The Evolution of Social Behavior George J.Gumerman Santa FeInstitute in the Prehistoric American 1399Hyde Park Road Southwest Santa Fe,NM 87501 AlanC. Swedlund Departmentof Anthropology Universityof Massachusetts– Amherst Jeffrey S.Dean Laboratory of Tree-Ring Abstract Long HouseV alley, located in theBlack Mesa area of northeastern Arizona (USA), was inhabited bythe Kayenta Research Anasazi from circa 1800 B.C. to circa A.D. 1300.These people TheUniversity of Arizona wereprehistoric precursors of themodern Pueblo cultures of JoshuaM. Epstein theColorado Plateau. Arich paleoenvironmental record, Centeron Social and based on alluvial geomorphology, palynology, and dendroclimatology, permitsthe accurate quantitative Economic Dynamics reconstruction of annual uctuations in potentialagricultural TheBrookings Institution production (kgmaize/ hectare).The archaeological record of and Anasazi farming groups from A.D. 200to 1300provides Santa FeInstitute information on amillennium of sociocultural stasis, variability, change, and adaptation. Wereporton a multi-agentcomputational model of this societythat closely reproduces themain featuresof its actual history, including population ebb and ow, changing spatial settlement Keywords patterns,and eventualrapid decline. Theagents in themodel Agent-basedmodeling, Anasazi, prehistory,American Southwest, are monoagriculturalists, who decideboth whereto situate environmentalreconstruction, their Želds and whereto locate their settlements. culturalevolution

1Introduction

Acentralquestion that anthropologists have asked for generations concerns how cul- turesevolve or transformthemselves from simple tomore complex forms. Traditional studyof human social changeand cultural evolutionhas resulted in many usefulgener- alizations concerning thetrajectory of change through prehistory and classiŽcations of typesof organization. Itis increasingly clear, however,that four fundamental problems havehindered the development of a powerful, uniŽed theoryfor understanding change in human social norms and behaviorsover long periodsof time. TheŽ rstof theseproblems isthe use of whole societies as the unit of analysis. Group- leveleffects, however, must themselves be explained. Sustainedcooperative behavior withpeople beyond close kin isachieved in mosthuman societies,and increasingly hierarchical political structuresdo emergethrough time in many cases.Successful explanation and thepossibility of developing fundamental theoryfor understanding theseprocesses depend on understandingbehavior at the level of the individual or thefamily [8]. Amongthe advantages of such base-level approaches isthat they allow speciŽc modeling ofpeoples’ behavioral rangesand norms and theiradaptive strategies ascommunity sizeand structurechange. Second, in addition tosubsuming the behavior of individuals within thatof larger social units,traditional analysesintegrate environmental variability overspace. Current c 2003Massachusetts Instituteof Technology ArtiŽcial Life 9:435– 444 (2003) ° G.J.Gumerman, A.C.Swedlund, J. S.Dean, and J.M.EpsteinPrehistoric American Southwest researchindicates that stable strategies for interpersonal interactions in aheterogeneous, spatially extendedpopulation may bevery different from thosein ahomogeneous population in which spaceis ignored [11]. Most social interactionsand relationshipsin human societiesbefore the recent advent of rapid transportationand communication werelocal in nature. Third, cultureshave been considered to behomogeneous,tending toward maximiza- tionof Žtnessfor their members. Little consideration wasgiven to historical processes in shaping evolutionarytrajectories or tononadaptive aspects of cultural practice. Finally, mostdiscussions of cultural evolutionhave failed totake into account the mechanisms ofcultural inheritanceand theeffects of changesin modesof transmission throughtime [2, 3]. Understandingculture as an inheritancesystem is fundamental to understandingculture change through time. TheArtiŽ cial Anasazi projectis at the juncture of theory building and experimenta- tion. Weuseagent-based modeling totest the Ž tbetweenactual archaeological and environmentaldata collectedover many yearsand simulations usingvarious rules about how householdsinteract with one another and withtheir natural environment.By sys- tematically alteringdemographic, social, and environmentalconditions, aswell asthe rulesof interaction, weexpectthat a clearerpicture will emergeas to why the Anasazi followed theevolutionary trajectory we recognize from archaeological investigation. Our long rangegoal isto develop agent-based simulations tounderstand the interac- tionof environmentand human behaviorand theirrole in theevolution of culture.

