Evolución cultural en sociedades artificiales

Autores:: Sterpin Buitrago, Dante Giovanni

Tipo de recurso:: Article of journal

Fecha de publicación:: 2025

Institución:: Universidad de Cundinamarca

Repositorio:: Repositorio UdeC

Idioma:

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dc.title.spa.fl_str_mv	Evolución cultural en sociedades artificiales
title	Evolución cultural en sociedades artificiales
spellingShingle	Evolución cultural en sociedades artificiales Evolución Cultural Genes Memes Memética Modelos Computacionales Sociedades Artificiales Artificial Societies Computational Models Cultural Evolution Genes Memes Memetics
title_short	Evolución cultural en sociedades artificiales
title_full	Evolución cultural en sociedades artificiales
title_fullStr	Evolución cultural en sociedades artificiales
title_full_unstemmed	Evolución cultural en sociedades artificiales
title_sort	Evolución cultural en sociedades artificiales
dc.creator.fl_str_mv	Sterpin Buitrago, Dante Giovanni
dc.contributor.author.spa.fl_str_mv	Sterpin Buitrago, Dante Giovanni
dc.subject.none.fl_str_mv	Evolución Cultural Genes Memes Memética Modelos Computacionales Sociedades Artificiales Artificial Societies Computational Models Cultural Evolution Genes Memes Memetics
topic	Evolución Cultural Genes Memes Memética Modelos Computacionales Sociedades Artificiales Artificial Societies Computational Models Cultural Evolution Genes Memes Memetics
publishDate	2025
dc.date.issued.none.fl_str_mv	%0-%08-%04
dc.date.accessioned.none.fl_str_mv	2018-08-04 00:00:00 2025-11-05T14:58:07Z
dc.date.available.none.fl_str_mv	2018-08-04 00:00:00
dc.type.spa.fl_str_mv	Artículo de revista
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dc.identifier.doi.none.fl_str_mv	10.52143/2346139X.610
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dc.relation.citationedition.spa.fl_str_mv	Núm. 12 , Año 2018 : Revista Hashtag 2018A
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dc.relation.citationissue.spa.fl_str_mv	12
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dc.relation.references.none.fl_str_mv	Acerbi, A. y Marocco, D. (Junio del 2009). Orienting learning by exploiting sociality: An evolutio¬nary robotics simulation. Conferencia presentada en 2009 International Joint Conference on Neural Networks, Atlanta, Estados Unidos, 20-27. doi: https://doi.org/10.1109/ IJCNN.2009.5178607 Aunger, R. (2002). The Electric Meme: A New Theory of How We Think. Nueva York: Free Press. Blackmore, S. (1999). The Meme Machine. Oxford: Oxford University Press. Bongard, J. (2013). Evolutionary robotics. Communications of the acm, 56(8), 74-83. Borenstein, E. y Ruppin E. (2004). Envolving imitating agents and the emergence of a neural mi¬rror system. En M. Bedau, P. Husbands, T. Ikegami, J. Pollack y R. Watson (eds.), Artificial life ix. Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems (pp. 146-151). Cambridge, Estados Unidos: The mit press. Brodie, R. (2009). Virus of the Mind: The New Science of the Meme. Nueva York: Hay House. Burke, E., Gendreau, M., Hyde, M., Kendall, G., Ochoa, G., Özcan, E. y Qu, R. (2013). Hyper-heu¬ristics: a survey of the state of the art. Journal of the Operational Research Society, 64(12), 1695- 1724. doi: https://doi.org/10.1057/jors.2013.71 Chen, X., Ong, Y., Lim, M. y Tan, K. (2011). A multi-facet survey on memetic computation. IEEE Transactions on evolutionary computation, 15(5), 591-607. doi: https://doi.org/10.1109/ TEVC.2011.2132725 Cowling, P., Kendall, G. y Soubeiga, E. (2001). A Hyperheuristic Approach to Scheduling a Sa¬les Summit. En E. Burke y