The bio-cultural, cognitive, and evolutionary sciences of religion comprise a growing interdisciplinary field.   The following is a list of important publications in this and related fields that are especially relevant for computer modeling and simulation in the study of religion.

Books

Bainbridge, W. S. (2006). God from the Machine: Artificial Intelligence Models of Religious Cognition. Lanham, MD: AltaMira Press.

Grimm, V., & Railsback, S. F. (2005). Individual-based Modeling and Ecology. Princeton: Princeton University Press.

Epstein, J. M. (1997). Nonlinear Dynamics, Mathematical Biology, And Social Science: Wise Use Of Alternative Therapies. Reading, Mass: Westview Press.

Epstein, J. M. (2006). Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton: Princeton University Press.

Epstein, J. M. (2014). Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science. Princeton, NJ: Princeton University Press.

Epstein, J. M., & Axtell, R. L. (1996). Growing Artificial Societies: Social Science From the Bottom Up (1St Edition edition). Washington, D.C: Brookings Institution Press & MIT Press.

Watts, F., & Turner, L. P. (2014). Evolution, Religion, and Cognitive Science: Critical and Constructive Essays. OUP Oxford.

Articles

Abdollahian, M., & Kang, K. (2008). In Search of Structure: The Nonlinear Dynamics of Power Transitions. International Interactions, 34(4), 333–357. doi.org/10.1080/03050620802574887

Abdollahian, M., Yang, Z., Coan, T., & Yesilada, B. (2013). Human development dynamics: an agent based simulation of macro social systems and individual heterogeneous evolutionary games. Complex Adaptive Systems Modeling, 1(1), 18. doi.org/10.1186/2194-3206-1-18

Axelrod, R. (1997). The Dissemination of Culture: A Model with Local Convergence and Global Polarization. Journal of Conflict Resolution, 41(2), 203–226. doi.org/10.1177/0022002797041002001

Axtell, R. L., Epstein, J. M., Dean, J. S., Gumerman, G. J., Swedlund, A. C., Harburger, J., … Parker, M. (2002). Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley. Proceedings of the National Academy of Sciences, 99(suppl 3), 7275–7279. doi.org/10.1073/pnas.092080799

Baumard, N., & Chevallier, C. (2015). The nature and dynamics of world religions: a life-history approach. Proc. R. Soc. B, 282(1818), 20151593. doi.org/10.1098/rspb.2015.1593

Butzer, K. W. (2012). Collapse, environment, and society. Proceedings of the National Academy of Sciences, 109(10), 3632–3639. doi.org/10.1073/pnas.1114845109

Conte, R., & Paolucci, M. (2014). On agent-based modeling and computational social science. Theoretical and Philosophical Psychology, 5, 668. doi.org/10.3389/fpsyg.2014.00668

Crabtree, S. A., & Kohler, T. A. (2012). Modelling across millennia: Interdisciplinary paths to ancient socio-ecological systems. Ecological Modelling, 241, 2–4. doi.org/10.1016/j.ecolmodel.2012.02.023

Doran, J. (28-Dec-97). Simulating Collective Misbelief. Journal of Artificial Societies and Social Simulation 1(1). jasss.soc.surrey.ac.uk/1/1/3.html

Fehr, E., & Fischbacher, U. (2004). Social norms and human cooperation. Trends in Cognitive Sciences, 8(4), 185–190. doi.org/10.1016/j.tics.2004.02.007

Graves, D. (2011). The use of predictive modelling to target Neolithic settlement and occupation activity in mainland Scotland. Journal of Archaeological Science, 38(3), 633–656. doi.org/10.1016/j.jas.2010.10.016

Inglehart, R., & Baker, W. E. (2000). Modernization, Cultural Change, and the Persistence of Traditional Values. American Sociological Review, 65(1), 19. doi.org/10.2307/2657288

Kohler, T. A., Bocinsky, R. K., Cockburn, D., Crabtree, S. A., Varien, M. D., Kolm, K. E., … Kobti, Z. (2012). Modelling prehispanic Pueblo societies in their ecosystems. Ecological Modelling, 241, 30–41. doi.org/10.1016/j.ecolmodel.2012.01.002

Madey, C. N. and G., & Madley, G. (2009). Tools of the Trade: A Survey of Various Agent Based Modeling Platforms. Journal of Artificial Societies and Social Simulation, 12(2). http://jasss.soc.surrey.ac.uk/12/2/2.html

