1. Emergence of Organization and Markets Lloyd Demetrius June 2014

2. Claim The Origin and Evolution of Organizational Structures Can be analytically explained in terms of a theory of autocatalytic networks. Classes of Networks (1) Social Networks: cooperation between individuals in a community (2) Economic Networks: transformation and production of economic commodities (3) Linguistic Networks: production and generation of symbols 2

3. 3 Autocatalytic Networks Chemical Reaction Networks Biochemical Examples 1)Glycolysis: 2 ATP 2) Oxidative Phosphorylation36 ATP Product C catalyses ist own synthesis from precursors A and B A + C D D + B E E 2C

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6. 6 Problem To what extent is the conceptual framework of autocatalytic networks an appropriate model for the analytic study of the origin and evolution of socio-economic networks?

7. 7 Origin and Evolution in Three Classes of Networks (1) Metabolic Networks: Energy production (2) Social Networks: Evolution of cooperation (3) Demographic Networks: Evolution of life history

8. 8 Metabolic Networks Origin and Evolution of Energy Production in Cells Glycolytic Networks Oxidative Phosphorylation Cancer cells: Predominantly Glycolysis Normal cells: Predominantly Ocidative Phosphorylation Problem The Evolutionary Basis for Glycolysis and Ocidative Phosphorylation

9. 9 Social Networks Origin and Evolution of Cooperation 2 3 1 2 3 1 Random Interaction Stratified Network Egalitarian Network 1 2 3 1 2 3 Structured Interaction Origin Evolution

10. 10 Aggregates of Interacting Molecules Solid Liquid Gas Problem Explain the stability of these states Non-Autocatalytic Networks

11. 11 Thermodynamic Entropy Measure of Complexity in Material Aggregates Solid: low entropy W = number of ways that the molecules of a system can be arranged to achieve the same total energy Gas: high entropy Second Law of Thermodynamics: Thermodynamic entropy increases

12. 12 Demographic Networks Origin and Evolution of Iteroparity Annual Plants Perennial Plants Problem: The evolutionary rationale for the diversity in life history 123d

13. 13 Organismic Evolution (1) Variation: individuals within a species vary in terms of their physiology and behavior (2) Heredity: there exists a positive correlation between the behavioral and physiological traits of parents and their offspring (3) Selection: individuals differ in their capacity to appropriate resources from the external environment and to convert their resources into offspring

14. 14 Prerequisites for an Analytical Model of Network Evolution (1) A mathematical description of network complexity (2) A formal description of the network-environment interaction (3) An analytic description of natural selection (4) A description of the rules of inheritance

15. 15 Demographic Networks Network Complexity Annual Plants W =1, S =0 Perennial Plants W >1, S >0 Network-Environment Resource abundance, resource composition Laws of Inheritance Mendelian W = number of distinct pathways of energy flow in the network

16. 16 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

17. 17 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)

18. 18 From Demographic Networks to Social Networks PropertiesDemographic Networks Social Networks UnitLife CycleCooperative and Selfish Transactions Target of SelectionPhenotypic TraitsBehavioral Traits Laws of InheritanceMendelianCultural Environmental Constraints Energy: FoodstuffsEnergy: Foodstuffs, Information Measure of Fitness Network Complexity Degree of IteroparityDegree of Cooperation

19. 19 Evolutionary Entropy Measure of Network Complexity Few pathways = low entropy W = number of distinct pathways of energy flow within a network 123 123 Several distinct pathways = high entropy NetworkLow EntropyHigh Entropy DemographicAnnual PlantsPerennial Plant MetabolicGlycolysisOxidative Phosphorylation SocialSelfishnessCooperative PoliticalStratifiedEgalitarian

20. 20 Applications of the Entropic Principles of Network Evolution Resource constraints Metabolic networks Social networks Economic networks constant abundance - diverse composition oxidative phosphorylation cooperationeconomic equality variable abundance - singular composition glycolysisselfishnesseconomic inequality