W. Erben (eds.), Practice and Theory of Automated Timetabling iii. patat 2000. Lecture Notes in Computer Science (vol. 2079) (pp. 176-190), Konstanz, Germany: Springer. Curran, D. y O’Riordan, C. (2007). The effects of cultural learning in populations of neural networks. Artificial Life, 13(1), 45-67. doi: https://doi.org/10.1162/artl.2007.13.1.45 Dawkins, R. (1976). The selfish gene. Oxford: Oxford University Press. Dawkins, R. (1983). Universal Darwinism. En D. Bendall (ed.), Evolution from Molecules to Man (pp. 403-425). Nueva York: Cambridge University Press. Dawkins, R. (1986). The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe Without Design. Nueva York y Londres: WW Norton & Company. Dawkins, R. (1993). Viruses of the mind. En B. Dahlbom (ed.), Dennett and His Critics: Demystifying Mind (pp. 13-27). Oxford: Blackwell. Dennett, D. (2006). Breaking the Spell: Religion as a Natural Phenomenon. Estados Unidos Penguin Books. Doncieux, S., Bredeche, N., Mouret, J-B. y Eiben A. (2015). Evolutionary robotics: what, why,and where to. Frontiers in Robotics and ai, 2(4), 1-18. doi: https://doi.org/10.3389/frobt.2015.00004 Espingardeiro, A. (2014). A roboethics framework for the development and introduction of social assistive robots in elderly care (tesis de doctorado). Universidad de Salford, Manchester. Recuperado de https://bit.ly/2toFxNQ Feng, L., Ong, Y., Tan, A. y Chen, X. (Junio del 2011). Towards human-like social multi agents with memetic automaton. Conferencia presentada en Congress of Evolutionary Computation (cec), Nueva Orleans, Estados Unidos, 1092-1099. doi: https://doi.org/10.1109/ CEC.2011.5949739 Ferber, J. (1999). Multi-Agent System: An Introduction to Distributed Artificial Intelligence. Boston: Addison-Wesley Longman Publishing Co. Floreano, D., Husbands, P. y Nolfi, S. (2008). Evolutionary robotics. En B. Siciliano y O. Khatib(eds.), Springer handbook of robotics (pp. 1423-1451). Berlin: Springer. Goldberg, D. (1989). Genetic algorithms in search, optimization, and machine learning. Boston: Addison-Wesley Longman Publishing Co. Gong, T. (2010). Exploring the roles of horizontal, vertical, and oblique transmissions in language evolution. Adaptive Behavior, 18(3-4), 356-376. González, S. (2004). ¿Sociedades artificiales? Una introducción a la simulación social. Revista Internacional de Sociología, 62(39), 199-222. Recuperado de https://bit.ly/2PpCa1y Hart, W., Krasnogor, N. y Smith, J. (2005). Memetic evolutionary algorithms. En W. Hart, N. Krasnogor y J. Smith. (eds.), Recent Advances in Memetic Algorithms (pp. 3-27). Berlin; Heidelberg; New York: Springer. Hauser, M. (2006). Moral Minds: How Nature Designed our Universal Sense of Right and Wrong.Nueva York: Harper Collins. Heinerman, J., Rango, M. y Eiben, A. (Diciembre del 2015). Evolution, individual learning, and social learning in a swarm of real robots. Conferencia presentada en 2015 ieee Symposium Series on Computational Intelligence, Cape Town, Sur Africa, 1055-1062. doi: https://doi.org/10.1109/SSCI.2015.152 Holland, J. (1975). Adaptation in Natural and Artificial Systems. An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Míchigan: University of Michigan Press. Huy, N., Soon, O., Hiot, L. y Krasnogor, N. (2009). Adaptive cellular memetic algorithms. Evolutionary Computation, 17(2), 231-256. doi: https://doi.org/10.1162/evco.2009.17.2.231 Kendall, G., Cowling, P. y Soubeiga, E. (2002). Choice function and random hyperheuristics. Conferencia presentada en 4th Asia-Pacific Conference on Simulated Evolution and Learning, Singapore, 667-671. Recuperado de