- -

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

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

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

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Pereda, María es_ES
dc.contributor.author Zamarreño, Jesús M. es_ES
dc.date.accessioned 2020-05-19T06:42:18Z
dc.date.available 2020-05-19T06:42:18Z
dc.date.issued 2015-07-10 es_ES
dc.identifier.issn 1697-7912 es_ES
dc.identifier.uri http://hdl.handle.net/10251/143651
dc.description.abstract [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 de modelado en el campo de la Automática es más bien testimonial. En este artículo mostramos cómo se puede abordar el modelado basado en agentes desde el punto de vista de la Ingeniería de Sistemas y Automática y las particularidades que tiene como herramienta de modelado. Asimismo, proponemos una descripción matemática de los modelos basados en agentes que ilustramos con un par de ejemplos. es_ES
dc.description.abstract [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 deal with ABM from the point of view of the System Engineering and Automatic Control field and the specific issues to take into account as modelling technique. Besides, we propose a mathematical description that is illustrated through two simple examples. es_ES
dc.description.sponsorship 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 de control jerárquico y distribuido basadas en MPCs para el control total de sistemas integrados y redes de distribución (DPI 2012- 39381-C02-02).
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Agents es_ES
dc.subject Dynamic modelling es_ES
dc.subject Systems engineering es_ES
dc.subject State space es_ES
dc.subject Conceptual representations es_ES
dc.subject Agentes es_ES
dc.subject Modelado dinámico es_ES
dc.subject Ingeniería de sistemas es_ES
dc.subject Espacio de estados es_ES
dc.subject Representaciones conceptuales es_ES
dc.title Modelado Basado en Agentes: un Enfoque desde la Ingeniería de Sistemas es_ES
dc.title.alternative Agent-Based Modelling: an Approach from the Systems Engineering. es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.riai.2015.02.007 es_ES
dc.relation.projectID 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/
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation 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 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.riai.2015.02.007 es_ES
dc.description.upvformatpinicio 304 es_ES
dc.description.upvformatpfin 312 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 3 es_ES
dc.identifier.eissn 1697-7920 es_ES
dc.relation.pasarela OJS\9364 es_ES
dc.contributor.funder Universidad de Valladolid
dc.contributor.funder Ministerio de Economía y Competitividad
dc.description.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). es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references Gilbert, G.N., 2008. Agent-based models. Quantitative applications in the social sciences. Sage. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references Luck, M., McBurney, P., Shehory, O., Willmott, S., 2005. Agent Technology: Computing as Interaction (A Roadmap for Agent Based Computing). AgentLink. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references MATLAB, 2010. version 7.10.0 (R2010b). The MathWorks Inc., Natick, Massachusetts. es_ES
dc.description.references 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). es_ES
dc.description.references 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. es_ES
dc.description.references 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). es_ES
dc.description.references Potter, B., Sinclair, J., Till, D., 1996. Introduction to Formal Specification and Z (2nd Edition). Prentice Hall PTR. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references Schelling, T.C., 1969. Models of segregation. The American Economic Review 59 (2), 488-493. es_ES
dc.description.references 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. es_ES
dc.description.references Torsun, I., 1995. Foundations of Intelligent Knowledge-Based Systems. Library and Information Science. Academic Press Limited. es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES
dc.description.references 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). es_ES
dc.description.references 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). es_ES
dc.description.references 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). es_ES
dc.description.references 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). es_ES
dc.description.references 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). es_ES
dc.description.references 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. es_ES
dc.description.references 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. es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem