Complex Adaptive Systems: Views from the Physical, Natural, and Social Sciences

254 Pages·2019·7.531 MB·English

by  Ted Carmichael, Andrew J. Collins, Mirsad Hadžikadić

Understanding Complex Systems
Ted Carmichael
Andrew J. Collins
Mirsad Hadžikadić Editors
Complex
Adaptive
Systems
Views from the Physical, Natural, and
Social Sciences
Springer Complexity
Springer Complexity is an interdisciplinary program publishing the best research and
academic-level teaching on both fundamental and applied aspects of complex systems—
cuttingacrossalltraditionaldisciplinesofthenaturalandlifesciences,engineering,economics,
medicine,neuroscience,socialandcomputerscience.
Complex Systems are systems that comprise many interacting parts with the ability to
generate a new quality of macroscopic collective behavior the manifestations of which are
the spontaneous formation of distinctive temporal, spatial or functional structures. Models
of such systems can be successfully mapped onto quite diverse “real-life” situations like
theclimate,thecoherentemissionoflightfromlasers,chemicalreaction-diffusionsystems,
biological cellular networks, the dynamics of stock markets andof the Internet, earthquake
statistics and prediction, freeway traffic, the human brain, or the formation of opinions in
social systems, toname just some ofthe popular applications.
Although their scope and methodologies overlap somewhat, one can distinguish the
following main concepts and tools: self-organization, nonlinear dynamics, synergetics,
turbulence,dynamicalsystems,catastrophes,instabilities,stochasticprocesses,chaos,graphs
and networks, cellular automata, adaptive systems, genetic algorithms and computational
intelligence.
The three major book publication platforms of the Springer Complexity program are the
monograph series “Understanding Complex Systems” focusing on the various applications
of complexity, the “Springer Series in Synergetics”, which is devoted to the quantitative
theoreticalandmethodologicalfoundations,andthe“SpringerBriefsinComplexity”which
are concise and topical working reports, case studies, surveys, essays and lecture notes of
relevance to the field. In addition to the books in these two core series, the program also
incorporates individual titles ranging from textbooks tomajor reference works.
Series Editors
HenryD.I.Abarbanel,InstituteforNonlinearScience,UniversityofCalifornia,SanDiego,LaJolla,CA,USA
DanBraha,NewEnglandComplexSystemsInstitute,UniversityofMassachusetts,Dartmouth,USA
Péter Érdi, Center for Complex Systems Studies, Kalamazoo College, USA and Hungarian Academy of
Sciences,Budapest,Hungary
KarlJ.Friston,InstituteofCognitiveNeuroscience,UniversityCollegeLondon,London,UK
HermannHaken,CenterofSynergetics,UniversityofStuttgart,Stuttgart,Germany
ViktorJirsa,CentreNationaldelaRechercheScientifique(CNRS),UniversitédelaMéditerranée,Marseille,
France
JanuszKacprzyk,PolishAcademyofSciences,SystemsResearchInstitute,Warsaw,Poland
KunihikoKaneko,ResearchCenterforComplexSystemsBiology,TheUniversityofTokyo,Tokyo,Japan
ScottKelso,CenterforComplexSystemsandBrainSciences,FloridaAtlanticUniversity,BocaRaton,USA
Markus Kirkilionis, Mathematics Institute and Centre for Complex Systems, University of Warwick,
Coventry,UK
JürgenKurths,NonlinearDynamicsGroup,UniversityofPotsdam,Potsdam,Germany
RonaldoMenezes,DepartmentofComputerScience,UniversityofExeter,UK
AndrzejNowak,DepartmentofPsychology,WarsawUniversity,Warszawa,Poland
HassanQudrat-Ullah,KingFahdUniversityofPetroleumandMinerals,Dhahran,SaudiArabia
LindaReichl,CenterforComplexQuantumSystems,UniversityofTexas,Austin,USA
PeterSchuster,TheoreticalChemistryandStructuralBiology,UniversityofVienna,Vienna,Austria
FrankSchweitzer,SystemDesign,ETHZürich,Zürich,Switzerland
DidierSornette,EntrepreneurialRisk,ETHZürich,Zürich,Switzerland
StefanThurner,SectionforScienceofComplexSystems,MedicalUniversityofVienna,Vienna,Austria
Understanding Complex Systems
Founding Editor: S. Kelso
Future scientific and technological developments in many fields will necessarily
depend uponcomingtogripswithcomplexsystems.Such systems arecomplex in
both their composition–typically many different kinds of components interacting
simultaneouslyandnonlinearlywitheachotherandtheirenvironmentsonmultiple
levels–and in the rich diversity of behavior of which they are capable.
TheSpringerSeriesinUnderstandingComplexSystemsseries(UCS)promotes
new strategies and paradigms for understanding and realizing applications of
complex systems research in a wide variety of fields and endeavors. UCS is
explicitlytransdisciplinary.Ithasthreemaingoals:First,toelaboratetheconcepts,
methodsandtoolsofcomplexsystemsatalllevelsofdescriptionandinallscientific
fields,especiallynewlyemergingareaswithinthelife,social,behavioral,economic,
neuro-andcognitivesciences(andderivativesthereof);second,toencouragenovel
applicationsoftheseideasinvariousfieldsofengineeringandcomputationsuchas
robotics, nano-technology,and informatics; third, to provide a single forum within
which commonalities and differences in the workings of complex systems may be
discerned, hence leadingto deeper insight and understanding.