https://bit.ly/2PSE9dU Krasnogor, N., Aragón, A. y Pacheco, J. (2006). Memetic algorithms. En E. Alba y R. Martí (eds.), Metaheuristic Procedures for Training Neutral Networks (pp. 225-248). Boston: Springer. doi:https://doi.org/10.1007/0-387-33416-5 Krasnogor, N. y Gustafson, S. (2002). Toward truly “memetic” memetic algorithms: Discussion and proofs of concept. En D. Corne, G. Fogel, W. Hart, J. Knowles, N. Krasnogor, R. Roy, J. Smith y A. Tiwari (eds.), Advances in Nature-Inspired Computation: The ppsn vii Workshops, (pp. 9-10). Reading: pedal; University of Reading. Krasnogor, N. y Gustafson, S. (2004). A study on the use of “self-generation” in memetic algorithms. Natural Computing, 3(1), 53-76. doi: https://doi.org/10.1023/B:NACO.0000023419.83147.67 Krasnogor, N. y Smith, J. (2005). A tutorial for competent memetic algorithms: models, taxonomy and design issues. ieee Trans Evol Comput, 9, 474-488. Lamma, E., Riguzzi, F. y Pereira, L. (2003). Belief revision via lamarckian evolution. New Generation Computing, 21(3), 247-275. DOI: https://doi.org/10.1007/BF03037475 Le, M., Neri, F. y Ong, Y. (2015). Memetic algorithms. En H. Ishibuchi (ed.), Encyclopedia of Life Support Systems: Computational Intelligence (vol. 2), (pp. 57-86). Singapur: Unesco; Eolss Publishers. Le, M., Ong, Y., Jin, Y. y Sendhoff, B. (2009). Lamarckian memetic algorithms: Local optimum and connectivity structure analysis. Memetic Computing, 1(3), 175-190. doi: https://doi.org/10.1007/s12293-009-0016-9 Lewontin, R. (1970). The Units of Selection. Annual Review of Ecology and Systematics, 1, 1-18. Maldonado, C. y Gómez, N. (2010). Modelamiento y simulación de sistemas complejos. Bogotá: Editorial Universidad del Rosario. Recuperado de https://bit.ly/36JK4sD Meuth, R., Lim, M., Ong, Y. y Wunsch, D. (2009). A proposition on memes and meta-memes incomputing for higher-order learning. Memetic Computing, 1(2), 85-100. Moscato, P. (1989). On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms. Pasadena, Estados Unidos: Caltech. Recuperado de https://bit.ly/38K6hsb Nedjah, N., Coelho, L. y Mourelle, L. (Eds.). (2007). Mobile robots: The evolutionary approach - Studies in Computational Intelligence (vol. 50). Berlin: Springer. Nguyen, Q., Ong, Y. y Lim, M. (Julio del 2008). Non-genetic transmission of memes by diffusion. Conferencia presentada en 10th annual conference on Genetic and evolutionary computation, Atlanta, Estados Unidos, 1017-1024. doi: http://doi.acm.org/10.1145/1389095.1389285 Pam, N. (13 de abril del 2013). Sociality [recurso en línea]. Recuperado de https://bit.ly/34vpt9Q Pan, Z., Feng, L., Ong, Y., Kang, Y., Tan, A. y Miao, C. (Septiembre del 2010). Meme selection, variation, and transmission in multi-agent system. Conferencia presentada en World Automation Congress, Kobe, Japón, 1-6. Recuperado de https://bit.ly/2rXpo1j Radetic, E., Pelikan, M. y Goldberg, D. (Julio del 2009). Effects of a deterministic hill climber on hBOA. Conferencia presentada en 11th Annual conference on Genetic and evolutionary computation, Montreal, Canadá, 437-444. doi: http://doi.acm.org/10.1145/1830483.1830543 Randsley de Moura, G. y Abrams, D. (2013). Bribery, Blackmail, and the Double Standard for Leader Transgressions. Group Dynamics: Theory, Research, and Practice, 17(1), 43-52. doi: https://doi.org/10.1037/a0031287 Reynolds, R. (1994). An introduction to cultural algorithms. En A. Sebald y L. Fogel (eds.), Proceedings of the third annual conference on evolutionary programming (pp. 131-139). River Edge, Estados Unidos: World Scientific Programming. Reynolds, R. y Peng, B. (2005). Cultural