Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural

Las tecnologías de investigación social son un conjunto de aplicaciones y modelos formales que posibilitan el abordaje de problemas sociales mediante métodos cuantitativos y cualitativos no necesariamente estadísticos, un gran campo iconológico de explicaciones visuales (Tufte, 1997), perspectivas t...

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Autores:
Luján Villar, Juan David
Tipo de recurso:
Article of journal
Fecha de publicación:
2018
Institución:
Universidad de Caldas
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Repositorio U. de Caldas
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spa
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oai:repositorio.ucaldas.edu.co:ucaldas/19198
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https://doi.org/10.17151/rasv.2018.20.1.4
Palabra clave:
sistemas complejos
modelado
simulación
sostenibilidad
complex systems
modeling
simulation
sustainability
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Revista de Antropología y Sociología: Virajes - 2018
id UCALDAS2_5593a5df3c3653267126c8dd7c939bb8
oai_identifier_str oai:repositorio.ucaldas.edu.co:ucaldas/19198
network_acronym_str UCALDAS2
network_name_str Repositorio U. de Caldas
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dc.title.spa.fl_str_mv Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural
dc.title.translated.eng.fl_str_mv Social sciences and sustainability: social research technologies applied to the urban and the rural
title Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural
spellingShingle Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural
sistemas complejos
modelado
simulación
sostenibilidad
complex systems
modeling
simulation
sustainability
title_short Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural
title_full Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural
title_fullStr Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural
title_full_unstemmed Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural
title_sort Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural
dc.creator.fl_str_mv Luján Villar, Juan David
dc.contributor.author.spa.fl_str_mv Luján Villar, Juan David
dc.subject.spa.fl_str_mv sistemas complejos
modelado
simulación
sostenibilidad
topic sistemas complejos
modelado
simulación
sostenibilidad
complex systems
modeling
simulation
sustainability
dc.subject.eng.fl_str_mv complex systems
modeling
simulation
sustainability
description Las tecnologías de investigación social son un conjunto de aplicaciones y modelos formales que posibilitan el abordaje de problemas sociales mediante métodos cuantitativos y cualitativos no necesariamente estadísticos, un gran campo iconológico de explicaciones visuales (Tufte, 1997), perspectivas transdisciplinares de conocimiento y ambientes de trabajo formal libres de disciplina. Este conjunto de aplicaciones presentan diversos retos y alternativas a los modelos mecánicos, estadísticos e interpretativos en estado puro de las ciencias sociales clásicas. El punto de partida de este trabajo enfatiza en la búsqueda de la sostenibilidad ecosistémica en escenarios urbanos y rurales y su investigación interdisciplinar, a propósito del impacto de las metodologías complejas, sus premisas, aplicaciones de trabajo práctico y conceptualizaciones básicas.
publishDate 2018
dc.date.accessioned.none.fl_str_mv 2018-01-01 00:00:00
2023-04-30T15:03:45Z
dc.date.available.none.fl_str_mv 2018-01-01 00:00:00
2023-04-30T15:03:45Z
dc.date.issued.none.fl_str_mv 2018-01-01
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.local.eng.fl_str_mv Journal article
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.doi.none.fl_str_mv 10.17151/rasv.2018.20.1.4
dc.identifier.eissn.none.fl_str_mv 2462-9782
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dc.relation.citationvolume.spa.fl_str_mv 20
dc.relation.ispartofjournal.spa.fl_str_mv Revista de Antropología y Sociología : Virajes
dc.relation.references.spa.fl_str_mv Amorim, L.M.E., Barros, M.N.M. and Cruz, D. (2014). Urban texture and space configuration: An essay on integrating socio spatial analytical techniques. Cities, 39, 58-67.
Ariza-Villaverde, A.B., Jiménez-Hornero, F.J. and Ravé, E.G.D. (2013). Multifractal analysis of axial maps applied to the study of urban morphology. Comput Environ Urban Systems, 38, 1-10.
Atmar, W. and Patterson, B.D. (1993). The Measure of Order and Disorder in the Distribution of Species in Fragmented Habitat. Oecologa, 96, 373-382.
