Abstract
The primary theme of this chapter is trying to describe, discuss and understand how human societies change over time using agent-based modeling. Agents become a major paradigm of social simulation allow us to model the complex social phenomena under the bottom-up approach. Certainly one of the key points of the bottom-up approach is the emergence of macro level phenomena from micro level actions and interactions. The main objective of this work is to build a Virtual Social Laboratory, from Rafael Pla Lopez Social evolution model, in order to explore the social evolution of a set of artificial societies/agents that evolve within a grid of cells which are characterized by a level of natural resources (artificial environment). This laboratory can help to explore and understand the East–West duality, the North–South Divide, the Human migration process, the globalization-polarization and some possible human social evolution.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Axelrod, R. (1997). The dissemination of culture—A model with local convergence and global polarization. Journal of Conflict Resolution, 41(2), 203–226.
Cioffi-Revilla, C., Luke, S., Parker, D. C., Daniel Rogers, J., Fitzhugh, W. W., Honeychurch, W., et al. (2007). Agent based modeling simulation of social adaptation and long-term change in inner Asia. In T. Terano & D. Sallach (Eds.), Advancing social simulation: The first world congress in social simulation. Tokyo: Springer.
Dahrendorf, R. (1958). Toward a theory of social conflict. Journal of Conflict Resolution, 2(2), 170–183.
Engels, F. (1884). Der Ursprung aus der Familie, der Privateigentum un der Staat, Zurich (translated to Spanish as “El Origen de la Familia, la Propiedad Privada y el Estado”, Fundamentos, Madrid, 1970).
Epstein, J. M., & Axtell, R. L. (1996). Growing artificial societies: Social science from the bottom up. Cambridge, MA: MIT Press.
Fukuyama, F. (1995). Reflections on the End of History, Five Years Later. History and Theory, Vol. 34, No. 2, Theme Issue 34: World Historians and Their Critics (May, 1995), pp. 27–43 Blackwell Publishing for Wesleyan University.
Giner, J. (s.f). Conflicto social (Teorías del). Retrieved from http://www.ucm.es/info/eurotheo/diccionario/C/conficto_social_teorias.pdf.
Godelier, M. (1970). Schéms d’evolution des sociétés (translated to Spanish as “Esquemas de evolución de las sociedades”, Miguel Castellote Editor, aprox. in 1970).
Izquierdo, L. R., Izquierdo, S. S., Galán, J. M., & Santos, J. I. (2009). Techniques to understand computer simulations: Markov chain analysis. Journal of Artificial Societies and Social Simulation, 12(1), 6. http://jasss.soc.surrey.ac.uk/12/1/6/appendixB/EpsteinAxtell1996.html, http://jasss.soc.surrey.ac.uk/12/1/6/appendixB/axelrod1997.html.
Marx, K., & Engels, F. (1888). Manifesto of the Communist Party, Written, Late 1847, First Published: February 1848; Source: Marx/Engels Selected Works, Vol. One, Progress Publishers, Moscow, 1969, pp. 98–137; Translated: Samuel Moore in cooperation with Frederick Engels, 1888.
Nemiche, M. (2002). Un modelo Sistémico de Evolución Social Dual. Doctoral thesis, Universidad de Valencia, Spain, ISBN: 8437059720.
Nemiche, M., M’Hamdi, A., Chakraoui, M., Cavero, V., & Pla Lopez, R. (2013). A theoretical agent-based model to simulate an artificial social evolution. Systems Research and Behavioral Science, 30, 693–702. doi:10.1002/sres.2238.
Nemiche, M., & Pla-Lopez, R. (2000). A model of dual evolution of the humanity. en 2nd International Conference on Sociocybernetics, Panticosa, 25–30 June. Retrieved from http://www.uv.es/~pla/models/MDEHabrid.htm.
Nemiche, M., & Pla-Lopez, R. (2003). A learning model for the dual evolution of human social behaviors. Kybernetes: The International Journal of Systems and Cybernetics, 32(5/6), 679–691.
Pla-López, R. (1989). Model of social evolution from science and power. en XVIIIth International Congress of History of Science, Hamburg & Munich.
Pla-Lopez, R. (2007). A simulation of the duality North-South in social evolution. In 7th International Conference of Sociocybernetics “Technology and Social Complexity”, Murcia, Spain, 18–23 June 2007.
Pla-López, R. (1988). Introduction to a learning general theory. Cybernetics and Systems: An International Journal, 19, 411–429. Hemisphere Publishing Corporation, The Austrian Society for Cybernetic Studies.
Pla-Lopez, R., & Nemiche, M. (2002, June 12–14). Consecuencias del ataque a las Torres Gemelas para la Evolución de la Humanidad. In L. Ferrer, A. Caselles, J. Martínez, R. Pla, & I. Martínez de Lejarza (Eds.), II Reunión Española de Ciencia de Sistemas (RECS-II), València. Published in Ciudad, sociedad, educación, control, caos y autoorganización, Universitat de València-Departament de Matemàtica Aplicada, ISBN 84-370-5528-8. Retrieved from http://www.uv.es/~pla/models/torres.htm.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix
Appendix
The model is implemented in java source code
-
1.
Class SocialVisualizer that implements a graphical interface as a grid to visualize the dynamic model
-
2.
Class SocialModel that implements the two-layer structure of Model (Resources and agents). The main tasks (methods) are:
Initialization:
-
Initialize “constants” (parameters of the model) from configuration file
-
Create resources
-
Initializes resources
-
Create agents (list of Societies Live)
-
Initializes agents (Initializes memory, probability, Repressive Capacity and Suffered Social Repression)
-
Main loop
public void run() { for ( T=0 ; T <= Tmax ; T += deltaT ) { for ( nAgent = 0; nAgent < listAgent.length; nAgent ++) { listAgent[nAgent].updateAgent(listAgent); } if ( getNumberAgentLive() == 0 ){ fLog.println("End: are not living systems."); break; } migration(); updateResources(); sleep(delay); } }
-
3.
Class Agent that implements dynamics and evolution of internal agent processes. The main methods are:
Initialization:
public void init() { initAccumulatedMemory(); initForce(); initFerocity(); initSatisfactionCapacity(); initRepressiveCapacity(); }
Update Agent:
public void updateAgent( Agent [] listAgents ) { if( this.isLive() ){ updateProbability(); updateSocialSufferedRepression(listAgents); updateRepressiveCapacity(); updateSatisfactionFunction(); updateAccumulatedMemory(); updateResourceAgent(); if( ! this.isDeath() ){ checkProgress (); } }else{ checkRecuperation(); } }
Rights and permissions
Copyright information
© 2017 Springer International Publishing Switzerland
About this chapter
Cite this chapter
M’hamdi, A., Nemiche, M., Pla Lopez, R., Ezzahra SFA, F., Sidati, K., Baz, O. (2017). A Generic Agent-Based Model of Historical Social Behaviors Change. In: Nemiche, M., Essaaidi, M. (eds) Advances in Complex Societal, Environmental and Engineered Systems. Nonlinear Systems and Complexity, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-46164-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-46164-9_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-46163-2
Online ISBN: 978-3-319-46164-9
eBook Packages: EngineeringEngineering (R0)