UCS will publish monographs, lecture notes, and selected edited contributions
aimed at communicating new findings to a large multidisciplinary audience.
More information about this series at http://www.springer.com/series/5394
Ted Carmichael Andrew J. Collins
(cid:129) (cid:129)
ž ć
Mirsad Had ikadi
Editors
Complex Adaptive Systems
Views from the Physical, Natural, and Social
Sciences
123
Editors
TedCarmichael AndrewJ. Collins
ComplexSystems Institute, Department of Department ofEngineering Management
Software andInformation Systems andSystems Engineering, Collegeof
Collegeof Computing andInformatics, Engineering andTechnology,
University of NorthCarolina atCharlotte OldDominion University
Charlotte, NC,USA Norfolk, VA, USA
Mirsad Hadžikadić
ComplexSystems Institute, Department of
Software andInformation Systems
Collegeof Computing andInformatics,
University of NorthCarolina atCharlotte
Charlotte, NC,USA
ISSN 1860-0832 ISSN 1860-0840 (electronic)
Understanding ComplexSystems
ISBN978-3-030-20307-8 ISBN978-3-030-20309-2 (eBook)
https://doi.org/10.1007/978-3-030-20309-2
©SpringerNatureSwitzerlandAG2019
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Preface
Most interesting phenomena in natural and social systems include constant tran-
sitions and oscillations among theirvariousphases. Biological and human systems
rarely stay in a stable, predictable state for long. Randomness, power laws, and
human behavior ensure that the future is both unknown and challenging. How do
events unfold? When do they take hold? Why do some initial events cause an
avalanche while others do not? What characterizes these events? What are the
thresholds that differentiate a sea change from a non-event?
Complex Adaptive Systems (CAS) have proven to be a powerful tool for
exploring these and other related phenomena. We characterize a general CAS
model as having a large number of self-similar agents that: (1) utilize one or more
levels of feedback; (2) exhibit emergent properties and self-organization; and
(3) produce nonlinear dynamic behavior. Advances in modeling and computing
technology have led not only to a deeper understanding of complex systems in
many areas, but they have also raised the possibility that similar fundamental
principles may be at work across these systems, even though the underlying
principles may manifest themselves differently.
This book emerged out of international conferences organized through the
Association for the Advancement of Artificial Intelligence (AAAI) Fall Symposia
series and the Swarmfest 2017 conference. Our goal was to bring together
researchers from diverse fields who study these complex systems using the tools
andtechniquesofCASandagent-basedmodeling.Inthepast,knowledgegainedin
each domain has remained mostly exclusive to that domain, especially when the
disciplinesarefarapart.Itisourbeliefthatbybringingtogetherscholarswhostudy
thesephenomena,wecanleverageadeepknowledgeofonedomaintogaininsight
into others.
Charlotte, NC, USA Ted Carmichael
Norfolk, VA, USA Andrew J. Collins
Charlotte, NC, USA Mirsad Hadžikadić
v
Contents
The Fundamentals of Complex Adaptive Systems . . . . . . . . . . . . . . . . . 1
Ted Carmichael and Mirsad Hadžikadić
A Cognitive-Consistency Based Model of Population Wide
Attitude Change. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Kiran Lakkaraju and Ann Speed
An Application of Agent Based Social Modeling in the DoD . . . . . . . . . 39
Catherine Zanbaka, Jason HandUber and Desmond Saunders-Newton
Agent-Based Behavior Precursor Model of Insider IT Sabotage . . . . . . 65
Erika G. Ardiles Cruz, John A. Sokolowski, Timothy Kroecker
and Sachin Shetty
Formal Measures of Dynamical Properties: Tipping Points,
Robustness, and Sustainability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Aaron Bramson
Identifying Unexpected Behaviors of Agent-Based Models Through
Spatial Plots and Heat Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
ChristopherJ.Lynch,HamdiKavak,RossGoreandDanieleVernon-Bido
Simulating the Ridesharing Economy: The Individual Agent
Metro-Washington Area Ridesharing Model (IAMWARM). . . . . . . . . . 143
Joseph A. E. Shaheen
Stigmergy for Biological Spatial Modeling . . . . . . . . . . . . . . . . . . . . . . . 169
Megan Olsen
Strategic Group Formation in the El Farol Bar Problem. . . . . . . . . . . . 199
Andrew J. Collins
vii
viii Contents
swarmFSTaxis: Borrowing a Swarm Communication Mechanism
from Fireflies and Slime Mold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
JoshuaCherianVarughese,DanielMoser,RonaldThenius,FranzWotawa