Batty, M. (2013). The New Science of Cities. Massachusetts, USA: The MIT Press.
Bascompte, J. and Jordana, P. (2006). The Structure of Plant-Animal M utualistic Networks. En M. Pascual and J.A. Dunne (Ed.), Ecological Networks: Linking Structure to Dynamics in Food Webs (pp. 143-159). New York, USA: Oxford University Press.
Booch, G., Rumbaugh, J. and Jacobson, I. (2005). The Unified Modeling Language User’s Guide. New York, USA: Addison-Wesley.
Borgatti, S. and Everett, M. (1999). Models of core/periphery structures. Social Networks, 21, 375-395.
Bousquet, F. and Le Page, C. (2004). Multi-agent simulations and ecosystem management: A review. Ecol Modell, 176, 313-332.
Brand, S. (2010). Whole Earth Discipline: Why Dense Cities, Nuclear Power, Transgenic Crops, Restored Wildlands, Radical Science, and Geoengineering are Necessary. New York, USA: Atlantic Books.
Cartozo, C.C., Garlaschelli, G. and Caldarelli, G. (2006). Graph Theory and Food Webs. En M. Pascual and J.A. Dunne (Ed.), Ecological Networks: Linking Structure to Dynamics in Food Webs (pp. 93-117). New York, USA: Oxford University Press.
Chen, S.H. and Yeh, C.H. (2002). On the Emergent Properties of Artificial Stock Markets: The Efficient Market Hypothesis and the Rational Expectations Hypothesis. Journal of Economic Behaviour and Organization, 49, 217-239.
Chen, Y. and Feng, J. (2012). Fractal-based exponential distribution of urban density and self-affine fractal forms of cities. Chaos, Solitons & Fractals, 45, 1404-1416.
Chen, Y. and Wang, J. (2013). Multifractal characterization of urban form and growth: The case of Beijing. Environment and Planning B: Urban Analytics and City Science, 40, 884-904.
de Vries, B. and Petersen, A. (2009). Conceptualizing sustainable development: An assessment methodology connecting values, knowledge, worldviews and scenarios. Ecological Economics, 68, 1006-1019.
Egerton, F.N. (2007). Understanding food chains and food webs, 1700-1970. Bulletin of the Ecological Society of America, 88, 50-69.
Feng, J. and Chen, Y. (2010). Spatiotemporal evolution of urban form and land use structure in Hangzhou, China: Evidence from fractals. Environment and Planning B: Urban Analytics and City Science, 37, 838-856.
Forrester, J. et al. (2014). Modeling Social-Ecological Problems in Coastal Ecosystems: A Case Study. Complexity, 19, 73-82.
Frankhauser, P. (2015). From Fractal Urban Pattern Analysis to Fractal Urban Planning Concepts. En M. Helbich, J.J. Arsanjani and M. Leitner (Ed.), Computational Approaches for Urban Environments (pp. 13-48). Geneva, Switzerland: Springer International Publishing.
Gilbert, N. and Troitzsch, K.G. (2005). Simulation for the Social Scientist. Buckingham, United Kingdom: Open University Press.
Gilbert, N., Ahrweiler, P. and Pyka, A. (2010). The SKIN (Simulating Knowledge Dynamics in Innovation Networks) model. Mainz, Germany: Johannes Gutenberg University Mainz, University of Hohenheim.
Gilbert, N., Ahrweiler, P. and Pyka, A. (Ed.). (2014). Simulating Knowledge Dynamics in Innovation Networks. Berlin, Germany: Springer-Verlag.
Harris, M. (1985). Good to Eat: Riddles of Food and Culture. New York, USA: Simon & Schuster.
Higgins, A.J. et al. (2010). Applying operations research to agricultural value chain to achieve a balance in efficiency and resilience. Journal of the Operations Research Society, 61, 964-973.
Holland, J. (1995). Hidden Order: How Adaptation Builds Complexity. Reading, England: Addison-Wesley.
ICSU. (2016). A Draft Framework for Understanding SDG Interactions. Recuperado de https://icsu.org/cms/2017/05/SDG-interactions-working-paper.pdf.