algorithms: computational modeling of how cultures learn to solve problems: an engineering example. Cybernetics and Systems: An International Journal, 36(8), 753-771. doi: https://doi.org/10.1080/01969720500306147 Sawyer, R. (2003). Artificial Societies: Multiagent Systems and the Micro-Macro Link in Sociological Theory. Sociological Methods & research, 31(3), 325-363. doi: https://doi.org/10.1177/0049124102239079 Smith, J. (Diciembre de 2003). Co-evolving memetic algorithms: A learning approach to robust scalableoptimisation. Conferencia presentada en The 2003 Congress on Evolutionary Computation, cec ‹03, Canberra, Australia, 498-505. doi: https://doi.org/10.1109/CEC.2003.1299617 Squazzoni, F., Jager, W. y Edmonds, B. (2014). Social Simulation in the Social Sciences: A Brief Overview. Social Science Computer Review, 32(3), 279-294. doi: https://doi.org/10.1177/0894439313512975 Sutton, R. y Barto, A. (1998). Reinforcement learning: An introduction. Cambridge, Estados Unidos: mit Press. Talbi, E. (2009). Metaheuristics: from design to implementation. Nueva Jersey: John Wiley & Sons. Tan, A., Lu, N. y Xiao, D. (2008). Integrating temporal difference methods and self-organizing neural networks for reinforcement learning with delayed evaluative feedback. ieee Transactions on Neural Networks, 19(2), 230-244. doi: https://doi.org/10.1109/TNN.2007.905839 Ullah, A., Sarker, R., Comfort, D. y Lokan, C. (Septiembre del 2007). An agent-based memetic algorithm (ama) for solving constrained optimization problems. Conferencia presentada en 2007 ieee Congress on Evolutionary Computation, Singapur, Singapur, 999-1006. doi: https://doi.org/10.1109/CEC.2007.4424579 Veruggio, G., Solis, J. y Van der Loos, M. (2011). Roboethics: Ethics Applied to Robotics. ieee Robotics & Automation Magazine, 18(1), 21-22. doi: 10.1109/MRA.2010.940149 Wooldridge, M. (2009). An introduction to multiagent systems. Glasgow: John Wiley & Sons. Zaikman, Y. y Marks, M. (2014). Ambivalent Sexism and the Sexual Double Standard. Sex Roles, 71(9-10), 333-344.
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spelling	Sterpin Buitrago, Dante Giovanni2018-08-04 00:00:002025-11-05T14:58:07Z2018-08-04 00:00:00%0-%08-%04https://repositorio.cun.edu.co/handle/cun/1081310.52143/2346139X.6102346-139Xhttps://doi.org/10.52143/2346139X.610application/pdfFondo Editorial CUNhttps://creativecommons.org/licenses/by-nc-nd/4.0/ - 2018https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.http://purl.org/coar/access_right/c_abf2https://revistas.cun.edu.co/index.php/hashtag/article/view/610Evolución CulturalGenesMemesMeméticaModelos ComputacionalesSociedades ArtificialesArtificial SocietiesComputational ModelsCultural EvolutionGenesMemesMemeticsEvolución cultural en sociedades artificialesArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Textinfo:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionhttps://revistas.cun.edu.co/index.php/hashtag/article/download/610/449Núm. 12 , Año 2018 : Revista Hashtag 2018A451231#ashtagAcerbi, A. y Marocco, D. (Junio del 2009). Orienting learning by exploiting sociality: An evolutio¬nary robotics simulation. Conferencia presentada en 2009 International Joint Conference on Neural Networks, Atlanta, Estados Unidos, 20-27. doi: https://doi.org/10.1109/ IJCNN.2009.5178607Aunger, R. (2002). The Electric Meme: A New Theory of How We Think. Nueva York: Free Press.Blackmore, S. (1999). The Meme Machine. Oxford: Oxford University Press.Bongard, J. (2013). Evolutionary robotics. Communications of the acm, 56(8), 74-83.Borenstein, E. y Ruppin E. (2004). Envolving imitating agents and the emergence of a neural mi¬rror system. En M. Bedau, P. Husbands, T. Ikegami, J. Pollack y R. Watson (eds.), Artificial life ix. Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems (pp. 146-151). Cambridge, Estados Unidos: The mit press.Brodie, R. (2009). Virus of the Mind: The New Science of the Meme. Nueva York: Hay House.Burke, E., Gendreau, M., Hyde, M., Kendall, G., Ochoa, G., Özcan, E. y Qu, R. (2013). Hyper-heu¬ristics: a survey of the state of the art. Journal of the Operational Research Society, 64(12), 1695- 1724. doi: https://doi.org/10.1057/jors.2013.71Chen, X., Ong, Y., Lim, M. y Tan, K. (2011). A multi-facet survey on memetic computation. IEEE Transactions on evolutionary computation, 15(5), 591-607. doi: https://doi.org/10.1109/ TEVC.2011.2132725Cowling, P., Kendall, G. y Soubeiga, E. (2001). A Hyperheuristic Approach to Scheduling a Sa¬les Summit. En E. Burke y W. Erben (eds.), Practice and Theory of Automated Timetabling iii. patat 2000. Lecture Notes in Computer Science (vol. 2079) (pp. 176-190), Konstanz, Germany: Springer.Curran, D. y O’Riordan, C. (2007). The effects of cultural learning in populations of neural networks. Artificial Life, 13(1), 45-67. doi: https://doi.org/10.1162/artl.2007.13.1.45Dawkins, R. (1976). The selfish gene. Oxford: Oxford University Press.Dawkins, R. (1983). Universal Darwinism. En D. Bendall (ed.), Evolution from Molecules to Man (pp. 403-425). Nueva York: Cambridge University Press.Dawkins, R. (1986). The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe Without Design. Nueva York y Londres: WW Norton & Company.Dawkins, R. (1993). Viruses of the mind. En B. Dahlbom (ed.), Dennett and His Critics: Demystifying Mind (pp. 13-27). Oxford: Blackwell.Dennett, D. (2006). Breaking the Spell: Religion as a Natural Phenomenon. Estados Unidos Penguin Books.Doncieux, S., Bredeche, N., Mouret, J-B. y Eiben A. (2015). Evolutionary robotics: what, why,and where to. Frontiers in Robotics and ai, 2(4), 1-18. doi: https://doi.org/10.3389/frobt.2015.00004Espingardeiro, A. (2014). A roboethics framework for the development and introduction of social assistive robots in elderly care (tesis de doctorado). Universidad de Salford, Manchester. Recuperado de https://bit.ly/2toFxNQFeng, L., Ong, Y., Tan, A. y Chen, X. (Junio del 2011). Towards human-like social multi agents with memetic automaton. Conferencia presentada en Congress of Evolutionary Computation (cec), Nueva Orleans, Estados Unidos, 1092-1099. doi: https://doi.org/10.1109/ CEC.2011.5949739Ferber, J. (1999). Multi-Agent System: An Introduction to Distributed Artificial Intelligence. Boston: Addison-Wesley Longman Publishing Co.Floreano, D., Husbands, P. y Nolfi, S. (2008). Evolutionary robotics. En B. Siciliano y O. Khatib(eds.), Springer handbook of robotics (pp. 1423-1451). Berlin: Springer.Goldberg, D. (1989). Genetic algorithms in search, optimization, and machine learning. Boston: Addison-Wesley Longman Publishing Co. Gong, T. (2010). Exploring the roles of horizontal, vertical, and oblique transmissions in language evolution. Adaptive Behavior, 18(3-4), 356-376.González, S. (2004). ¿Sociedades artificiales? Una introducción a la simulación social. Revista Internacional de Sociología, 62(39), 199-222. Recuperado de https://bit.ly/2PpCa1yHart, W., Krasnogor, N. y Smith, J. (2005). Memetic evolutionary algorithms. En W. Hart, N. Krasnogor y J. Smith. (eds.), Recent Advances in Memetic Algorithms (pp. 3-27). Berlin; Heidelberg; New York: Springer.Hauser, M. (2006). Moral Minds: How Nature Designed our Universal