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Selfish Reciprocal Altruism PDF

77 Pages·2017·1.6 MB·English
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Politecnico di Milano School of Industrial and Information Engineering Master of Science in Mathematical Engineering Selfish Reciprocal Altruism: an evolutionary rule for strategy update in social networks Supervisor: Prof. Carlo PICCARDI Co-supervisor: Prof. Fabio DERCOLE Dott. Fabio DELLA ROSSA Candidate: Claudia RUFFONI Personal ID 836977 Academic Year 2015-2016 Ai miei genitori, Giovanna e Cesare Contents Sommario 1 Abstract 3 1 Introduction 5 1.1 The role of cooperation . . . . . . . . . . . . . . . . . . . . . . 5 1.2 About this work . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2 Evolutionary Dynamics 11 2.1 The Prisoner’s Dilemma game . . . . . . . . . . . . . . . . . . 11 2.2 Mechanisms to favor cooperation . . . . . . . . . . . . . . . . 13 2.3 Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.3.1 Network Properties . . . . . . . . . . . . . . . . . . . . 20 2.3.2 Network Models . . . . . . . . . . . . . . . . . . . . . . 23 2.4 Evolutionary Dynamics in Social Networks . . . . . . . . . . . 25 2.4.1 Strategy Update . . . . . . . . . . . . . . . . . . . . . 25 i ii CONTENTS 2.4.2 The PD Game in Social Networks . . . . . . . . . . . . 28 2.5 Evolution by imitation . . . . . . . . . . . . . . . . . . . . . . 31 2.5.1 Evolutionary Dynamics of Social Dilemmas in Struc- tured Heterogeneous Populations . . . . . . . . . . . . 32 3 Selfish Reciprocal Altruism 35 3.1 The model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2 Preliminary Analysis . . . . . . . . . . . . . . . . . . . . . . . 39 3.2.1 Preliminary analysis for star network . . . . . . . . . . 41 3.3 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.3.1 Explanatory example . . . . . . . . . . . . . . . . . . . 45 3.3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.4 A possible extension: Mean Field Analysis . . . . . . . . . . . 55 4 Conclusions 59 Ringraziamenti 67 List of Figures 2.1 Undirected graph . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.2 Directed graph . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3 Weighted and unweighted graphs . . . . . . . . . . . . . . . . 19 2.4 Connected and disconnected graphs . . . . . . . . . . . . . . . 20 2.5 Examples of assortative and disassortative networks . . . . . . 22 2.6 Complete network . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.7 Star network . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.8 Birth-Death process . . . . . . . . . . . . . . . . . . . . . . . . 26 2.9 Death-Birth process . . . . . . . . . . . . . . . . . . . . . . . . 27 2.10 Link dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.11 Imitation process . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.12 Replicator Dynamics . . . . . . . . . . . . . . . . . . . . . . . 29 2.13 Heterogeneous network . . . . . . . . . . . . . . . . . . . . . . 30 2.14 Results of Santos’ model . . . . . . . . . . . . . . . . . . . . . 34 iii iv LIST OF FIGURES 3.1 Initialization step . . . . . . . . . . . . . . . . . . . . . . . . . 36 3.2 Interaction step . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.3 Update step . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.4 Star network with C hub . . . . . . . . . . . . . . . . . . . . . 42 3.5 Selfish reciprocal altruism: example 1 . . . . . . . . . . . . . . 46 3.6 Selfish reciprocal altruism: example 2 . . . . . . . . . . . . . . 46 3.7 Selfish reciprocal altruism: example 3 . . . . . . . . . . . . . . 47 3.8 Selfish reciprocal altruism: example 4 . . . . . . . . . . . . . . 47 3.9 Selfish reciprocal altruism: example 5 . . . . . . . . . . . . . . 47 3.10 Selfish reciprocal altruism: example 6 . . . . . . . . . . . . . . 48 3.11 Selfish reciprocal altruism: example 7 . . . . . . . . . . . . . . 48 3.12 Selfish reciprocal altruism for BA networks . . . . . . . . . . . 52 3.13 Selfish reciprocal altruism for ER networks . . . . . . . . . . . 53 3.14 Selfish reciprocal altruism for complete networks . . . . . . . . 54 3.15 Selfish reciprocal altruism for star networks . . . . . . . . . . . 55 List of Tables 2.1 Prisoner’s Dilemma example . . . . . . . . . . . . . . . . . . . 12 2.2 PD 4-parameter . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3 PD 2-parameter: T and S . . . . . . . . . . . . . . . . . . . . 12 2.4 PD 2-parameter: b and c . . . . . . . . . . . . . . . . . . . . . 13 2.5 PD 1-parameter . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.1 Payoff values and conditions for strategy change . . . . . . . . 41 v

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3.14 Selfish reciprocal altruism for complete networks 54. 3.15 Selfish reciprocal . We propose a new rule for strategy update, called selfish reciprocal altruism, where players decide to update L the number of iterations considered and m(t) the floating average at iteration t, then: m(t) = 1.
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