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Understanding Artificial Anasazi

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Abstract

A replication and analysis of the Artificial Anasazi model is presented. It is shown that the success of replicating historical data is based on two parameters that adjust the carrying capacity of the Long House Valley. Compared to population estimates equal to the carrying capacity the specific agent behavior contributes only a modest improvement of the model to fit the archaeological records.

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  • Marco A. Janssen, 2009. "Understanding Artificial Anasazi," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-13.
    • Handle: RePEc:jas:jasssj:2009-50-2
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    1. Robert G. Reynolds & Timothy A. Kohler & Ziad Kobti, 2003. "The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region," Computational and Mathematical Organization Theory, Springer, vol. 9(3), pages 227-254, October.
    2. Jared M. Diamond, 2002. "Life with the artificial Anasazi," Nature, Nature, vol. 419(6907), pages 567-568, October.
    3. Bruce Edmonds & David Hales, 2003. "Replication, Replication and Replication: Some Hard Lessons from Model Alignmen," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(4), pages 1-11.
    4. Oliver Will & Rainer Hegselmann, 2008. "A Replication That Failed - on the Computational Model in 'Michael W. Macy and Yoshimichi Sato: Trust, Cooperation and Market Formation in the U.S. and Japan. Proceedings of the National Academy of Sc," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(3), pages 1-3.
    5. Rick L. Riolo & Michael D. Cohen & Robert Axelrod, 2001. "Evolution of cooperation without reciprocity," Nature, Nature, vol. 414(6862), pages 441-443, November.
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    1. Carrella, Ernesto & Saul, Steven & Marshall, Kristin & Burgess, Matthew G. & Cabral, Reniel B. & Bailey, Richard M. & Dorsett, Chris & Drexler, Michael & Madsen, Jens Koed & Merkl, Andreas, 2020. "Simple Adaptive Rules Describe Fishing Behaviour Better than Perfect Rationality in the US West Coast Groundfish Fishery," Ecological Economics, Elsevier, vol. 169(C).
    2. Chathika Gunaratne & Ivan Garibay, 2020. "Evolutionary model discovery of causal factors behind the socio-agricultural behavior of the Ancestral Pueblo," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-18, December.
    3. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    4. James D. A. Millington & John Wainwright, 2016. "Comparative Approaches for Innovation in Agent-Based Modelling of Landscape Change," Land, MDPI, vol. 5(2), pages 1-4, May.
    5. Lee, Ju-Sung & Filatova, Tatiana & Ligmann-Zielinska, Arika & Hassani-Mahmooei, Behrooz & Stonedahl, Forrest & Lorscheid, Iris & Voinov, Alexey & Polhill, J. Gareth & Sun, Zhanli & Parker, Dawn C., 2015. "The complexities of agent-based modeling output analysis," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 18(4).
    6. Joaquim Carvalho & Rui L. Lopes & João Tojo, 2011. "Modeling Settlement Patterns In Real Territories," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 14(04), pages 549-565.

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