Skip to main content

Event-Driven Multi-agent Simulation

  • Conference paper
  • First Online:
Multi-Agent-Based Simulation XV (MABS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9002))

Abstract

Most agent-based models today apply a time-driven approach, i.e. simulation time is advanced in equidistant steps. This time advance method is considerably easier to implement than the more flexible and efficient event-driven approach.

Applying the event-driven approach requires that (a) the durations for agent and environment actions are determined before they terminate, (b) each agent is able to instantly react to changes in its environment, and (c) the update of the state of the environment can be kept efficient despite updating agents asynchronously.

The simulation toolkit famos fulfils these requirements, extending an existing discrete-event simulator. The toolkit also supports a flexible representation of space and the movement of agents in that space. These are areas where existing toolkits for agent-based modelling show shortcomings, despite the fact that a majority of multi-agent models explicitly model space and allow for mobile agents.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    Available at http://famos.sourceforge.net.

  2. 2.

    Available at http://desmoj.sourceforge.net.

  3. 3.

    Another example is David O’Sullivan’s combination of graphs with irregular cellular automata to model spatial processes in cities [30].

  4. 4.

    http://www.jessrules.com/jess.

References

  1. Axtell, R.: Effects of interaction topology and activation regime in several multi-agent systems. In: Moss, S., Davidsson, P. (eds.) MABS 2000. LNCS (LNAI), vol. 1979, pp. 33–48. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  2. Banks, J., Carson, J.S., Nelson, B.L., Nicol, D.: Discrete-Event System Simulation, 3rd edn. Prentice Hall, Upper Saddle River (2000)

    Google Scholar 

  3. Barnes, D.J., Chu, D.: Introduction to Modeling for Biosciences. Springer, London (2010)

    Book  Google Scholar 

  4. Baveco, J.M., Lingeman, R.: An object-oriented tool for individual-oriented simulation: host-parasitoid system application. Ecol. Model. 61, 267–286 (1992)

    Article  Google Scholar 

  5. de Berg, M., van Kreveld, M., Overmars, M., Schwarzkopf, O.: Computational Geometry: Algorithms and Applications. Springer, Heidelberg (1997)

    Book  MATH  Google Scholar 

  6. Boer, K., Kaymak, U., Spiering, J.: From discrete-time models to continuous-time, asynchronous models of financial markets. Comput. Intell. 23(2), 142–161 (2007)

    Article  MathSciNet  Google Scholar 

  7. Bordini, R.H., Hübner, J.F.: Agent-based simulation using BDI programming in Jason. In: Uhrmacher and Weyns [39], pp. 451–476

    Google Scholar 

  8. Daniel, G.: Asynchronous Simulations of a Limit Order Book. Dissertation, University of Manchester, Faculty of Science and Engineering (2006)

    Google Scholar 

  9. Davidsson, P., Holmgren, J., Kyhlbäck, H., Mengistu, D., Persson, M.: Applications of agent based simulation. In: Antunes, L., Takadama, K. (eds.) MABS 2006. LNCS (LNAI), vol. 4442, pp. 15–27. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  10. Edmonds, B., Meyer, R. (eds.): Simulating Social Complexity: A Handbook. Understanding Complex Systems. Springer, Berlin (2013)

    Google Scholar 

  11. Epstein, J.M.: Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton University Press, Princeton (2007)

    Google Scholar 

  12. Gamma, E., Helm, R., Johnson, R.E., Vlissides, J.M.: Design Patterns - Elements of Reusable Object-Oriented Software. Addison-Wesley, Reading (1994)

    Google Scholar 

  13. Gilbert, N., Troitzsch, K.G.: Simulation for the Social Scientist, 2nd edn. Open University Press, Maidenhead (2005)

    Google Scholar 

  14. Grimm, V., Railsback, S.F.: Individual-Based Modeling and Ecology. Princeton series in theoretical and computational biology. Princeton University Press, Princeton (2005)