Metzler, T. (2001). Can Agent-Based Simulation Improve Dialogue between Science and Theology?  Journal of Artificial Societies and Social Simulation 5(1). http://jasss.soc.surrey.ac.uk/5/1/5.html

Murphy, J. T. (2012). Exploring complexity with the Hohokam Water Management Simulation: A middle way for archaeological modeling. Ecological Modelling, 241, 15–29. doi.org/10.1016/j.ecolmodel.2011.12.026

Neyapti, B. (2013). Modeling institutional evolution. Economic Systems, 37(1), 1–16. doi.org/10.1016/j.ecosys.2012.05.004

Nielbo, K. L., Braxton, D. M., & Upal, A. (2012). Computing Religion: A New Tool in the Multilevel Analysis of Religion. Method & Theory in the Study of Religion, 24(3), 267–290. doi.org/10.1163/157006812X635709

Nielbo, K. L., & Sørensen, J. (2015). Attentional resource allocation and cultural modulation in a computational model of ritualized behavior. Religion, Brain & Behavior. doi.org/10.1080/2153599X.2015.1087420

Parker, D. C., Hessl, A., & Davis, S. C. (2008). Complexity, land-use modeling, and the human dimension: Fundamental challenges for mapping unknown outcome spaces. Geoforum, 39(2), 789–804. doi.org/10.1016/j.geoforum.2007.05.005

Pecora, L. M., & Carroll, T. L. (1990). Synchronization in chaotic systems. Physical Review Letters, 64(8), 821–824. doi.org/10.1103/PhysRevLett.64.821

Powers, S. T., & Lehmann, L. (2013). The co-evolution of social institutions, demography, and large-scale human cooperation. Ecology Letters, 16(11), 1356–1364. doi.org/10.1111/ele.12178

Powers, S. T., & Lehmann, L. (2014). An evolutionary model explaining the Neolithic transition from egalitarianism to leadership and despotism. Proc. R. Soc. B, 281(1791), 20141349. doi.org/10.1098/rspb.2014.1349

Rodrik, D. (1998). Globalisation, Social Conflict and Economic Growth. The World Economy, 21(2), 143–158. doi.org/10.1111/1467-9701.00124

Rogers, J. D., Nichols, T., Emmerich, T., Latek, M., & Cioffi-Revilla, C. (2012). Modeling scale and variability in human–environmental interactions in Inner Asia. Ecological Modelling, 241, 5–14. doi.org/10.1016/j.ecolmodel.2011.11.025

Roitto, R. (2015). Dangerous but contagious altruism: recruitment of group members and reform of cooperation style through altruism in two modified versions of Hammond and Axelrod’s simulation of ethnocentric cooperation. Religion, Brain & Behavior. doi.org/10.1080/2153599X.2015.1022795

Sala-i-Martin, X. X. (1996). Regional cohesion: evidence and theories of regional growth and convergence. European Economic Review, 40(6), 1325–1352. doi.org/10.1016/0014-2921(95)00029-1

Sigmund, K., & Nowak, M. A. (1999). Evolutionary game theory. Current Biology, 9(14), R503–R505. doi.org/10.1016/S0960-9822(99)80321-2

Tremlin, T. (2002). A Theory of Religious Modulation: Reconciling Religious Modes and Ritual Arrangements. Journal of Cognition and Culture, 2(4), 309–348. doi.org/10.1163/15685370260441017

Trenholme, R. (1994). Analog Simulation. Philosophy of Science, 61(1), 115–131.

Upal, M. A. (2005). Simulating the Emergence of New Religious Movements.  Journal of Artificial Societies and Social Simulation, 8. http://jasss.soc.surrey.ac.uk/8/1/6.html

Whitehouse, H., Kahn, K., Hochberg, M. E., & Bryson, J. J. (2012). The role for simulations in theory construction for the social sciences: case studies concerning Divergent Modes of Religiosity. Religion, Brain & Behavior, 2(3), 182–224. doi.org/10.1080/2153599X.2012.691033

Wildman, W. J., & Sosis, R. (2011). Stability of Groups with Costly Beliefs and Practices. Journal of Artificial Societies and Social Simulation, 14(3).

Yang, Y.-H., Bhikshu, H., & Tsaih, R.-H. (2015). The Power of One Sentient Being: The Computer Simulation of a Bodhisattva’s Altruism Using Agent-based Modelling. Contemporary Buddhism: An Interdisciplinary Journal. doi.org/10.1080/14639947.2015.1041676