Sense of Right and Wrong.Nueva York: Harper Collins.Heinerman, J., Rango, M. y Eiben, A. (Diciembre del 2015). Evolution, individual learning, and social learning in a swarm of real robots. Conferencia presentada en 2015 ieee Symposium Series on Computational Intelligence, Cape Town, Sur Africa, 1055-1062. doi: https://doi.org/10.1109/SSCI.2015.152Holland, J. (1975). Adaptation in Natural and Artificial Systems. An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Míchigan: University of Michigan Press.Huy, N., Soon, O., Hiot, L. y Krasnogor, N. (2009). Adaptive cellular memetic algorithms. Evolutionary Computation, 17(2), 231-256. doi: https://doi.org/10.1162/evco.2009.17.2.231Kendall, G., Cowling, P. y Soubeiga, E. (2002). Choice function and random hyperheuristics. Conferencia presentada en 4th Asia-Pacific Conference on Simulated Evolution and Learning, Singapore, 667-671. Recuperado de https://bit.ly/2PSE9dUKrasnogor, N., Aragón, A. y Pacheco, J. (2006). Memetic algorithms. En E. Alba y R. Martí (eds.), Metaheuristic Procedures for Training Neutral Networks (pp. 225-248). Boston: Springer. doi:https://doi.org/10.1007/0-387-33416-5Krasnogor, N. y Gustafson, S. (2002). Toward truly “memetic” memetic algorithms: Discussion and proofs of concept. En D. Corne, G. Fogel, W. Hart, J. Knowles, N. Krasnogor, R. Roy, J. Smith y A. Tiwari (eds.), Advances in Nature-Inspired Computation: The ppsn vii Workshops, (pp. 9-10). Reading: pedal; University of Reading.Krasnogor, N. y Gustafson, S. (2004). A study on the use of “self-generation” in memetic algorithms. Natural Computing, 3(1), 53-76. doi: https://doi.org/10.1023/B:NACO.0000023419.83147.67Krasnogor, N. y Smith, J. (2005). A tutorial for competent memetic algorithms: models, taxonomy and design issues. ieee Trans Evol Comput, 9, 474-488.Lamma, E., Riguzzi, F. y Pereira, L. (2003). Belief revision via lamarckian evolution. New Generation Computing, 21(3), 247-275. DOI: https://doi.org/10.1007/BF03037475Le, M., Neri, F. y Ong, Y. (2015). Memetic algorithms. En H. Ishibuchi (ed.), Encyclopedia of Life Support Systems: Computational Intelligence (vol. 2), (pp. 57-86). Singapur: Unesco; Eolss Publishers.Le, M., Ong, Y., Jin, Y. y Sendhoff, B. (2009). Lamarckian memetic algorithms: Local optimum and connectivity structure analysis. Memetic Computing, 1(3), 175-190. doi: https://doi.org/10.1007/s12293-009-0016-9Lewontin, R. (1970). The Units of Selection. Annual Review of Ecology and Systematics, 1, 1-18.Maldonado, C. y Gómez, N. (2010). Modelamiento y simulación de sistemas complejos. Bogotá: Editorial Universidad del Rosario. Recuperado de https://bit.ly/36JK4sDMeuth, R., Lim, M., Ong, Y. y Wunsch, D. (2009). A proposition on memes and meta-memes incomputing for higher-order learning. Memetic Computing, 1(2), 85-100.Moscato, P. (1989). On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms. Pasadena, Estados Unidos: Caltech. Recuperado de https://bit.ly/38K6hsbNedjah, N., Coelho, L. y Mourelle, L. (Eds.). (2007). Mobile robots: The evolutionary approach - Studies in Computational Intelligence (vol. 50). Berlin: Springer.Nguyen, Q., Ong, Y. y Lim, M. (Julio del 2008). Non-genetic transmission of memes by diffusion. Conferencia presentada en 10th annual conference on Genetic and evolutionary computation, Atlanta, Estados Unidos, 1017-1024. doi: http://doi.acm.org/10.1145/1389095.1389285Pam, N. (13 de abril del 2013). Sociality [recurso en línea]. 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Evolución cultural en sociedades artificiales

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