John, B.E., Vera, A.H. and Newell, A. (1994). Toward real-time GOMS: A model of expert behavior in a highly interactive task. Behavior and Information Technology, 13, 255-267.
Kim, J., Lerch, F. and Simon, H.A. (1995). Internal representation and rule development in object-oriented design. ACM Transactions on Computer-Human Interaction, 2 (4), 357-390.
Klüver, J. (1996). Simulations of Self Organizing Social Systems. En F. Faulbaum and W. Bandilla (Ed.), SoftStat 95. Advances in Statistical Software (pp. 425-432). Stuttgart, Germany: Lucius.
Lansing, J.S. (2006). Perfect Order: Recognizing Complexity in Bali. New Jersey, USA: Princeton University Press.
Lansing, J.S. et al. (2017). Adaptive self-organization of Bali’s ancient rice terraces. Proceedings of the National Academy of Sciences, 114 (25), 6504-6509.
LeBaron, B. (2002). Short Memory Traders and Their Impact on Group Learning in Financial Markets. Proceedings of the U.S. National Academy of Sciences, 99, 7201-7206.
LeBaron, B., Arthur, W.B. and Palmer, R. (1999). Time Series Properties of an Artificial Stock Market. Journal of Economic Dynamics and Control, 23, 1487-1516.
Moss, S. and Edmonds, B. (2005). Sociology and Simulation: Statistical and Qualitative Cross-Validation. AJS, 110 (4), 1095-1131.
Murcott, A. (Ed.). (1983). The Sociology of Food and Eating: Essays on the Sociological Significance of Food. Aldershot, England: Gower.
Newell, A. (1990). Unified Theories of Cognition. Cambridge, USA: Harvard University Press.
Nilsson, M., Griggs, D. and Visbeck, M. (2016). Map the interactions between Sustainable Development Goals. Nature, 534, 320-322.
Northrop, R.B. and Connor, A.N. (2013). Ecological Sustainability. Understanding Complex Issues. Boca Raton, USA: CRC Press, Taylor & Francis Group.
Pascual, M. and Dunne, J.A. (Ed.). (2006). Ecological Networks: Linking Structure to Dynamics in Food Webs. New York, USA: Oxford University Press.
Pierce, W.D., Cushman, R.A. and Hood, C.E. (1912). The insect enemies of the cotton boll weevil. U.S. Department of Agriculture, Bureau of Entomology Bulletin, 100, 1-99.
Poincaré, H. (1908). Science et Méthode. Paris, France: Flammarion.
Reeves, C.R. (1993). Using genetic algorithms with small populations. En S. Forrest (Ed.), Proceedings of the Fifth International Conference on Genetic Algorithms, University of Illinois at Urbana-Champaign (pp. 92-99). San Mateo, USA: Morgan Kaufmann.
Reynolds, G.R. (1994). An Introduction to Cultural Algorithms. Recuperado de http://ai.cs.wayne.edu/ai/availablePapersOnLine/IntroToCA.pdf.
Reynolds, R. and Kobti, Z. (2003). A Multi-Agent Simulation Using Cultural Algorithms: The Effect of Culture on the Resilience of Social Systems. Recuperado de http://ieeexplore.ieee.org/document/1299917/?reload=true.
Reynoso, C. (2006). Complejidad y caos: una exploración antropológica. Buenos Aires, Argentina: Editorial SB.
Reynoso, C. (2013). Etnicidad y redes territoriales: perspectivas de complejidad. En B. Nates (Coord.), La frontera, las fronteras: diálogos transversales en estudios territoriales contemporáneos (pp. 63-90). Riohacha, Colombia: RETEC.
Salingaros, N.A. (2005). Principles of Urban Structure. Amsterdam, Netherlands: Techne Press. Schelling, T. (1978). Micromotives and Macrobehavior. New York, USA: Norton.
Sibertin-Blanc, C. et al. (2013). SocLab: A Framework for the Modeling, Simulation and Analysis of Power in Social Organizations. Journal of Artificial Societies and Social Simulation, 16 (4). Recuperado de http://jasss.soc.surrey.ac.uk/16/4/8.html.
