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Modelado Basado en Agentes: un Enfoque desde la Ingeniería de Sistemas

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Modelado Basado en Agentes: un Enfoque desde la Ingeniería de Sistemas

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Pereda, M.; Zamarreño, JM. (2015). Modelado Basado en Agentes: un Enfoque desde la Ingeniería de Sistemas. Revista Iberoamericana de Automática e Informática industrial. 12(3):304-312. https://doi.org/10.1016/j.riai.2015.02.007

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Título: Modelado Basado en Agentes: un Enfoque desde la Ingeniería de Sistemas
Otro titulo: Agent-Based Modelling: an Approach from the Systems Engineering.
Autor: Pereda, María Zamarreño, Jesús M.
Fecha difusión:
Resumen:
[ES] El modelado basado en agentes (ABM, Agent Based Modeling) es una técnica de modelado que está siendo explotada con gran éxito en áreas como la ecología, ciencias sociales, economía, etc. Sin embargo, su uso como técnica ...[+]


[EN] Agent-Based Modelling (ABM) is a modelling technique with great success in fields like ecology, social sciences, economy, etc. However, it is not so widespread in the Automatic field. In this paper, we present how to ...[+]
Palabras clave: Agents , Dynamic modelling , Systems engineering , State space , Conceptual representations , Agentes , Modelado dinámico , Ingeniería de sistemas , Espacio de estados , Representaciones conceptuales
Derechos de uso: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Fuente:
Revista Iberoamericana de Automática e Informática industrial. (issn: 1697-7912 ) (eissn: 1697-7920 )
DOI: 10.1016/j.riai.2015.02.007
Editorial:
Universitat Politècnica de València
Versión del editor: https://doi.org/10.1016/j.riai.2015.02.007
Código del Proyecto:
info:eu-repo/grantAgreement/MINECO//DPI2012-39381-C02-02/ES/METODOLOGIA DE DISEÑO DE ESTRATEGIAS DE CONTROL JERARQUICO Y DISTRIBUIDO BASADAS EN MPCS PARA EL CONTROL TOTAL DE SISTEMAS INTEGRADOS Y REDES DE DISTRIBUCION/
Agradecimientos:
Los autores agradecen el soporte a la Universidad de Valladolid bajo la beca Ayuda para la Formación de Personal Investigador, y al Ministerio de Economía y Competitividad, bajo el proyecto Metodología de diseño de estrategias ...[+]
Tipo: Artículo

References

Borshchev, A., Filippov, A., July 2004. From system dynamics and discrete event to practical agent based modeling: Reasons, techniques, tools. In: Proceedings of the 22nd International Conference of the System Dynamics Society. Oxford, England. Collier, N., 2003. RePast: An Extensible Framework for Agent Simulation. http://repast.sourceforge.net/(last visited August 2013).

Dong, J., xin Yin, Y., xiang Peng, K., 2008. Industrial process coordinated and controlled based on multi-agent technology. Systems Engineering - Theory & Practice 28 (10), 119-124. DOI: http://dx.doi.org/10.1016/S1874-8651(10)60004-X.

Galán, J.M., Izquierdo, L.R., Izquierdo, S.S., Santos, J.I., del Olmo, R., López-Paredes, A., Edmonds, B., 2009. Errors and artefacts in agent-based modelling. Journal of Artificial Societies and Social Simulation 12 (1), 1. URL: http://jasss.soc.surrey.ac.uk/12/1/1.html. [+]
Borshchev, A., Filippov, A., July 2004. From system dynamics and discrete event to practical agent based modeling: Reasons, techniques, tools. In: Proceedings of the 22nd International Conference of the System Dynamics Society. Oxford, England. Collier, N., 2003. RePast: An Extensible Framework for Agent Simulation. http://repast.sourceforge.net/(last visited August 2013).

Dong, J., xin Yin, Y., xiang Peng, K., 2008. Industrial process coordinated and controlled based on multi-agent technology. Systems Engineering - Theory & Practice 28 (10), 119-124. DOI: http://dx.doi.org/10.1016/S1874-8651(10)60004-X.

