COMMUNICATING SEQUENTIAL AGENTS: AN ANALYSIS OF CONCURRENT AGENT ...

163 Pages·2016·2.42 MB·English

COMMUNICATINGSEQUENTIALAGENTS:
ANANALYSISOFCONCURRENTAGENTSCHEDULING
by
StefanD.McCabe
AThesis
Submittedtothe
GraduateFaculty
of
GeorgeMasonUniversity
InPartialFulfillmentof
TheRequirementsfortheDegree
of
MasterofArts
InterdisciplinaryStudies
Committee:
Director
ProgramDirector
Dean,Collegeof
HumanitiesandSocialSciences
Date: SpringSemester2016
GeorgeMasonUniversity
Fairfax,VA
CommunicatingSequentialAgents: AnAnalysisofConcurrent
AgentScheduling
Athesissubmittedinpartialfulfillmentoftherequirementsforthedegreeof
MasterofArtsatGeorgeMasonUniversity
By
StefanD.McCabe
BachelorofArts
GeorgeMasonUniversity,2013
Director: RobertL.Axtell,Professor
DepartmentofComputationalandDataSciences
SpringSemester2016
GeorgeMasonUniversity
Fairfax,VA
Copyright©2016byStefanD.McCabe
AllRightsReserved
ii
Dedication
ForMom—Icouldn’thavedoneitwithoutyoursupporteverystepoftheway.
iii
Acknowledgments
First,Imustthankmycommitteefortheirmassivecontributionstothisproject:
Dr. RobertAxtell,whomentoredmethroughoutthisprocessandsupportedmyresearchin
thisarea.
Dr. Kenneth Comer, whose dissertation provided a foundation for my own work, and who
encouragedmealongtheway.
Dr. AndrewCrooks,withoutwhomIwouldneverhavefinishedwriting.
IoweagreatdealofthankstoMatthewOldham,whoencouragedmethroughoutthethesis-
writingprocessandwhoservedasasoundingboardformanyofmyideas.
I also would like to thank my friends and family for putting up with my endless worrying
andcomplaining.
iv
Table of Contents
Page
ListofTables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
ListofFigures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
ListofAbbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 LiteratureReview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.1 Agent-BasedModeling: AnOverview . . . . . . . . . . . . . . . . 3
1.2.2 Agent-BasedModelingandHigh-PerformanceComputing . . . . . 6
1.2.3 ActivationandUpdatinginAgent-BasedModels . . . . . . . . . . 11
2 ATypologyofAgentActivationRegimes . . . . . . . . . . . . . . . . . . . . . 20
2.1 AgentSelection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.2 Uniformity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.3 Reproducibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.4 Updating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.5 Endogeneity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.6 Parallelization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.7 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3 ASystematicReviewoftheUsageofDifferentAgentActivationRegimes . . . . 31
3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.2 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.5.1 FutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4 StudyingAgentActivationinaModelofBilateralExchange . . . . . . . . . . . 41
4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
v
4.2 ModelSpecification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.2.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.2.3 Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
4.2.4 Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
4.3 MethodologyandResults . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.3.1 Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.3.2 SerialActivationRegimes . . . . . . . . . . . . . . . . . . . . . . 47
4.3.3 ParallelActivationRegimes . . . . . . . . . . . . . . . . . . . . . 52
4.3.4 Fork-and-JoinActivationRegimes . . . . . . . . . . . . . . . . . . 55
4.4 Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.4.1 ScalinginFork-and-Join . . . . . . . . . . . . . . . . . . . . . . . 58
4.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.5.1 FutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
A ODDProtocolforExchangeModel . . . . . . . . . . . . . . . . . . . . . . . . 64
A.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
A.1.1 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
A.1.2 StateVariablesandScales . . . . . . . . . . . . . . . . . . . . . . 64
A.1.3 ProcessOverviewandScheduling . . . . . . . . . . . . . . . . . . 66
A.2 DesignConcepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
A.2.1 Emergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
A.2.2 Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
A.2.3 Stochasticity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
A.3 Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
A.3.1 Initialization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
A.3.2 Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
A.3.3 Submodels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