2The Study Area

Thetest area forexploring the use of agent-based modeling forunderstanding social evolutionis the prehistoric American Southwestfrom about A.D. 200to 1450 using a culturearchaeologists refer to as the Anasazi and alocality called Long HouseV alley. TheAnasazi arethe ancestors of the present day Pueblo peoples,such as the Hopi, the Zuni, theAcoma, and thegroups along theRio Grandein NewMexico. Acommonly heldview is that technological, social, and linguistic complexitycoevolve. Anasazi cul- tural developmentunderscores the interdependence of these aspects of culture. The Anasazi werea technologically simple agricultural societywhose major foodsource wasmaize supplementedby beans, squash, wild plants, and game. Inthe A.D. 200 to 1450period theonly major technological changesthat are archaeologically veriŽable areagricultural intensiŽcation (terracingand ditch irrigation) and theintroduction ofa moreefŽ cient system for grinding maize. Duringthis time, however,there is evidence ofgreatly increased social complexity. ContemporaryPueblo peoplehave complicated social systemsmade up ofsodalities(distinct social associations) including clans, moi- eties(division ofthe village intotwo units), feastgroups, religioussocieties and cults(68 differentceremonial groupshave been recorded), war societies,healing groups, winter and summergovernments, and village governments.Details of the groups come from historical documentsand contemporaryethnographies. The economic, religious, and social realms ofPueblo societyare so tightlyintegrated it is difŽ cult tounderstand them asseparate elements of the society. Long HouseV alley, a180km 2 landform in northeasternArizona, providesa re- alistic archaeological testof the agent-based modeling ofsettlement and economic behavioramong subsistence-levelagricultural societiesin marginal habitats. This area iswell suitedfor such a testfor a number ofreasons. First, it is a topographically bounded, self-containedlandscape thatcan berealistically reproducedon acomputer. Second, arich paleoenvironmental record, basedon alluvial geomorphology,palynol- ogy,and dendroclimatology, permitsthe accurate quantitativereconstruction of annual

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uctuationsin potentialagricultural production in kilograms ofmaize perhectare [6]. Combined, thesefactors permit thecomputerized creation ofadynamic resourceland- scapethat accurately replicates actual conditions in thevalley from A.D. 200 to the present.The agents of the simulation interactwith one another and withtheir environ- menton thislandscape. Third, tree-ringchronology provides annual calendric dating. Fourth,intensive archaeological research,involving a 100%survey of the area supple- mentedby limited excavations,creates a databaseon human behaviorduring thelast 2,000years that constitutes the real-world targetfor the modeling [7]. Finally, histori- cal and ethnographic reportsof contemporary Pueblo groupsprovide anthropological analogs forprehistoric human behavior. Betweenroughly 7000 and 1800 B.C.,thevalley was sparsely occupied bypeople who dependedon huntingand gathering.The introduction ofmaize around 1800 B.C. beganthe transition to afood-producing economyand thebeginning of the Anasazi cul- tural tradition, which persisteduntil theabandonment ofthe region around A.D. 1300. Long HouseV alley providesarchaeological data on economic, settlement,social, and religiousconditions among alocalized Anasazi population. Thesearchaeological data provideevidence of stasis, variability, and changeagainst which theagent-based sim- ulation ofhuman behavioron thedynamic, artiŽcial Long HouseV alley landscape can be judged. Wehavetested a largenumber ofhypothesesabout the Long HouseV alley Anasazi [6, 1], butwe focus on onlytwo issues here: (1) the role of environment in explain- ing thepopulation dynamics ofsettlement placement, thelarge population increase after A.D. 1000,and thecomplete abandonment ofthe region around A.D. 1300;and (2) thesize of simulated and actual settlementsthat were selected and abandoned under variousenvironmental, demographic, and social conditions in differentyears.

