markets

Explore the theory of autocatalytic networks to explain the origin and evolution of organizational structures in social, economic, and linguistic networks. Delve into metabolic, social, and demographic networks to study energy production, cooperation, and life history evolution. Investigate stability of non-autocatalytic networks and analyze evolutionary changes in network complexity. Understand the principles of demographic evolution and how they relate to social networks.

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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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