Abstract
The mobility models followed within metropolitan areas, mainly based on the massive use of the car instead of the public transportation, will soon become unsustainable unless there is a change of citizens’ minds and transport policies. The main challenge related to urban mobility is that of getting free-flowing greener cities, which are provided with a smarter and accessible urban transport system. In this paper, we present an agent-based social simulation approach to tackle this kind of social-ecological systems. The Jason Multi-modal Agent Decision Making (JMADeM) library enable us to model and implement the social decisions made by each habitant about how to get to work every day, e.g., by train, by car, sharing a car, etc. In this way, we focus on the decision making aspects of this problem at a micro level, instead of focussing on spatial or other macro issues. The first results show the different outcomes produced by societies of individualist and egalitarian agents, in terms of the average travel time, the use of the urban transportation and the amount of CO 2 emitted to the environment.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bordini, R.H., Hübner, J.F., Wooldrige, M.: Programming Multi-Agent Systems in Agent Speak using Jason. Wiley, Chichester (2007)
Chevaleyre, Y., Dunne, P.E., Endriss, U., Lang, J., Lemaitre, M., Maudet, N., Padget, J., Phelps, S., Rodriguez-Aguilar, J.A., Sousa, P.: Issues in multiagent resource allocation. Informatica 30, 3–31 (2006)
E. Commission Towards a new culture for urban mobility (September 2007), http://ec.europa.eu/transport/urban/index_en.htm
Conte, R., Castelfranchi, C.: Cognitive and Social Action. UCL Press, London (1995)
Decker, K.S.: Task environment centered simulation. In: Simulating Organizations: Computational Models of Institutions and Groups, pp. 105–128. AAAI Press / MIT Press, Menlo Park (1998)
Dignum, V., Dignum, F.: Modelling agent societies: Co-ordination frameworks and institutions. In: Brazdil, P.B., Jorge, A.M. (eds.) EPIA 2001. LNCS (LNAI), vol. 2258, pp. 191–204. Springer, Heidelberg (2001)
Falcone, R., Pezzulo, G., Castelfranchi, C., Calvi, G.: Why a cognitive trustier performs better: Simulating trust-based contract nets. In: Proc. of AAMAS 2004: Autonomous Agents and Multi-Agent Systems, pp. 1392–1393. ACM, New York (2004)
Ferber, J., Gutknecht, O.: A meta-model for the analysis and design of organizations in multi-agents systems. In: Proc. of the 3rd International Conference on Multi-Agent Systems (ICMAS 1998), pp. 128–135. IEEE Press, Los Alamitos (1998)
Grimaldo, F., Lozano, M., Barber, F.: MADeM: a multi-modal decision making for social MAS. In: Proc. of AAMAS 2008: Autonomous Agents and Multi-Agent Systems, pp. 183–190. ACM, New York (2008)
Grimaldo, F., Lozano, M., Barber, F.: J-MADeM, an open-source library for social decision-making. In: Proc. of CCIA 2009: International Conference of the Catalan Association for Artificial Intelligence, pp. 207–214. IOS Press, Amsterdam (2009)
Grimm, V.: Ten years of individual-based modelling in ecology: what have we learned and what could we learn in the future? Ecological Modelling 115(2-3), 129–148 (1999)
Hexmoor, H.: From inter-agents to groups. In: Proc. of ISAI 2001: International Symposium on Artificial Intelligence (2001)
Hübner, J.F., Sichman, J.S., Boissier, O.: Developing organised multi-agent systems using the Moise+ model: Programming issues at the system and agent levels. International Journal of Agent-Oriented Software Engineering 1(3/4), 370–395 (2007)
Janssen, M.A., Ostrom, E.: Governing social-ecological systems. In: Tesfatsion, L., Judd, K.L. (eds.) Handbook of Computational Economics, 1st edn., vol. 2, ch. 30, pp. 1465–1509. Elsevier, Amsterdam (2006)
Kohler, T., Gumerman, G., Reynolds, R.: Simulating ancient societies. Scientific American 293(2), 76–83 (2005)
Prietula, M., Carley, K., Gasser, L. (eds.): Simulating Organizations: Computational Models of Institutions and Groups. AAAI Press / MIT press (1998)
Rao, A.S.: AgentSpeak(L): BDI agents speak out in a logical computable language. In: Perram, J., Van de Velde, W. (eds.) MAAMAW 1996. LNCS, vol. 1038, pp. 42–55. Springer, Heidelberg (1996)
Sichman, J., Demazeau, Y.: On social reasoning in multi-agent systems. Revista Ibero-Americana de Inteligencia Artificial 13, 68–84 (2001)
Tesfatsion, L.: Agent-based computational economics: A constructive approach to economic theory. In: Tesfatsion, L., Judd, K.L. (eds.) Handbook of Computational Economics, vol. 2, ch. 16, pp. 831–880. Elsevier, Amsterdam (2006)
Waddell, P.: Urbansim: Modeling urban development for land use, transportation and environmental planning. Journal of the American Planning Association 68, 297–314 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Grimaldo, F., Lozano, M., Barber, F., Guerra-Hernández, A. (2011). A J-MADeM Agent-Based Social Simulation to Model Urban Mobility. In: Demazeau, Y., Pěchoucěk, M., Corchado, J.M., Pérez, J.B. (eds) Advances on Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, vol 88. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19875-5_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-19875-5_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19874-8
Online ISBN: 978-3-642-19875-5
eBook Packages: EngineeringEngineering (R0)