and Thomas Schmickl
Teaching Complexity as Transdisciplinarity. . . . . . . . . . . . . . . . . . . . . . 223
Loren Demerath and E. Dante Suarez
The Fundamentals of Complex Adaptive
Systems
TedCarmichaelandMirsadHadžikadic´
Abstract ComplexAdaptiveSystems(CAS)isaframeworkforstudying,explain-
ing,andunderstandingsystemsofagentsthatcollectivelycombinetoformemergent,
global level properties. These agents can be nearly anything, from ants or bees, to
braincells,towaterparticlesinaweatherpattern,togroupsofcarsorpeopleinacity
ortown.Theseagentsproduceemergentpatternsviacorrelatedfeedbacksthrough-
out the system, feedbacks that create and fortify a basin of attraction: a persistent
patternofbehaviorthatitselfisoutsideofequilibrium.Thereisalsoanever-growing
understandingthatsimilarfeaturesincomplexsystemsacrossadiversityofdomains
mayindicatesimilarfundamentalprinciplesatwork,andassuchthereisoftenutility
inusingthekeyfeaturesofonesystemtogaininsightintotheworkingsofseemingly
distinctfields.Herewealsoincludeabriefreviewofmultiplemodelsthatattemptto
doexactlythis,includingsomeofourpreviouswork.Thoughthereisnotcomplete
agreementonallaspectsanddefinitionsinthisfield,thisintroductionalsosumma-
rizesourunderstandingofwhatdefinesaCAS,includingtheconceptsofcomplexity,
agents,adaptation,feedbacks,emergence,andself-organization;andplacesthisdef-
initionanditskeyfeaturesinahistoricalcontext.Finallywebrieflydiscusstwoof
thecommonbiasesoftenfoundthatthetoolsofCAScanhelpcounteract:thehierar-
chicalbias,assumingastrongtop-downorganization;andthecomplexitybias,the
tendencytoassigncomplicatedfeaturestoagentsthatturnouttobequitesimple.
B
T.Carmichael( )·M.Hadžikadic´
DepartmentofSoftwareandInformationSystems,UniversityofNorthCarolinaatCharlotte,
9201UniversityCityBlvd,Charlotte,NC28223,USA
e-mail:[email protected]
M.Hadžikadic´
e-mail:[email protected]
T.Carmichael
TutorGen,Inc.,1037SFtThomasAve,FortThomas,KY41075,USA
©SpringerNatureSwitzerlandAG2019 1
T.Carmichaeletal.(eds.),ComplexAdaptiveSystems,Understanding
ComplexSystems,https://doi.org/10.1007/978-3-030-20309-2_1
2 T.CarmichaelandM.Hadžikadic´
1 Overview
Mostinterestingcollectivephenomenainnaturalandsocialsystemscanbedescribed
ashavingstableandpersistentstates,oftenoutsideofequilibrium.Thetermbasinof
attractionhasbeenusedtodescribesuchsystems,capturingtheideaofcorrelated
feedbacksamongtheagentsofasystemthatcreatetheseidentifiableanddistinctpat-
terns.Thesesystemsaresodefinedbecausetheyareresilientinthefaceofexternal
forces,butcannevertheless alsoexhibittippingpoints:situationswherethestable
systemfinallycrossessomethreshold,andbeginsarapidtransitiontoanewstate.
Thesethresholdscanbecharacterizedasaqualitativechangeinsystemcharacteris-
tics:achangeinsignorabruptchangeinmagnitude(eitherenduringoraspike)in
thefirstorsecondderivativeofasystemvariable.
Thresholdeffectsarefoundallaroundus.Ineconomics,thiscouldbemovement
fromabullmarkettoabearmarket;insociology,itcouldbethespreadofpolitical
dissent,culminatinginrebellion;inbiology,theimmunesystemresponsetoinfection
ordiseaseasthebodymovesfromsicknesstohealth.Companies,societies,markets,
orevenhumansrepresentsuchpersistentstatesthatcanchangerapidlyatanytime.
Both endogenous and exogenous feedbacks can cause sudden, non-linear shifts in
system behavior, ensuring that the future of these systems are often unknown and
challenging.Howdoeventsunfold?Whendotheytakehold?Whydosomeinitial
eventscauseanavalancheofchangewhileothersdonot?Whatcharacterizessystem
stabilityandresilience?Whatarethethresholdsthatdifferentiateaseachangefrom
negligiblevariations?
Complex Adaptive Systems (CAS) has proven to be a powerful framework for
exploring thresholds and resilience, and other related phenomena. As the name
implies, a CAS is a system of agents that interact among themselves and/or their
environment,suchthatevenrelativelysimpleagentswithsimplerulesofbehavior
canproducecomplex,emergentbehavior.ThekeytoCASisthatthesystem-level
propertiesgenerallycannotbeunderstood,oroftenevendefined,atthelevelofthe
individualagentdescription.Therefore,thesesystemsmustbestudiedholistically,
asthesumoftheagentsandtheirinteractions.
1.1 DefiningCAS
WecharacterizeageneralCASmodelashavingasignificantnumberofself-similar
agentsthat:
(cid:129) Utilizeoneormorelevelsoffeedback;
(cid:129) Exhibitemergentpropertiesandself-organization;
(cid:129) Producenon-lineardynamicbehavior.
TheCASframeworkcanbeusedtodescribesystemsthatencompassphenomena
across many diverse environments and a wide range of disciplines. These systems