3 Methods

TheArtiŽ cial Anasazi Projectis an agent-basedmodeling studybased on theSugarscape model createdby Joshua M. Epsteinand RobertAxtell [10]. The project was created to providean empirical, real-world evaluation ofthe principles and proceduresembodied in theSugarscape model and toexplore the ways in which bottom-up, agent-based computersimulations can illuminate human behaviorin areal world setting.The land- scape(analogous toSugarscape) iscreated from reconstructedenvironmental variables and ispopulated byartiŽ cial agents—in thiscase households, the basic social unitof local Anasazi society.Agent demographic and marriage characteristicsand nutritional requirementsare derived from ethnographic studiesof historical Pueblo groupsand othersubsistence agriculturists. Thesimulations takeplace onthislandscape ofannual variations in potentialmaize production valuesbased on empirical reconstructionsof low- and high-frequencypaleo- environmentalvariability in thestudy area. Theproduction valuesrepresent as closely aspossible the actual production potentialof various segments of the Long House Valley environmentover the period ofstudy.In general,the reconstructed environment formaize agriculture can becharacterized asdramatically improving about A.D. 1000, sufferinga deteriorationin themid 1100s,and improving until thelate 1200s, when thereis a major environmentaldisruption involvingthe Great Drought (1276– 1299), falling alluvial watertable levels, severe  oodplain erosion, and changesin theseasonal patterningof precipitation [5]. On thislandscape, theagents of the ArtiŽ cial Anasazi model play outtheir lives, adapting tochangesin theirphysical and social environments. TheŽ rststep was to enterrelevant environmental data, and data onreal sitelocation and size.Simulations usingthese landscapes varyin anumber ofways. The initial

ArtiŽcial Life Volume 9,Number 4 437 G.J.Gumerman, A.C.Swedlund, J. S.Dean, and J.M.EpsteinPrehistoric American Southwest population ofagents (households) can bescattered randomly or placed wherethey actually existedat some initial year.The simulations reportedhere were begun with the number ofagents(households) actually presentin thevalley during theinitial yearwith thehouseholds distributed randomly acrossthe artiŽ cial landscape. Theenvironmental parametersmay beleft as they were originally reconstructedor adjustedto enhanceor reducemaize production. Finally, and mostimportantly, therules by which theagents operatemay bechanged. Thesimulation has22 user-controlled variables thatgovern bothagent interactions and interactionwith the annually changing environment. Agent(household) behavioron theproduction landscape isgoverned by agent at- tributesand asetof simple rulesentrained sequentially. Standard demographic tables forsubsistence agriculturalists areused to determinenutritional requirements,marriage agesand reproduction rates,and householdŽ ssioningand longevity.A household (agent)consists of Ž veindividuals, twoparents and threechildren, each withnutri- tional requirementsthat are represented in themodel by160 kg of maize perperson peryear for a totalrequirement of 800 kg of maize perhousehold per year. Because ethnographic data indicate thatmodern Puebloans tryto keepat least two years’ worth ofcorn on hand, our agentsattempt to have at least two years’ supply (1600 kg) in storageafter the harvest in September.An internal clock tracksthe amount ofmaize each householdhas in storage.This quantityis diminished each month bythe amount consumedby the household and isreplenished once a yearby the amount harvested atthe end of the growing season. The amount harvestedequals the reconstructed po- tentialproduction ofthe household’ s farmland minus avariable percentagethat re ects fallowing, insectdamage, and reservationof seed corn. EveryApril, each household assessesthe status of its food supply, adding whatit expects to have in storageby harvesttime to thepredicted yield of its farmplot forthe coming growingseason based on theprevious year’ s production. Ifthe expected stored amount plus thepredicted yieldexceeds 1600 kg, the household decides to maintain itscurrent Ž eldsand stay whereit is. Ifthe sum isless than 1600 kg, the household decides to move to amore productivelocation wheresufŽ cient yield can beexpected. Movementrules for agents are triggered when a newhousehold is created by the marriage ofaresidentfemale or whena householddetermines in April thatthe amount ofstored maize plus thepredicted maize production ofits current farmplot cannot sustainit for the coming year.Once a householddecides to move to amore productive location, itemploys three sufŽ ciency criteria forselecting new farmland: (1) theplot mustbe currently unfarmed; (2) theplot mustbe currently uninhabited; and (3) the plot musthave a minimum estimatedpotential maize production of160 kg of maize perhousehold member. Thereare also threesufŽ ciency criteria forselecting residential sites:(1) thesite must be within 2km ofthe farmplot; (2)the site must be unfarmed; and (3) thesite must be less productive than the selected farmplot. Ifmore than one sitemeets the sufŽ ciency criteria, thesite selected is the one with closest access to domesticwater. The fact that potential residential locations neednot be unoccupied allows thedevelopment of multihousehold settlements. Howclosely the simulations mimic thehistorical data providesthe most obvious test ofmodel adequacy, or “generativesufŽ ciency” in theterminology of Epstein [9]. We mustask: Dothese exceedingly simple rulesfor household behavior ,whensubjected tothe parallel computation ofother agents and reactingto a dynamic environment, produce thecomplex behaviorthat actually did evolve,or aremore complex rules necessary?When it is free to vary, does the population trajectoryfollow therecon- structedcurve, and doesthe population aggregateinto villages when we know the population actually did? Doesthe simulated population crash at A.D. 1300,as we know itdid? Dothe simulated settlementsizes and population densitiesclosely associated withhierarchy known forthe area emergethrough time?

