Abstract
Using purely agent-based platforms for any kind of simulation requires to address the following challenges: (1) scalability (efficient scheduling of agent cycles is difficult), (2) efficient memory management (when and which data should be fetched, cached, or written to/from disk), and (3) modelling (no generally accepted meta-models exist: what are essential concepts, what just implementation details?). While dedicated professional simulation tools usually provide rich domain libraries and advanced visualisation techniques, and support the simulation of large scenarios, they do not allow for “agentization” of single components. We are trying to bridge this gap by developing a distributed, scalable runtime platform for multiagent simulation, MASeRaTi, addressing the three problems mentioned above. It allows to plug-in both dedicated simulation tools (for the macro view) as well as the agentization of certain components of the system (to allow a micro view). If no agent-related features are used, its performance should be as close as possible to the legacy system used.
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Ahlbrecht, T., Dix, J., Köster, M., Kraus, P., Müller, J.P.: A scalable runtime platform for multiagent-based simulation. Technical Report IfI-14-02, TU Clausthal (February 2014)
Ahlbrecht, T., Dix, J., Köster, M., Schlesinger, F.: Multi-Agent Programming Contest 2013. In: Cossentino, M., El Fallah Seghrouchni, A., Winikoff, M. (eds.) EMAS 2013. LNCS (LNAI), vol. 8245, pp. 292–318. Springer, Heidelberg (2013)
Behrens, T.: Towards Building Blocks for Agent-Oriented Programming. PhD thesis, Clausthal University of Technology (2012)
Behrens, T., Dastani, M., Dix, J., Köster, M., Novák, P.: The Multi-Agent Programming Contest from 2005-2010. Annals of Mathematics and Artificial Intelligence 59, 277–311 (2010)
Behrens, T.M., Dix, J., Dastani, M., Köster, M., Novák, P.: Technical Foundations of the Agent Contest 2008. Technical Report IfI-08-05, Clausthal University of Technology (December 2008)
Bordini, R.H., Dastani, M., Dix, J., El Fallah-Seghrouchni, A. (eds.): Multi-Agent Programming: Languages, Tools and Applications. Springer, Berlin (2009)
Bordini, R.H., Hübner, J.F., Wooldridge, M.: Programming multi-agent systems in AgentSpeak using Jason. Wiley & Sons (2007)
Chu, V.-H., Görmer, J., Müller, J.P.: ATSim: Combining AIMSUN and Jade for agent-based traffic simulation. In: Proceedings of the 14th Conference of the Spanish Association for Artificial Intelligence (CAEPIA), vol. 1, AEPIA (2011), Electronic Proceedings
Dávila, J., Uzcátegui, M.: Galatea: A multi-agent simulation platform. In: Proceedings of the International Conference on Modeling, Simulation and Neural Networks (2000)
Driel, M., Kraaijeveld, J., Shao, Z.K., van der Zon, R.: A Survey on MMOG System Architectures (2011)
Fiosins, M., Fiosina, J., Müller, J.P., Görmer, J.: Reconciling Strategic and Tactical Decision Making in Agent-oriented Simulation of Vehicles in Urban Traffic. In: Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques, SIMUTools 2011, pp. 144–151. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), Brussels (2011)
Fiosins, M., Fiosina, J., Müller, J.P., Görmer, J.: Agent-Based Integrated Decision Making for Autonomous Vehicles in Urban Traffic. In: Demazeau, Y., Pechoucek, M., Corchado, J.M., Perez, J.B. (eds.) Adv. on Prac. Appl. of Agents and Mult. Sys. AISC, vol. 88, pp. 173–178. Springer, Heidelberg (2011)
Garro, A., Russo, W.: easyABMS: A domain-expert oriented methodology for agent-based modeling and simulation. Simulation Modelling Practice and Theory 18(10), 1453–1467 (2010)