Galán, J.M., Izquierdo, L.R., Izquierdo, S.S., Santos, J.I., del Olmo, R., López-Paredes, A., Edmonds, B., 2009. Errors and artefacts in agent-based modelling. Journal of Artificial Societies and Social Simulation 12 (1), 1. URL: http://jasss.soc.surrey.ac.uk/12/1/1.html.

Gilbert, G.N., 2008. Agent-based models. Quantitative applications in the social sciences. Sage.

Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S.K., Huse, G., Huth, A., Jepsen, J.U., Jorgensen, C., Mooij, W.M., Muller, B., Pe’er, G., Piou, C., Railsback, S.F., Robbins, A.M., Robbins, M.M., Rossmanith, E., Ruger, N., Strand, E., Souissi, S., Stillman, R.A., Vabo, R., Visser, U., Deangelis, D.L., 2006. A standard protocol for describing individual-based and agent-based models. Ecological Modelling 198, 115-126.

Grimm, V., Berger, U., DeAngelis, D.L., Polhill, J.G., Giske, J., Railsback, S.F., Nov. 2010. The ODD protocol: A review and first update. Ecological Modelling 221 (23), 2760-2768. DOI: http://dx.doi.org/10.1016/j.ecolmodel.2010.08.019.

Hinkelmann, F., Murrugarra, D., Jarrah, A.S., Laubenbacher, R.C., 2010. A mathematical framework for agent based models of complex biological networks. Computing Research repository abs/1006.0408. URL: http://dblp.uni-trier.de/db/journals/corr/corr1006. html#abs-1006-0408.

Hu, H.-X., Liu, A., Xuan, Q., Yu, L., Xie, G., 2013. Second-order consensus of multi-agent systems in the cooperation-competition network with switching topologies: A time-delayed impulsive control approach. Systems & Control Letters 62 (12), 1125-1135. DOI: http://dx.doi.org/10.1016/j.sysconle.2013.09.002.

Innocenti, B., López, B., Salvi, J., 2007. A multi-agent architecture with cooperative fuzzy control for a mobile robot. Robotics and Autonomous Systems 55 (12), 881-891, robotics and Autonomous Systems in the 50th Anniversary of Artificial Intelligence Campus Multidisciplinary in Perception and Intelligence. DOI: http://dx.doi.org/10.1016/j.robot.2007.07.007.

Izquierdo, L., Galán, J.M., Santos, J.I., del Olmo, R., 2008. Modelado de sistemas complejos mediante simulación basada en agentes y mediante dinámica de sistemas. Empiria: Revista de metodología de ciencias sociales 16, 85-112.

Leombruni, R., Richiardi, M., Sep. 2005. Why are economists sceptical about agent-based simulations? Physica A: Statistical Mechanics and its Applications 355 (1), 103-109. DOI: http://dx.doi.org/10.1016/j.physa.2005.02.072.

Lo, S.K., 2012. A collaborative multi-agent message transmission mechanism in intelligent transportation system - a smart freeway example. Information Sciences 184 (1), 246-265. DOI: http://dx.doi.org/10.1016/j.ins.2011.08.024.

Luck, M., McBurney, P., Shehory, O., Willmott, S., 2005. Agent Technology: Computing as Interaction (A Roadmap for Agent Based Computing). AgentLink.

Luke, S., Balan, G.C., Panait, L., Cioffi-Revilla, C., Paus, S., 2003. MASON: A Java Multi-Agent Simulation Library. In: Macal, C.M., North, M., Sallach, D. (Eds.), Proceedings of Agent 2003, Conference on Challenges in Social Simulation. Argonne National Laboratory.

Macal, C.M., North, M.J., Dec. 2006. Tutorial on agent-based modeling and simulation part 2: How to model with agents. In: Winter Simulation Conference, 2006. WSC 06. Proceedings of the. pp. 73-83. DOI: http://dx.doi.org/10.1109/wsc.2006.323040.

