Towards Validating a Model of Households and Societies in East Africa
One of the major challenges of social simulations is the validation of the models. When modeling societies, where experimentation is not practical or ethical, validation of models is inherently difficult. However, one of the significant strengths of the agent-based modeling (ABM) approach is that it begins with the implementation of a theory of behavior for relatively low-level agents and then produces high-level behaviors emerging from the low-level theory’s implementation. Our ABM model of societies is based on modeling the decision making of rural households in a 1,600 km (1,000 mile) square around Lake Victoria in East Africa. We report on the first validation of our model of households making their living on a daily basis by comparing resulting activities against societal data collected by anthropologists.
KeywordsAgent-based modeling East Africa Household decision making
This work was supported by the Center for Social Complexity at George Mason University and by the Office of Naval Research (ONR) under a Multidisciplinary University Research Initiative (MURI) Grant no. N00014-08-1-0921. The authors thank the members of the Mason-HRAF Joint Project on Eastern Africa (MURI Team), especially Jeffrey K. Bassett, Atesmachew B. Hailegiorgis, Joseph Harrison, and Eric Scott for their comments and discussions. Carol Ember, Ian Skoggard, and Teferi Abate of HRAF provided assistance with the anthropological data. The opinions, findings, and conclusions or recommendations expressed in this work are those of the authors and do not necessarily reflect the views of the sponsors.
- 1.Cioffi-Revilla C (2010) MASON RebeLand and data aspects of agent-based simulation models. In: Schmorrow D, Nicholson D (eds) Advances in cross-cultural decision making. CRC Press-Taylor and Francis, Orlando, pp 291–301Google Scholar
- 2.Hailegiorgis AB, Kennedy WG, Catalin Balan G, Bassett JK, Gulden T (2010) An agent based model of climate change and conflict among pastoralists in East Africa. In: Proceedings of the international congress on environmental modeling and software (IEMSS2010), OttawaGoogle Scholar
- 3.Kennedy WG, Bassett, JK (2011) Implementing a “fast and frugal” cognitive model within a computational social simulation. In: Proceedings of the second annual conference of the Computational Social Science Society of the Americas CSSSA-2011, Santa FeGoogle Scholar
- 4.Kennedy WG, Gulden T, Hailegiorgis AB, Bassett JK, Coletti M, Catalin Balan G, Clark M, Cioffi-Revilla C (2010) An agent-based model of conflict in East Africa and the effect of the privatization of land. In: Proceedings of the third world congress on social simulation WCSS-2010, KasselGoogle Scholar
- 5.Lewis IM (1955) Peoples of the horn of Africa. International African Institute, LondonGoogle Scholar
- 7.McCabe JT (2004) Cattle bring us to our enemies. University of Michigan Press, Ann ArborGoogle Scholar
- 9.Luke S (2012) Multiagent simulation and the MASON library. http://cs.gmu.edu/~eclab/projects/mason/
- 10.Cioffi-Revilla C, Crooks A, De Jong K, Gulden T, Kennedy W, Luke S, Coletti M (2012) MASON RiftLand: an agent-based model for analyzing conflicts, disasters, and humanitarian crises in east Africa. Working Paper, Mason-Yale Joint Project on Eastern Africa. Center for Social Complexity, George Mason University, FairfaxGoogle Scholar
- 12.Murdock GP (1967) Ethnographic atlas: a summary (codes). Int J Cult Soc Anthropol 4:154–169Google Scholar
- 14.Taylor BK (1962) The west Lacustrine Bantu. International African Institute, LondonGoogle Scholar