Suleiman, R., Troitzsch, K.G. and Gilbert, N. (Ed.). (2000). Tools and Techniques for Social Science Simulation. Heidelberg, Germany: Physica-Verlag.
Tufte, E.R. (1997). Visual Explanations. Images and Quantities, Evidence and Narrative. Cheshire/ Connecticut, USA: Graphics Press.
von Bertalanffy, L. (1976). Teoría general de los sistemas. Fundamentos, desarrollo, aplicaciones. Buenos Aires, Argentina: Fondo de Cultura Económica.
Wells, J. (2013). Complexity and Sustainability. New York, USA: Routledge.
Wilensky, U. and Rand, W. (2015). An Introduction to Agent-Based Modeling. Modeling Natural, Social, and Engineered Complex Systems with NetLogo. Cambridge, USA: The MIT Press.
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spelling Luján Villar, Juan Davida271a922db1e1475f3f0d29c77b83a255002018-01-01 00:00:002023-04-30T15:03:45Z2018-01-01 00:00:002023-04-30T15:03:45Z2018-01-010123-4471https://repositorio.ucaldas.edu.co/handle/ucaldas/1919810.17151/rasv.2018.20.1.42462-9782https://doi.org/10.17151/rasv.2018.20.1.4Las tecnologías de investigación social son un conjunto de aplicaciones y modelos formales que posibilitan el abordaje de problemas sociales mediante métodos cuantitativos y cualitativos no necesariamente estadísticos, un gran campo iconológico de explicaciones visuales (Tufte, 1997), perspectivas transdisciplinares de conocimiento y ambientes de trabajo formal libres de disciplina. Este conjunto de aplicaciones presentan diversos retos y alternativas a los modelos mecánicos, estadísticos e interpretativos en estado puro de las ciencias sociales clásicas. El punto de partida de este trabajo enfatiza en la búsqueda de la sostenibilidad ecosistémica en escenarios urbanos y rurales y su investigación interdisciplinar, a propósito del impacto de las metodologías complejas, sus premisas, aplicaciones de trabajo práctico y conceptualizaciones básicas.Social research technologies are a set of applications and formal models that allow the approach of social problems through quantitative and qualitative methods not necessarily statistical, a large iconological field of visual explanations (Tufte, 1997), transdisciplinary perspectives of knowledge and free from any discipline formal work environments. This set of applications presents different challenges and alternatives to the mechanical, statistical and interpretative models in the pure state of the classical social sciences. The starting point of this work emphasizes the search for ecosystem sustainability in urban and rural settings and its interdisciplinary research regarding the impact of complex methodologies, their premises, applications of practical work and basic conceptualizations.application/pdfspaUniversidad de CaldasRevista de Antropología y Sociología: Virajes - 2018https://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://revistasojs.ucaldas.edu.co/index.php/virajes/article/view/3176sistemas complejosmodeladosimulaciónsostenibilidadcomplex systemsmodelingsimulationsustainabilityCiencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo ruralSocial sciences and sustainability: social research technologies applied to the urban and the ruralArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a858116120Revista de Antropología y Sociología : VirajesAmorim, L.M.E., Barros, M.N.M. and Cruz, D. (2014). Urban texture and space configuration: An essay on integrating socio spatial analytical techniques. Cities, 39, 58-67.Ariza-Villaverde, A.B., Jiménez-Hornero, F.J. and Ravé, E.G.D. (2013). Multifractal analysis of axial maps applied to the study of urban morphology. Comput Environ Urban Systems, 38, 1-10.Atmar, W. and Patterson, B.D. (1993). The Measure of Order and Disorder in the Distribution of