MATLAB, 2010. version 7.10.0 (R2010b). The MathWorks Inc., Natick, Massachusetts.

Minar, N., Burkhart, R.and Langton, C., Askenazi, M., 1996. The swarm simulation system: A toolkit for building multi-agent simulations. Santa Fe Institute working paper 96-06-042. Swarm available at http://www.swarm. org (last visited August 2013).

Pereda, M., Zamarreño, J.M., Jun. 2011. Agent-based modeling of an activated sludge process in a batch reactor. In: 2011 19th Mediterranean Conference on Control & Automation (MED). IEEE, Corfu, pp. 1128-1133. DOI: http://dx.doi.org/10.1109/MED. 2011.5983027.

Pereda, M., Zamarreño, J.M., 2014. “Thermostat II” (Version 3). CoMSES Computational Model Library. Retrieved from: https://www.openabm. org/model/4234/version/3 (last visited June 2014).

Potter, B., Sinclair, J., Till, D., 1996. Introduction to Formal Specification and Z (2nd Edition). Prentice Hall PTR.

Rahmandad, H., Sterman, J., 2008. Heterogeneity and network structure in the dynamics of diffusion: Comparing agent-based and differential equation models. Management Science 54 (5), 998-1014. DOI: http://dx.doi.org/10.1287/mnsc.1070.0787.

Reynolds, C.W., Aug. 1987. Flocks, herds and schools: A distributed behavioral model. SIGGRAPH Computer Graphics 21 (4), 25-34. DOI: http://dx.doi.org/10.1145/37402.37406.

Schelling, T.C., 1969. Models of segregation. The American Economic Review 59 (2), 488-493.

Schieritz, N., Milling, P.M., 2003. Modeling the forest or modeling the trees. comparison of sd and ab simulation. In: Proceedings of the 21st International Conference of the System Dynamics Society.

Torsun, I., 1995. Foundations of Intelligent Knowledge-Based Systems. Library and Information Science. Academic Press Limited.

Van Dyke Parunak, H., Savit, R., Riolo, R.L., 1998. Agent-based modeling vs. equation-based modeling: A case study and userś guide. In: Sichman, J.S. a., Conte, R., Gilbert, N. (Eds.), Multi-Agent Systems and Agent-Based Simulation. Vol. 1534 of Lecture Notes in Computer Science. Springer Berlin Heidelberg, pp. 10-25. DOI: http://dx.doi.org/10.1007/10692956 2.

Wen, G., Hu, G., Yu, W., Cao, J., Chen, G., 2013. Consensus tracking for higher-order multi-agent systems with switching directed topologies and occasionally missing control inputs. Systems & Control Letters 62 (12), 1151-1158. DOI: http://dx.doi.org/10.1016/j.sysconle.2013.09.009.

Wilensky, U., 1997. NetLogo Segregation model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. http://ccl.northwestern.edu/netlogo/models/Segregation (last visited March 2013).

Wilensky, U., 1998. NetLogo Thermostat model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. http://ccl.northwestern.edu/netlogo/models/Thermostat (last visited March 2013).

Wilensky, U., 1999. NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. http://ccl. northwestern.edu/netlogo/(last visited March 2013).

Wilensky, U., 2002. NetLogo Crystallization Basic model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. http://ccl.northwestern.edu/netlogo/models/CrystallizationBasic (last visited March 2013).

Wilensky, U., 2007. NetLogo Solid Diffusion model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. http://ccl.northwestern.edu/netlogo/models/SolidDiffusion (last visited March 2013).

Yu, L., Wang, J., 2013. Robust cooperative control for multi-agent systems via distributed output regulation. Systems & Control Letters 62 (11), 1049-1056. DOI: http://dx.doi.org/10.1016/j.sysconle.2013.08.005.

Zhu, J., 2014. Stabilization and synchronization for a heterogeneous multiagent system via harmonic control. Systems & Control Letters 66 (0), 1-7. DOI: http://dx.doi.org/10.1016/j.sysconle.2013.12.019.

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