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Weigle X-Machines for Agent-Based Modeling: FLAME Perspectives Mariam Kiran X-Machines for Agent-Based Modeling FLAME Perspectives Mariam Kiran CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2017 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed on acid-free paper Version Date: 20170722 International Standard Book Number-13: 978-1-4987-2385-5 (Hardback) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. 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Contents Foreword xiii Preface xvii List of Figures xix List of Tables xxv FLAME Contributors xxvii 1 Setting the Stage: Complex Systems, Emergence and Evolution 1 1.1 ComplexandAdaptiveSystems . 3 1.2 WhatIsChaos? ......................... 4 1.3 ConstructingArtificialSystems . 5 1.4 ImportanceofEmergence . .. .. .. .. .. .. .. .. 6 1.5 DynamicSystems ........................ 6 1.6 IsThereEvolutionatWork? .................. 7 1.6.1 Adaptation ........................ 8 1.7 Distributing Intelligence? . 9 1.8 Modeling and Simulation . 10 1.8.1 ResearchExamples.................... 12 2 Artificial Agents 17 2.1 IntelligentAgents ........................ 18 2.1.1 “CanMachinesThink?” . 19 2.2 Engineering Self-Organizing Systems . 21 2.2.1 BringintheAgents ................... 22 2.2.2 Characteristics of Agent-Based Models . 23 2.3 Agent-BasedModelingFrameworks . 33 2.4 AdaptiveAgentDesign ..................... 37 2.5 MathematicalFoundations . 38 2.6 ObjectsorAgents? ....................... 39 2.7 InfluenceofOtherResearchAreasonABM . 40 ix x Contents 3 DesigningX-AgentsUsingFLAME 43 3.1 FLAMEandItsX-MachineMethodology . 44 3.1.1 Transition Functions . 47 3.1.2 MemoryandStates ................... 47 3.2 Using Agile Methods to Design Agents . 48 3.2.1 ExtensiontoExtremeProgramming . 51 3.3 Overview:FLAMEVersion1.0 . 51 3.4 Libmboard(FLAMEmessageboardlibrary) . 54 3.4.1 Compiling and Installing Libmboard . 55 3.4.2 FLAME’s Synchronization Points . 57 3.5 FLAME’s Missing Functionality . 58 4 Getting Started with FLAME 61 4.1 SettingUpFLAME ....................... 62 4.1.1 MinGW.......................... 63 4.1.2 GDBGNUDebugger .................. 63 4.1.3 Dotty as an Extra Installation . 64 4.2 MessagingLibrary:Libmboard . 64 4.3 HowtoRunaModel? ...................... 65 4.4 Implementation Details . 65 4.5 UsingGrids ........................... 68 4.6 Integrating with More Libraries . 69 4.7 Writing a Model - Fox and Rabbit Predator Model . 71 4.7.1 Adding Complexity to Models . 72 4.7.2 XML Model Description File . 72 4.7.3 CFunction ........................ 76 4.7.4 Additional Files . 81 4.7.5 0.xml File . 83 4.8 EnhancingtheEnvironment . 84 4.8.1 ConstantVariables.................... 84 4.8.2 Time Rules . 84 5 Agents in Social Science 87 5.1 SugarscapeModel ........................ 92 5.1.1 EvolutionfromBottom-Up . 93 5.1.2 Distribution of Wealth . 94 5.1.3 LocationIsImportant!. 95 5.1.4 FindAgentsaroundMe . 104 5.1.5 Handle Multiple ‘Eaten’ Requests . 105 5.1.6 Change Starting Conditions . 105 5.2 ModelingSocialNetworks . 107 5.2.1 SetUpaRecurringFunction . 112 Contents xi 5.2.2 Assigning Conditions with Functions . 113 5.2.3 Using Dynamic Arrays and Data Structures . 113 5.2.4 CreatingLocalDynamicArrays. 114 5.3 Modeling Pedestrians in Crowds . 114 5.3.1 Calculate Movement toward Other Agents . 116 5.3.2 Entering and Exiting Agents . 118 6 AgentsinEconomicMarketsandGames 121 6.1 Perfect Rationality versus Bounded Rationality . 125 6.2 Modeling Multiple Shopper Behaviors . 126 6.3 LearningFirmsinaCournotModel . 129 6.3.1 Genetic Programming with Agents . 143 6.3.2 Filtering Messages in Advance . 150 6.3.3 ComparingTwoDataStructures . 151 6.4 A Virtual Mall Model: Labor and Goods Market Combined . 152 6.5 ProgrammingGames ...................... 159 6.5.1 Nash Equilibrium . 160 6.5.2 EvolutionaryGameTheory . 161 6.5.3 Evolutionary Stable State . 162 6.5.4 Game Theory versus Evolutionary Game Theory . 162 6.5.5 ContinuousStrategies . 163 6.5.6 Red Queen and Equilibrium . 163 6.6 Learning in an Iterated Prisoner’s Dilemma Game . 164 6.7 Multi-AgentSystemsandGames . 173 7 Agents in Biology 175 7.1 ExampleModels ......................... 176 7.1.1 Molecular Systems Models . 176 7.1.2 TissueandOrganModels . 179 7.1.3 Ecological Models . 182 7.1.4 Industrial Applications of Agent-Based Modeling with FLAME.......................... 183 7.2 Modeling Epithelial Tissue . 184 7.2.1 Merging with Other Toolkits . 185 7.3 Modeling Drosophila Embryo Development . 187 7.3.1 Stochastic Modeling . 188 7.3.2 ConvertingtoanAgent-BasedModel . 188 7.3.3 Find Optimum Model Settings