One of the advantages of simulation models is the ability to develop models which explore the future (economic development, climate change) or the past (archaeology). In this chapter we discuss examples of the use of models in archaeology to compare possible explanations of the rise and fall of ancient societies (Kohler and van der Leeuw, 2007).
In discussing these models we also will discuss some more complicated models where data is imported to the model. For example, importing data to recreate historical landscapes and climate records.
The Artificial Anasazi model is one of the icon models of the agent-based modeling community. The model describes the population dynamics in the Long House Valley in Arizona between 800 and 1350. For many years archaeologists have studied the collapse of the Anasazi. Around 1350 the Anasazi seems to have disappeared. What wasthe cause of this disappearence? One of the main hypotheses is that prolonged drought made it impossible for the Anasazi to continue their livelihood. In order to test whether climate change led to the collapse of the Anasazi, archaeologist George Gumerman collaborated with colleagues and modelers to develop an agent-based model. They used many available data sets about the climate records, soil types combined with insights about the societies of those time: family size, population demographics, storage of corn, etc. A Netlogo model version can be found at http://www.openabm.org/model/2222
Can they simulate the population numbers over time as estimated by the archaeologists? These estimates are very rough. They are based on counts of rooms and buildings, estimates of how long these buildings were used, and how many people were living in a building. For each site excavated the starting year of occupation, the end day of occupation and the maximum number of households is estimated. A lot of these estimates are based on wood pieces found in the remains of the buildings and comparing these pieces with the tree ring data base to determine when a piece of wood was cut. If we combine many estimates of small settlements we end up with Figure 1. Although the graph gives the impression of a precise count of numbers, this impression is only caused by adding many rough estimates. It clearly shows that after 1300 no evidence is found of occupation of the valley.
Figure 1: Estimates of the number of households in the Long House Valley over time.
The model developed by Gumerman et al. basically simulates households who perform agriculture and try to feed themselves. There is no social hierarchy, no exchange of resource, no kinship networks, etc. The only interaction of households is indirectly via the occupation of a site for agriculture. Agents have a unique spot for agriculture on the landscape, and live on a nearby spot. The climate variability results in some years being more agriculturally productive than others. Households can store excess corn for up to three years. If a household does not get enough food it will look for another spot. If no suitable spot is available, they leave the valley. No agents enter from outside the valley. Households also have their own demography. They produce offspring (other households from their children) and die of old age.
The model shows that with simple household rules for choosing the locations of farms and settlements, archaeological based demographic records on the occupation of the Anasazi in Long House Valley can be reproduced. The model analysis also shows that the abandonment of the valley around 1300 cannot be explained solely by environmental variations. Figure 2 shows the best fit of the model with the data. This fit is derived by tweaking a number of parameters, such as the fertility probability, the variance of harvest among plots with the same soil, the maximum age of a household, etc.
Figure 2: Simulated (“best” fit) and historical data for the parameter values from Axtell et al. (2002).
One of the differences of the Anasazi model wehn compared to previous models we discussed is the use of large sets of data. Below you see the code for importing some data from the file water.txt. You first define a list water-data, and then read through the file to import all the data in the list water-data. The model starts reading the file at the beginning of the file and continues till the end of the site. The command sentence makes a list out of values. In the water.txt file there are 6 types of data for each year, and therefore we see the structure list (list file-read file-read file-read file-read file-read file-read). This leads to a list like [ [1 2 3 4 5 6] [11 12 13 14 15 16]]. When all data is read, the file is closed.
set water-data  file-open "water.txt" while [ not file-at-end? ] [ set water-data sentence water-data (list (list file-read file-read file-read file-read file-read file-read)) ] file-close
The model of the Artificial Anasazi is based on an actual case which helps to test the model, but the model outcomes are also driven by the input data (Janssen, 2009). In Janssen (2010) a more abstract model is developed to simulate population dynamics of households on a larger scale in the ancient south west. Instead of one valley, there are multiple places where agents can live. The agents also share food within a settlement and exchange food in a limited way between “valleys”. The landscape is artificial and by doing many simulations we generate many possible landscapes to see the sensitivities of the results of variations of possible landscapes. Still we use climate input data to capture the type of resource variability the population experience. The model can be found at http://www.openabm.org/model-archive/populationaggregationinaridenvironments
One of the questions is what drives the population size in the larger landscape and the movements of the agents. We know from archaeological data that people moved alot on the landscape. Was this driven by soil degradation, climate variability or other causes? Where did the households move to? With a model we cannot answer an empirical question, but we can test possible causal relationships.
Compared to the Artificial Anasazi model, Janssen (2010) added a number of new mechanisms:
soil degradation. The more people use the land in a valley for a long time, the more the soil gets degraded. This means that less output is derived with the same inputs. One the other hand there is a modest increase of production if more people are in the same valley. People can cooperate to manage their plots of land which can increase the production.
Agents share resources within a settlement. This will reduce the inequality of resources among agents in a settlement, and increase the likelihood that agents are sufficiently fed. Janssen (2010) tested different forms of sharing.
Settlements exchange resources. Settlements that have shortages will ask settlements with surplus to give them food. Such requests are rewarded if the settlements who ask have a good reputation. Depending on the distance a share of the original surplus id provided to the other village.
The results show that the climactic amerlioration leads to an increased carrying capacity for the environment. Droughts lead households to leave the settlement and look for better places. This avoids the issue that soils are depleted severely. After a settlement is abandoned the soil can recover if it is occupied in later years. Hence the climate variability results in the agents not to staying too long at one place and not depleting the soils.
Axtell R L, Epstein J M, Dean J S, Gumerman G J, Swedlund A C, Harburger J, Chakravarty S, Hammond R, Parker J, and Parker M. (2002) Population Growth and Collapse in a Multi-Agent Model of the Kayenta Anasazi in Long House Valley. Proceedings of the National Academy of Sciences of the United States of America 99(3): 7275-7279.
Janssen, M.A. (2009) Understanding Artificial Anasazi, Journal of Artificial Societies and Social Simulation 12 (4) 13 http://jasss.soc.surrey.ac.uk/12/4/13.html
Janssen, M.A. (2010) Population aggregation in the ancient arid environments, Ecology and Society 15(2): 19. [online] URL: http://www.ecologyandsociety.org/vol15/iss2/art19/
Kohler, T A , Gumerman, G J and Reynolds, R G (2005) Simulating ancient societies, Scientific American 293(1): 76-82
Kohler, T A and van der Leeuw, S A (eds) (2007) The Model-based Archaeology of Socionatural Systems, School for Advanced Research Press.