Gehrke, J.D., Ober-Blöbaum, C.: Multiagent-based Logistics Simulation with PlaSMA. In: Informatik 2007 - Informatik trifft Logistik, Band 1. Beiträge der 37. Jahrestagung der Gesellschaft für Informatik, pp. 416–419. Technologie-Zentrum Informatik (2007)
Ghorbani, A., Bots, P.W.G., Dignum, V., Dijkema, G.P.J.: MAIA: A Framework for Developing Agent-Based Social Simulations. J. Artificial Societies and Social Simulation 16(2) (2013)
Görmer, J., Müller, J.P.: Group Coordination for Agent-Oriented Urban Traffic Management. In: Demazeau, Y., Müller, J.P., Rodríguez, J.M.C., Pérez, J.B. (eds.) Advances on PAAMS. AISC, vol. 155, pp. 245–248. Springer, Heidelberg (2012)
Helbing, D., Hennecke, A., Shvetsov, V., Treiber, M.: MASTER: Macroscopic traffic simulation based on a gas-kinetic, non-local traffic model. Transportation Research Part B: Methodological 35(2), 183–211 (2001)
Hill, M.D., Marty, M.R.: Amdahl’s Law in the Multicore Era. Computer 41(7), 33–38 (2008)
Huhn, M., Müller, J.P., Görmer, J., Homoceanu, G., Le, N.-T., Märtin, L., Mumme, C., Schulz, C., Pinkwart, N., Müller-Schloer, C.: Autonomous agents in organized localities regulated by institutions. In: 2011 Proceedings of the 5th IEEE International Conference on Digital Ecosystems and Technologies (DEST), pp. 54–61 (May 2011)
Ierusalimschy, R.: Programming with multiple paradigms in lua. In: Escobar, S. (ed.) WFLP 2009. LNCS, vol. 5979, pp. 1–12. Springer, Heidelberg (2010)
Klügl, F., Davidsson, P.: AMASON: Abstract Meta-model for Agent-Based SimulatiON. In: Klusch, M., Thimm, M., Paprzycki, M. (eds.) MATES 2013. LNCS, vol. 8076, pp. 101–114. Springer, Heidelberg (2013)
Klügl, F., Puppe, F.: The Multi-Agent Simulation Environment SeSAm. In: Kleine Büning, H. (ed.) Proceedings of Simulation in Knowledge-based Systems, Universität Paderborn, Reihe Informatik, Universität Paderborn, Universität Paderborn (April 1998)
Krajzewicz, D., Hertkorn, G., Rössel, C., Wagner, P.: Sumo (simulation of urban mobility). In: Proc. of the 4th Middle East Symposium on Simulation and Modelling, pp. 183–187 (2002)
Kuhl, F., Dahmann, J., Weatherly, R.: Creating computer simulation systems: An introduction to the high level architecture. Prentice Hall PTR Englewood Cliffs, Upper Saddle River (2000)
Ierusalimschy, R., de Figueiredo, L.H., Celes, W.: Lua Programming Gems. Roberto Ierusalimschy (2008)
Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K.: Mason: A new multi-agent simulation toolkit. In: Proceedings of the 2004 SwarmFest Workshop, vol. 8 (2004)
Papageorgiou, M., Blosseville, J.-M., Hadj-Salem, H.: Modelling and real-time control of traffic flow on the southern part of Boulevard Peripherique in Paris: Part I: Modelling. Transportation Research Part A: General 24(5), 345–359 (1990)
Shoham, Y.: Agent-Oriented Programming. Artificial Intelligence 60(1), 51–92 (1993)
Subrahmanian, V.S., Bonatti, P., Dix, J., Eiter, T., Kraus, S., Özcan, F., Ross, R.: Heterogenous Active Agents. MIT Press (2000)
Tisue, S., Wilensky, U.: NetLogo: A simple environment for modeling complexity. In: International Conference on Complex Systems, pp. 16–21 (2004)
Weiss, G. (ed.): Multiagent systems. MIT-Press (2013)
Wooldridge, M.J.: An Introduction to MultiAgent Systems (2009)
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Ahlbrecht, T., Dix, J., Köster, M., Kraus, P., M”uller, J.P. (2014). A Scalable Runtime Platform for Multiagent-Based Simulation. In: Dalpiaz, F., Dix, J., van Riemsdijk, M.B. (eds) Engineering Multi-Agent Systems. EMAS 2014. Lecture Notes in Computer Science(), vol 8758. Springer, Cham. https://doi.org/10.1007/978-3-319-14484-9_5
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DOI: https://doi.org/10.1007/978-3-319-14484-9_5
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