B OpenABMEntriesExcludedFromReview . . . . . . . . . . . . . . . . . . . . 70
C OpenABMReviewData . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
D ModelCode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
D.1 RNG.h . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
D.2 RNG.cpp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
D.3 main.h . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
D.4 main.cpp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
D.5 Dockerfile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
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List of Tables
Table Page
2.1 Overview of activation regime typology. In bold are the design choices
representedbyNetLogo’saskcommand. . . . . . . . . . . . . . . . . . . 21
3.1 Deviations from the mode for different aspects of the activation regime,
contingentonmodel’suseoftheODDprotocol. . . . . . . . . . . . . . . . 37
3.2 Deviations from the mode for different aspects of the activation regime,
contingentonthemodelingplatformused. . . . . . . . . . . . . . . . . . . 37
4.1 Parameterizationoftheexchangemodel. . . . . . . . . . . . . . . . . . . . 43
4.2 Overviewofserialactivationregimesexamined. . . . . . . . . . . . . . . . 48
vii
List of Figures
Figure Page
1.1 Atypologyofagent-basedmodels,fromCrooksandCastle(2012,p. 228). 5
1.2 DynamicsofstandarddeviationofwealthinaLevellermodelwithdifferent
activationregimes. FromComer(2014,p. 136). . . . . . . . . . . . . . . . 16
3.1 Piechartsshowingthedistributionofdifferentareasoftheactivationregime
acrossallpublicOpenABMmodels. . . . . . . . . . . . . . . . . . . . . . 35
3.2 AdoptionrateofODDprotocolovertime. Notethatthehighearlyadoption
rateislikelyanartifactofresearchersupdatingveryoldmodels. . . . . . . 36
3.3 Selection orders used, contingent on ODD adoption. “F” is fixed, “R” is
random,“P”isPoisson. Multiplelettersmeansthemodelincludesmultiple
activationregimes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.4 Selection orders used, contingent on modeling platform used. “F” is fixed,
“R” is random, “P” is Poisson. Multiple letters means the model includes
multipleactivationregimes. . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.5 Updatingsystemsused,contingentonmodelingplatformused. . . . . . . . 40
4.1 Runtimeofthebilateralexchangemodel,N =2. . . . . . . . . . . . . . . 46
4.2 Memoryusageofthebilateralexchangemodel,N =2. . . . . . . . . . . . 46
4.3 Numberofinteractions(successfultrades)overtime,serialactivation. . . . 48
4.4 Histogramsofagentactivations,serialactivation. Notethatthesecondrow
haslog-10axes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
4.5 Histograms of successful agent trades, serial activation. Note that the sec-
ondrowhaslog-10axes. . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.6 QQplotofagentactivations,serialrandomselection. . . . . . . . . . . . . 51
4.7 Minimumagentwealthovertime,serialactivation. . . . . . . . . . . . . . 52
4.8 Standarddeviationofagentmarginalratesofsubstitution,serialactivation. 53
4.9 Numberofinteractions(successfultrades)overtime,parallelactivation. . . 53
viii
4.10 Histograms of agent activations, parallel activation. Note that the second
rowhaslog-10axes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
4.11 Histograms of successful agent trades, parallel activation. Note that the
secondrowhaslog-10axes. . . . . . . . . . . . . . . . . . . . . . . . . . 54
4.12 Numberofinteractions(successfultrades)overtime,fork-and-joinactivation. 56
4.13 Histograms of agent activations, fork-and-join activation. Note that the
secondrowhaslog-10axes. . . . . . . . . . . . . . . . . . . . . . . . . . 56
4.14 Histograms of successful agent trades, fork-and-join activation. Note that
thesecondrowhaslog-10axes. . . . . . . . . . . . . . . . . . . . . . . . 57
4.15 Standard deviation of agent marginal rates of substitution, fork-and-join
activation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.16 Performancemeasuresfordifferentimplementations. . . . . . . . . . . . . 58
4.17 Scalingoffork-and-joinimplementation. Randomandrandom-with-shuffle
only. Thedashedlinerepresentstheaverageruntimeoftheserialmodel. . . 59
4.18 Number of interactions as the number of threads are varied. Above is ran-
domactivation,belowisrandom-shuffleactivation. . . . . . . . . . . . . . 60
4.19 Changeinmeanagentutilityasthenumberofthreadsarevaried. Aboveis
randomactivation,belowisrandom-shuffleactivation. . . . . . . . . . . . 60
4.20 Change the standard deviation of agent MRSes as the number of threads
arevaried. Aboveisrandomactivation,belowisrandom-shuffleactivation. 61
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