Species in Fragmented Habitat. Oecologa, 96, 373-382.Batty, M. (2013). The New Science of Cities. Massachusetts, USA: The MIT Press.Bascompte, J. and Jordana, P. (2006). The Structure of Plant-Animal M utualistic Networks. En M. Pascual and J.A. Dunne (Ed.), Ecological Networks: Linking Structure to Dynamics in Food Webs (pp. 143-159). New York, USA: Oxford University Press.Booch, G., Rumbaugh, J. and Jacobson, I. (2005). The Unified Modeling Language User’s Guide. New York, USA: Addison-Wesley.Borgatti, S. and Everett, M. (1999). Models of core/periphery structures. Social Networks, 21, 375-395.Bousquet, F. and Le Page, C. (2004). Multi-agent simulations and ecosystem management: A review. Ecol Modell, 176, 313-332.Brand, S. (2010). Whole Earth Discipline: Why Dense Cities, Nuclear Power, Transgenic Crops, Restored Wildlands, Radical Science, and Geoengineering are Necessary. New York, USA: Atlantic Books.Cartozo, C.C., Garlaschelli, G. and Caldarelli, G. (2006). Graph Theory and Food Webs. En M. Pascual and J.A. Dunne (Ed.), Ecological Networks: Linking Structure to Dynamics in Food Webs (pp. 93-117). New York, USA: Oxford University Press.Chen, S.H. and Yeh, C.H. (2002). On the Emergent Properties of Artificial Stock Markets: The Efficient Market Hypothesis and the Rational Expectations Hypothesis. Journal of Economic Behaviour and Organization, 49, 217-239.Chen, Y. and Feng, J. (2012). Fractal-based exponential distribution of urban density and self-affine fractal forms of cities. Chaos, Solitons & Fractals, 45, 1404-1416.Chen, Y. and Wang, J. (2013). Multifractal characterization of urban form and growth: The case of Beijing. Environment and Planning B: Urban Analytics and City Science, 40, 884-904.de Vries, B. and Petersen, A. (2009). Conceptualizing sustainable development: An assessment methodology connecting values, knowledge, worldviews and scenarios. Ecological Economics, 68, 1006-1019.Egerton, F.N. (2007). Understanding food chains and food webs, 1700-1970. Bulletin of the Ecological Society of America, 88, 50-69.Feng, J. and Chen, Y. (2010). Spatiotemporal evolution of urban form and land use structure in Hangzhou, China: Evidence from fractals. Environment and Planning B: Urban Analytics and City Science, 37, 838-856.Forrester, J. et al. (2014). Modeling Social-Ecological Problems in Coastal Ecosystems: A Case Study. Complexity, 19, 73-82.Frankhauser, P. (2015). From Fractal Urban Pattern Analysis to Fractal Urban Planning Concepts. En M. Helbich, J.J. Arsanjani and M. Leitner (Ed.), Computational Approaches for Urban Environments (pp. 13-48). Geneva, Switzerland: Springer International Publishing.Gilbert, N. and Troitzsch, K.G. (2005). Simulation for the Social Scientist. Buckingham, United Kingdom: Open University Press.Gilbert, N., Ahrweiler, P. and Pyka, A. (2010). The SKIN (Simulating Knowledge Dynamics in Innovation Networks) model. Mainz, Germany: Johannes Gutenberg University Mainz, University of Hohenheim.Gilbert, N., Ahrweiler, P. and Pyka, A. (Ed.). (2014). Simulating Knowledge Dynamics in Innovation Networks. Berlin, Germany: Springer-Verlag.Harris, M. (1985). Good to Eat: Riddles of Food and Culture. New York, USA: Simon & Schuster.Higgins, A.J. et al. (2010). Applying operations research to agricultural value chain to achieve a balance in efficiency and resilience. Journal of the Operations Research Society, 61, 964-973.Holland, J. (1995). Hidden Order: How Adaptation Builds Complexity. Reading, England: Addison-Wesley.ICSU. (2016). A Draft Framework for Understanding SDG Interactions. Recuperado de https://icsu.org/cms/2017/05/SDG-interactions-working-paper.pdf.John, B.E., Vera, A.H. and Newell, A. (1994). Toward real-time GOMS: A model of