Analysis of Wealth Distribution Based on the Renewal Interval of Natural Resources Through Agent-Based Simulation
DOI:
https://doi.org/10.18041/1909-2458/ingeniare.14.610Keywords:
Agent-based simulation, Social standard, Renewable and non-renewable resourcesAbstract
This research paper presents the results of the performance analysis in the distribution of wealth in three social standards of living from the assessment of economies based on renewable and non-renewable resources, contextualized in the Colombian economy, given the high levels poverty that are registered in this country. In the course of the investigation a thorough review of theoretical aspects of renewable and non-renewable resources, levels of social groups and agent-based simulation was made. Also, a model of agent-based simulation was designed which allowed to analyze the distribution of wealth in three social levels from the construction of scenarios posed by model’s variables in the Colombian context. Finally, a comparative analysis of the results was performed using the statistical technique ANOVA. The results show that economies based in renewable resources generate higher levels of wealth in the long run
Downloads
References
DANE. (2012). Declaración –Comité de Expertos– Pobreza, pobreza extrema y desigualdad. Consultado el 31 de agosto en www.dane.gov.co/fi les/investigaciones/condiciones_vida/ pobreza/declaracion_expertos_pobreza_2012.pdf
Departamento Nacional de Planeación. (2010). Plan Nacional de Desarrollo 2010-2014. Capítulo III Crecimiento sostenible y competitividad. Consultado en febrero 15 2012 en http://www.dnp.
gov.co/PND/PND20102014.aspx
R. Axelrod, “Advancing the Art of Simulation in the Social Sciences. En Conte, R., Hegselmann, R. & Terna, P. (Eds.)”, Simulating Social Phenomena, Lecture Notes in Economics and Mathematical Systems, n°. 456, pp. 21-40, 1997a.
P. E. Johnson, “Simulation modeling in political science”, American Behavioral Scientist, n°. 10, pp. 1509-1530, 1999.
T. Kohler y G. J. Gumerman, Dynamics in human and primate societies: Agent-based modeling of social and spatial processes. New York: Oxford University Press & Santa Fe Institute, 2000.
B. Lebaron, “Agent Based Computational Finance: Suggested Readings and Early Research”,Journal of Economic Dynamics & Control, n°. 5-7, pp. 679-702, 2000.
L. Tesfatsion, “Agent-based computational economics: growing economies from the bottom up”,Artifi cial life, n°. 1, pp. 55-82, 2002.
Y. Mansury, M. Kimura, J. Lobo y T. S. Deisboeck, “Emerging Patterns in Tumor Systems: Simulating the Dynamics of Multicellular Clusters with an Agentbased Spatial Agglomeration Model”,
Journal of Theoretical Biology, n°. 3, pp. 343-370, 2002.
] Y. Mansury y T. S. Deisboeck, “Simulating the time series of a selected gene expression profi le in an agent-based tumor model”, Physica D: Nonlinear Phenomena, n°. 1-2, pp. 193-204, 2004.
R. Paton, R. Gregory, C. Vlachos, J. Saunders y H. Wu, “Evolvable social agents for bacterial systems modeling”, IEEE Transactions on Nanobioscience, n°. 3, pp. 208-216, 2004.
D. C. Walker, G. Hill, R. H. Smallwood y J. Southgate, “Agent-based computational modelling of wounded epithelial cell monolayers”, IEEE Transactions on Nanobioscience, n°. 3, pp. 153-163, 2004.
D. C. Walker, J. Southgate, G. Hill, M. Holcombe, D. R. Hose, S. Wood, S. Mac Neil, y R. H. Smallwood, “The epitheliome: agent-based modelling of the social behaviour of cells”, Biosystems, n°. 1-3, pp. 89-100, 2004b.
F. Bousquety y C. Le Page, “Multi-agent simulations and ecosystem management: A review”, Ecological Modelling, n°. 3-4, pp. 313-332, 2004.
A. López Paredes y C. Hernández Iglesias, Agent Based Modelling in Natural Resource Management. España: Insiso, 2008.
J. H. Holland, Emergence. From chaos to order. Addison-Wesley: Reading, 1998.
C. Sansores y J. Pavón, “Simulación Social basada en Agentes. Inteligencia Artifi cial”, RevistaIberoamericana de Inteligencia Artificial, n°. 25, pp. 71-78, 2005.
J. Izquierdo, J. Galán, J. Santos, y R. Del Olmo, “Modelado de Sistemas Complejos Mediante Simulación basada en Agentes y Mediante Dinámica de Sistema”, EMPIRIA. Revista de Metodología
de Ciencias Sociales, n°. 16, pp. 85-112, 2008.
N. Jennings, K. Sycara, M. Wooldridge. “A Roadmap of Agent Research and Development Autonomous Agents and Multi-Agent Systems”, n°. 1, pp. 7-38, 1998.
M. Wooldridge y N. Jennings, “Intelligent Agents: Theory and Practice”, Knowledge Engineering Review, n°. 2, pp. 115-152, 1995.
M. Luck, P. McBurney, & C. Preist, “Agent Technology: Enabling Next Generation computing. A Roadmap for Agent-Based Computing”, AgentLink, 2003.
S. Franklin y A. Graesser, Is it an agent, or just program? A Taxonomy for Autonomous Agents. En Müller, J., Wooldridge, M. & Jennings, N. Intelligent Agents III Proceedings of the third International Workshop on Agent Theories, Architectures, and Languages, Lecture Notes in Artificial Intelligence 1193: 21-36. Berlin, Germany: Springer-Verlag, 1997.