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4Results and Discussion

While potentiallyenormously informative, agent-basedsimulations remain theoretical constructsunless their outcomes are independently evaluated against actual casesthat involvesimilar entities,landscapes, and behavior. Thedegree of Ž tbetweenthe results ofa simulation and comparable real-world situationsallows theexplanatory power of thesociocultural model encodedin thesimulation’ s structureto beobjectively assessed. Lack ofŽ timplies thatthe model isin someway inadequate. Such “failures”are likely tobe as informative as successes, because they illuminate deŽciencies of explanation and indicate potentiallyfruitful new research approaches. Departuresof real human behaviorfrom theexpectations of a model identifypotential causal variables notin- cluded in themodel orspecifynew evidence to besought in thearchaeological record ofhuman activities. Themost appropriate comparisons betweenthe model and thereal world beginat A.D. 400with the same number ofrandomly locatedsimulated householdsas in that year’s actual historical situation, aswell asthe environmental situation as it has been reconstructedfor each year.The simulation ofhousehold and Želdlocations, aswell as thesize of each community (thenumber ofhouseholds at each site),runs on an annual basis, operatingunder the movement rules on thechanging resourcelandscape. Amap ofannual simulated Želdlocations and householdresidence locations and sizesruns simultaneouslywith a map oftheactual archaeological and environmentaldata sothat thereal and simulated population dynamics and residencelocations can becompared (Figures1, 2, 3). Inaddition, timeseries plots and histogramsillustrate annual variation in simulated and actual population numbers, aggregationof population, location and sizeof residences by environmental zone, simulated amounts ofmaize storedand harvested,and thenumber ofhouseholds that Ž ssion,die out, or leavethe valley.

Real Long House Valley :Around 1150,largely in responseto changes in productive ² potential, theinhabitants beganto aggregate in localities particularly suitablefor farming underthe changing hydrologic and climatic conditions. This changein population distributioninitiated a trendtoward increasing sociocultural complexity, adevelopmentdriven by problems resultingfrom increasing settlementsize and population density.Among these problems arecoordinating theactivities of larger groupsof people, taskallocation, conict resolution,and theaccumulation, storage,control, and redistributionof critical resourcessuch as food and domestic water.An important outcomeof this trend was the development of a settlement hierarchy that,by A.D. 1250,involved four levels of organization: theindividual habitation site,the central pueblo ,thesite cluster of 5 to20habitation sitesfocused on acentralpueblo, and thevalley as a whole. This settlementsystem is evident in theconcentration of sitesin favorablelocalities withempty areas in between,the structuredspatial and conŽgurational relationships among siteswithin clusters,and line-of-sightrelationships betweenthe clusters’ central pueblos. ArtiŽcial Long House Valley :Thesimulation exhibitsthe demographic markersof ² thereal situation. Thegreatest similarity isthe development of site clusters in the samelocalities asthe actual ones(Figures 1, 2)and thereplication ofthe location and sizeof the site of Long Houseitself (Figure 2). Inthe ArtiŽ cial Anasazi source code, hierarchy ofany kind isnot explicitly modeled. However,in thehistorical recordthere is an extremelyhigh correlation betweenorganizational hierarchy and settlementclustering. Clustering does emerge from themodel, and on thisbasis we guardedlyinfer the presence of hierarchy. Ratherthan producing asiteorgani- zational hierarchy in which thepopulation isdistributed across several kinds of