expert behavior in a highly interactive task. Behavior and Information Technology, 13, 255-267.Kim, J., Lerch, F. and Simon, H.A. (1995). Internal representation and rule development in object-oriented design. ACM Transactions on Computer-Human Interaction, 2 (4), 357-390.Klüver, J. (1996). Simulations of Self Organizing Social Systems. En F. Faulbaum and W. Bandilla (Ed.), SoftStat 95. Advances in Statistical Software (pp. 425-432). Stuttgart, Germany: Lucius.Lansing, J.S. (2006). Perfect Order: Recognizing Complexity in Bali. New Jersey, USA: Princeton University Press.Lansing, J.S. et al. (2017). Adaptive self-organization of Bali’s ancient rice terraces. Proceedings of the National Academy of Sciences, 114 (25), 6504-6509.LeBaron, B. (2002). Short Memory Traders and Their Impact on Group Learning in Financial Markets. Proceedings of the U.S. National Academy of Sciences, 99, 7201-7206.LeBaron, B., Arthur, W.B. and Palmer, R. (1999). Time Series Properties of an Artificial Stock Market. Journal of Economic Dynamics and Control, 23, 1487-1516.Moss, S. and Edmonds, B. (2005). Sociology and Simulation: Statistical and Qualitative Cross-Validation. AJS, 110 (4), 1095-1131.Murcott, A. (Ed.). (1983). The Sociology of Food and Eating: Essays on the Sociological Significance of Food. Aldershot, England: Gower.Newell, A. (1990). Unified Theories of Cognition. Cambridge, USA: Harvard University Press.Nilsson, M., Griggs, D. and Visbeck, M. (2016). Map the interactions between Sustainable Development Goals. Nature, 534, 320-322.Northrop, R.B. and Connor, A.N. (2013). Ecological Sustainability. Understanding Complex Issues. Boca Raton, USA: CRC Press, Taylor & Francis Group.Pascual, M. and Dunne, J.A. (Ed.). (2006). Ecological Networks: Linking Structure to Dynamics in Food Webs. New York, USA: Oxford University Press.Pierce, W.D., Cushman, R.A. and Hood, C.E. (1912). The insect enemies of the cotton boll weevil. U.S. Department of Agriculture, Bureau of Entomology Bulletin, 100, 1-99.Poincaré, H. (1908). Science et Méthode. Paris, France: Flammarion.Reeves, C.R. (1993). Using genetic algorithms with small populations. En S. Forrest (Ed.), Proceedings of the Fifth International Conference on Genetic Algorithms, University of Illinois at Urbana-Champaign (pp. 92-99). San Mateo, USA: Morgan Kaufmann.Reynolds, G.R. (1994). An Introduction to Cultural Algorithms. Recuperado de http://ai.cs.wayne.edu/ai/availablePapersOnLine/IntroToCA.pdf.Reynolds, R. and Kobti, Z. (2003). A Multi-Agent Simulation Using Cultural Algorithms: The Effect of Culture on the Resilience of Social Systems. Recuperado de http://ieeexplore.ieee.org/document/1299917/?reload=true.Reynoso, C. (2006). Complejidad y caos: una exploración antropológica. Buenos Aires, Argentina: Editorial SB.Reynoso, C. (2013). Etnicidad y redes territoriales: perspectivas de complejidad. En B. Nates (Coord.), La frontera, las fronteras: diálogos transversales en estudios territoriales contemporáneos (pp. 63-90). Riohacha, Colombia: RETEC.Salingaros, N.A. (2005). Principles of Urban Structure. Amsterdam, Netherlands: Techne Press. Schelling, T. (1978). Micromotives and Macrobehavior. New York, USA: Norton.Sibertin-Blanc, C. et al. (2013). SocLab: A Framework for the Modeling, Simulation and Analysis of Power in Social Organizations. Journal of Artificial Societies and Social Simulation, 16 (4). Recuperado de http://jasss.soc.surrey.ac.uk/16/4/8.html.Suleiman, R., Troitzsch, K.G. and Gilbert, N. (Ed.). (2000). Tools and Techniques for Social Science Simulation. Heidelberg, Germany: Physica-Verlag.Tufte, E.R. (1997). Visual Explanations. Images and Quantities, Evidence and Narrative. 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