D. Romulus, An Agent-Based Computational Study of Wealth Distribution in Function of Resource Growth Interval Using Netlogo, 2008. Consultado en http://www.researchgate.net/publication/222199673_An_agent-based_computational_study_of_wealth_distribution_in_function_of_
resource_growth_interval_using_NetLogo
Departamento Nacional de Planeación. (2010). Plan Nacional de Desarrollo 2010-2014. Capítulo III Crecimiento sostenible y competitividad. Consultado en febrero 15 2012 en http://www.dnp.
gov.co/PND/PND20102014.aspx
R. Axelrod, “Advancing the Art of Simulation in the Social Sciences. En Conte, R., Hegselmann, R. & Terna, P. (Eds.)”, Simulating Social Phenomena, Lecture Notes in Economics and Mathematical Systems, n°. 456, pp. 21-40, 1997a.
P. E. Johnson, “Simulation modeling in political science”, American Behavioral Scientist, n°. 10, pp. 1509-1530, 1999.
T. Kohler y G. J. Gumerman, Dynamics in human and primate societies: Agent-based modeling of social and spatial processes. New York: Oxford University Press & Santa Fe Institute, 2000.
B. Lebaron, “Agent Based Computational Finance: Suggested Readings and Early Research”,Journal of Economic Dynamics & Control, n°. 5-7, pp. 679-702, 2000.
L. Tesfatsion, “Agent-based computational economics: growing economies from the bottom up”,Artifi cial life, n°. 1, pp. 55-82, 2002.
Y. Mansury, M. Kimura, J. Lobo y T. S. Deisboeck, “Emerging Patterns in Tumor Systems: Simulating the Dynamics of Multicellular Clusters with an Agentbased Spatial Agglomeration Model”,
Journal of Theoretical Biology, n°. 3, pp. 343-370, 2002.
] Y. Mansury y T. S. Deisboeck, “Simulating the time series of a selected gene expression profi le in an agent-based tumor model”, Physica D: Nonlinear Phenomena, n°. 1-2, pp. 193-204, 2004.
R. Paton, R. Gregory, C. Vlachos, J. Saunders y H. Wu, “Evolvable social agents for bacterial systems modeling”, IEEE Transactions on Nanobioscience, n°. 3, pp. 208-216, 2004.
D. C. Walker, G. Hill, R. H. Smallwood y J. Southgate, “Agent-based computational modelling of wounded epithelial cell monolayers”, IEEE Transactions on Nanobioscience, n°. 3, pp. 153-163, 2004.
D. C. Walker, J. Southgate, G. Hill, M. Holcombe, D. R. Hose, S. Wood, S. Mac Neil, y R. H. Smallwood, “The epitheliome: agent-based modelling of the social behaviour of cells”, Biosystems, n°. 1-3, pp. 89-100, 2004b.
F. Bousquety y C. Le Page, “Multi-agent simulations and ecosystem management: A review”, Ecological Modelling, n°. 3-4, pp. 313-332, 2004.
A. López Paredes y C. Hernández Iglesias, Agent Based Modelling in Natural Resource Management. España: Insiso, 2008.
J. H. Holland, Emergence. From chaos to order. Addison-Wesley: Reading, 1998.
C. Sansores y J. Pavón, “Simulación Social basada en Agentes. Inteligencia Artifi cial”, RevistaIberoamericana de Inteligencia Artificial, n°. 25, pp. 71-78, 2005.
J. Izquierdo, J. Galán, J. Santos, y R. Del Olmo, “Modelado de Sistemas Complejos Mediante Simulación basada en Agentes y Mediante Dinámica de Sistema”, EMPIRIA. Revista de Metodología
de Ciencias Sociales, n°. 16, pp. 85-112, 2008.
N. Jennings, K. Sycara, M. Wooldridge. “A Roadmap of Agent Research and Development Autonomous Agents and Multi-Agent Systems”, n°. 1, pp. 7-38, 1998.
M. Wooldridge y N. Jennings, “Intelligent Agents: Theory and Practice”, Knowledge Engineering Review, n°. 2, pp. 115-152, 1995.
M. Luck, P. McBurney, & C. Preist, “Agent Technology: Enabling Next Generation computing. A Roadmap for Agent-Based Computing”, AgentLink, 2003.
S. Franklin y A. Graesser, Is it an agent, or just program? A Taxonomy for Autonomous Agents. En Müller, J., Wooldridge, M. & Jennings, N. Intelligent Agents III Proceedings of the third International Workshop on Agent Theories, Architectures, and Languages, Lecture Notes in Artificial Intelligence 1193: 21-36. Berlin, Germany: Springer-Verlag, 1997.
D. Romulus, An Agent-Based Computational Study of Wealth Distribution in Function of Resource Growth Interval Using Netlogo, 2008. Consultado en http://www.researchgate.net/publication/222199673_An_agent-based_computational_study_of_wealth_distribution_in_function_of_
resource_growth_interval_using_NetLogo
Downloads
Published
2013-01-01
Issue
Section
Artículos
How to Cite
1.
de la Hoz Granadillo E, Fontalvo Herrera T, Vergara Schmalbach juan C. Analysis of Wealth Distribution Based on the Renewal Interval of Natural Resources Through Agent-Based Simulation. ingeniare [Internet]. 2013 Jan. 1 [cited 2025 Apr. 7];(14):31-42. Available from: https://revistas.unilibre.edu.co/index.php/ingeniare/article/view/610