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Figure1. Simulated population distribution on the reconstructed environment (right) and the actual situation (left) in A.D. 1170.Hatching on both sides is thesimulated land under cultivation. Gray represents thedepth of the water table.Darker grayrepresents higherwater table,lighter gray represents lowerwater table.White is unfarmable.Dots, triangles,and squares represent settlements. Dots 5orfewer households.T riangles 6 to 20. Squares 21ormore. Settlements tend to be clustered in the same Dplaces, but simulatedsettlements areD more aggregated.The D positions of the largest settlements inthesimulated and actual situations are within100 m ofone another—thesquare on the upper arm of thenarrow canyon on the left. This is theactual site ofLong House after whichthe valley was named.

settlementunit, thesimulation tendsto pack peopleinto a fewlarge sites that correspondto each real sitecluster (Figure 2). Giventhe agent rules, this seems a reasonableŽ t,and population sizeand distributionsimilarities indicate thatthe artiŽcial versionof thecomplexity trajectory is in many waysequivalent to the actual situation. Asshown by the smaller sitesand morescattered settlements in thereal valleyat A.D. 1100(Figure 1), settlementclustering and sizegrowth begin somewhatearlier in themodel thanin theactual valley.This differencelikely is dueto lagsin theresponse of the real Anasazi tosigniŽ cant environmentalchanges.

By A.D. 1170(Figure 1), population concentrationshave developed in thesame localities in boththe real and simulated valleys.In both cases, a largeunoccupied area hasappeared in themiddle ofthe valley, and sitedensity is much reducedalong the easternmargin ofthe valley  oor. Alsoin bothcases, the settlement distributions result from combinations ofthree environmental factors: (1) thevalley  oor, which issubject toalluvial depositionand erosionand istherefore a poor place toestablish residences; (2) arable land nearwhich settlementscan belocated; and (3) domesticwater resources

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Figure2. Simulated population distribution on the reconstructed environment (right) and the actual situation (left) in A.D. 1270.Symbols are thesame as inFigure 1. In both cases thepopulation has begun to move out of the southernpart of thevalley because of erosion and a dropin the water table. thatwere concentrated along thenorthwestern margin ofthe valley  oor between A.D. 1130and 1180and after A.D. 1250.Large sites in thesimulation areequivalent to groupsof small sitesin thereal world. Early in theprocess, neither system exhibits ahierarchical settlementstructure. By A.D. 1270(Figure 2), theactual Long House Valley wasthe locus ofthe fully developed settlement organizational hierarchy. This developmentis evident in thespatial association ofsites of different size (see legend) on theleft image. Thesimulation (rightimage) showsless site size differentiation than thereal valley,with most of the population packed intolarge sites. Nevertheless, some differentiationis evident along thenorthwestern margin ofthe valley. In addition, the simulation accuratelycaptures the concentration of sites in thenorthern part ofthe valley,the clustering of sites, and thelocation and sizeof the largest actual sitein the valley,Long House. Comparing thesimulated (Figure4) and real timetrajectories of site sizes gener- atessome provocative inferences. The number ofsimulated siteswith more than39 householdspeaks around A.D. 1100,remains high fornearly two centuries, and drops precipitouslyat the end of the 13th century, with the largest sites disappearing shortly after A.D. 1300.In contrast, simulated siteswith fewer than 40 households maintain a fairly stableproŽ le and increasein number afterthe late 13th-century population crash and demiseof the large settlements. While therapid declineof the large sites mirrors theAnasazi abandonment ofthe real valleyaround A.D. 1300,the persistence of small tomedium sitesin thesimulation contrastssharply withthe abandonment ofall real sitesat that time.

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Figure3. Simulated population distribution on thereconstructed environment (right) the actual situation (left) in A.D. 1305.Symbols are thesame as inFig. 1. The actual population has abandoned the valley, but there are still settlements inthesimulated version.

