Page 141 -

138 J.M. Galán et al.

Bigbee, T., Cioffi-Revilla, C., & Luke, S. (2007). Replication of sugarscape using MASON. In T.
Terano, H. Kita, H. Deguchi, & K. Kijima (Eds.), Agent-based approaches in economic and
social complex systems IV: Post-proceedings of the AESCS international workshop 2005 (pp.
183–190). Tokyo: Springer.
Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human
systems. Proceedings of the National Academy of Sciences of the United States of America,
99(2), 7280–7287.
Castellano, C., Marsili, M., & Vespignani, A. (2000). Nonequilibrium phase transition in a model
for social influence. Physical Review Letters, 85(16), 3536–3539.
Christley, S., Xiang, X., & Madey, G. (2004). Ontology for agent-based modeling and simulation.
In C. M. Macal, D. Sallach, & M. J. North (Eds.), Proceedings of the agent 2004 conference
on social dynamics: interaction, reflexivity and emergence. Chicago, IL: Argonne National
Laboratory and The University of Chicago. http://www.agent2005.anl.gov/Agent2004.pdf.
Cioffi-Revilla, C. (2002). Invariance and universality in social agent-based simulations. Proceed-
ings of the National Academy of Sciences of the United States of America, 99(3), 7314–7316.
Conlisk, J. (1996). Why bounded rationality? Journal of Economic Literature, 34(2), 669–700.
David, N., Fachada, N., & Rosa, A. C. (2017). Verifying and validating simulations.
doi:https://doi.org/10.1007/978-3-319-66948-9_9.
Drogoul, A., Vanbergue, D., & Meurisse, T. (2003). Multi-agent based simulation: Where are the
agents? In J. S. Sichman, F. Bousquet, & P. Davidsson (Eds.), Proceedings of MABS 2002
multi-agent-based simulation. (Lecture Notes in Computer Science, 2581) (pp. 1–15). Bologna:
Springer.
Edmonds, B. (2001). The use of models: making MABS actually work. In S. Moss & P. Davidsson
(Eds.), Multi-agent-based simulation. (Lecture notes in artificial intelligence, 1979) (pp. 15–
32). Berlin: Springer.
Edmonds, B. (2005). Simulation and complexity: How they can relate. In V. Feldmann & K.
Mühlfeld (Eds.), Virtual worlds of precision: Computer-based simulations in the sciences and
social sciences (pp. 5–32). Lit-Verlag: Münster.
Edmonds, B. (2017). Different modelling purposes. doi:https://doi.org/10.1007/978-3-319-66948-
9_4.
Edmonds, B., & Hales, D. (2003). Replication, replication and replication: Some hard lessons
from model alignment. Journal of Artificial Societies and Social Simulation, 6(4). http://
jasss.soc.surrey.ac.uk/6/4/11.html.
Edmonds, B., & Hales, D. (2005). Computational Simulation as Theoretical Experiment. Journal
of Mathematical Sociology, 29, 1–24.
Edwards, M., Huet, S., Goreaud, F., & Deffuant, G. (2003). Comparing an individual-based
model of behaviour diffusion with its mean field aggregate approximation. Journal of Artificial
Societies and Social Simulation, 6(4). http://jasss.soc.surrey.ac.uk/6/4/9.html.
Epstein, J. M. (1999). Agent-based computational models and generative social science. Complex-
ity, 4(5), 41–60.
Epstein, J. M. (2008). Why model?. Journal of Artificial Societies and Social Simulation, 11(4), 12.
http://jasss.soc.surrey.ac.uk/11/4/12.html.
Epstein, J. M., & Axtell, R. L. (1996). Growing artificial societies: Social science from the bottom
up. Cambridge, MA: Brookings Institution Press/MIT Press.
Fensel, D. (2001). Ontologies: A silver bullet for knowledge management and electronic commerce.
Berlin: Springer.
Galán, J. M., et al. (2009). Errors and artefacts in agent-based modelling. Journal of Artificial
Societies and Social Simulation, 12(1). http://jasss.soc.surrey.ac.uk/12/1/1.html.
Galán, J. M., & Izquierdo, L. R. (2005). Appearances can be deceiving: lessons learned re-
implementing Axelrod’s ‘evolutionary approach to norms’. Journal of Artificial Societies and
Social Simulation, 8(3). http://jasss.soc.surrey.ac.uk/8/3/2.html
Gilbert, N. (1999). Simulation: A new way of doing social science. The American Behavioral
Scientist, 42(10), 1485–1487.
Gilbert, N. (2007). Agent-based models. London: Sage Publications.