Thedifferent responses by thesimulated and real Anasazi totheenvironmental crisis ofthe late 13th century have important explanatoryimplications. Ithaslong beenclear [4]that even the seriously degraded post- A.D. 1275environment of the valley could havesupported a certainnumber ofpeople and thatthe deleterious environmental conditions would nothave forced all theAnasazi todepart. Asmaller population could havesustained itself by abandoning largesettlements and dispersinginto smaller com- munitiessituated near the few locations thatremained agriculturally productive.The ArtiŽcial Anasazi do preciselythat, the reduced population shiftingfrom large, aggre- gatedcommunities intosmaller settlements(Figure 4) scattered across the northern part ofthe valley where isolated pockets of farmable land still exist(Figure 3). That thereal Anasazi employeda differentoption indicatesthat environmental degradation wasnot responsible for the complete abandonment ofthe valley and thatother, un- doubtedlysocial, factorswere involved in theŽ nal emigration. That thesesocial factors included theunwillingness or inability toforsake the relatively high levelof social com- plexityembedded in thehierarchical settlementsystem of the late 13th century for a simpler, disaggregatedsocial systemis supported by the ready dispersion of the ArtiŽ - cial Anasazi, who, drivenprimarily byenvironmental constraints, lacked suchcultural inhibitions. All theevidence indicates that by A.D. 1305,the real Anasazi (Figure3, left) had abandoned thevalley. The ArtiŽ cial Anasazi (Figure3, right), however,survived by spreadingout across the part ofthe valley that remained productiveeven under the

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Figure4. Changes in simulatedsettlement size. Largesettlements ( 80households)develop rapidly after A.D. 1050, uctuatein size for200 years, and disappear abruptly after A.D. 1300.¸ In sharp contrast, the number of smaller sites (4to 9 households)tends toincrease gradually until after A.D. 1300,when it increases more rapidly. worsenedenvironmental circumstances of the post-1300 period. This differenceac- curatelyre ects the fact that the real Anasazi could havestayed on byfarming the northernvalley  oor and dispersinginto medium-size communities [4]. Theenviron- mentallyunnecessary total abandonment ofthe real valleyundoubtedly re ects the pull ofsocial factorsdrawing peopleto the distant communities establishedby previ- ousemigrants from Long HouseValley. Elementsof this social attractionwould have included maintaining alargeenough pool ofpotential marriage partners,fulŽ lling cer- emonial and social obligations totheirformer neighbors, and retainingachieved levels ofsociocultural complexity.

5Conclusion

Insummary, agent-basedmodels are laboratories wherecompeting hypotheses and explanationsabout Anasazi behaviorcan betested and judgedin adisciplined, empir- ical way. Thesimple agentsposited here explain important aspectsof Anasazi history while leavingother important aspectsunaccounted for. Sitedistribution and density arewell approximated bythe agent-based simulations. Countlesssimulations have beenrun, and theresults we report here are quite robust. The hierarchical structure identiŽed in thearchaeological contextcan bemore closelyapproximated withsome logical modiŽcations tothe settlement rules in thesimulations. Theexplicit modeling ofhierarchical social structuresis a planned topic offuture model development.The departurebetween real Anasazi and ArtiŽcial Anasazi in theŽ nal period ofsettlement

ArtiŽcial Life Volume 9,Number 4 443 G.J.Gumerman, A.C.Swedlund, J. S.Dean, and J.M.EpsteinPrehistoric American Southwest isa fascinating challenge. Thepattern of abandonment isobserved in many regionsof theprehistoric Anasazi atapproximately thissame time. With agent-basedmodeling, wecan systematicallyalter the quantitative parameters or make qualitativechanges that introduce completely new, and evenunlikely, elements intothe artiŽ cial world ofthe simulation. Interms of the ArtiŽ cial Anasazi model, we can experimentwith agent attributes, such as fecundity or foodconsumption, and we can introducenew elements, such as mobile raiders, environmentalcatastrophes, or epidemics. Actual environmentalconstraints might have been the trigger to induce many ofthe Anasazi toabandon theregion; however,social or ideological factorswere responsiblefor the complete abandonment ofthe valley. Demographic and epidemi- ological modelsmay beutilized toderive additional parametersfor the agent-based modeling. Wehavealso consideredsynergies among variables in thereal contextthat wehave not yet experimented with in themodeling efforts.In this analysis, using thisbottom-up approach tomodeling prehistoricsettlement behaviors, we havegreatly improved our understandingof the underlying processes involved in thepopulation dynamics.

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