    MATH  Google Scholar 

  15. Heppenstall, A.J., Crooks, A.T., See, L.M., Batty, M. (eds.): Agent-Based Models of Geographical Systems. Springer, Dordrecht (2012)

    Google Scholar 

  16. Himmelspach, J., Uhrmacher, A.M.: Plug’n simulate. In: Proceedings of the 40th Annual Simulation Symposium (ANSS-40 2007), Norfolk, VA, 26–28 March 2007, pp. 137–143. IEEE Computer Society (2007)

    Google Scholar 

  17. Jacobs, B.I., Levy, K.N., Markovitz, H.M.: Financial market simulation in the 21st century. J. Portfolio Manage. (30th Anniversary Issue) 30, 142–151 (2004)

    Article  Google Scholar 

  18. Klügl, F., Herrler, R., Fehler, M.: Sesam: implementation of agent-based simulation using visual programming. In: Nakashima, H., Wellman, M.P., Weiss, G., Stone, P. (eds.) Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, 8–12 May 2006, pp. 1439–1440. ACM (2006)

    Google Scholar 

  19. Knaak, N., Meyer, R., Page, B.: Agent-based simulation of sustainable logistic strategies for large city courier services. In: Proceedings of EnviroInfo 2003, 17th International Conference Informatics for Environmental Protection, Cottbus, pp. 318–325, September 2003

    Google Scholar 

  20. Knaak, N., Meyer, R., Page, B.: Logistic strategies for sustainable city courier services - an agent-based simulation approach. In: Proceedings of HMS 2004, 8th International Workshop on Harbour, Maritime & Multimodal Logistics Modelling and Simulation, Rio de Janeiro, September 2004

    Google Scholar 

  21. Law, A.M., Kelton, W.D.: Simulation Modeling and Analysis, 3rd edn. McGraw-Hill, Boston (2000)

    Google Scholar 

  22. Lawson, B.G., Park, S.: Asynchronous time evolution in an artificial society model. J. Artif. Soc. Soc. Simul. 3(1) (2000). http://jasss.soc.surrey.ac.uk/3/1/2.html

  23. Luke, S.: Multiagent simulation and the MASON library. Manual version 17, Department of Computer Science, George Mason University, Fairfax, VA, May 2013, http://cs.gmu.edu/~eclab/projects/mason/manual.pdf

  24. Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K., Balan, G.: MASON: a multi-agent simulation environment. Simulation 82(7), 517–527 (2005)

    Article  Google Scholar 

  25. Macal, C.M., North, M.J.: Agent-based modeling and simulation: Abms examples. In: Mason, S.J., Hill, R.R., Mönch, L., Rose, O., Jefferson, T., Fowler, J.W. (eds.) Proceedings of the 2008 Winter Simulation Conference, pp. 101–112 (2008)

    Google Scholar 

  26. Michel, F., Ferber, J., Drogoul, A.: Multi-agent systems and simulation: a survey from the agents community’s perspective. In: Uhrmacher and Weyns [39], pp. 3–52

    Google Scholar 

  27. Minar, N., Burkhart, R., Langton, C.G., Askenazi, M.: The swarm simulation system: a toolkit for building multi-agent simulations. Working Paper 96-06-042, Santa Fe Institute (1996), http://www.santafe.edu/media/workingpapers/96-06-042.pdf

  28. North, M.J., Collier, N.T., Ozik, J., Tatara, E.R., Macal, C.M., Bragen, M., Sydelko, P.: Complex adaptive systems modeling with Repast Simphony. Complex Adapt. Syst. Model. 1, 3 (2013). http://www.casmodeling.com/content/1/1/3

    Article  Google Scholar 

  29. North, M.J., Collier, N.T., Vos, J.R.: Experiences creating three implementations of the Repast agent modeling toolkit. ACM Trans. Model. Comput. Simul. 16(1), 1–25 (2006)

    Article  Google Scholar 

  30. O’Sullivan, D.: Graph-based Cellular Automaton Models of Urban Spatial Processes. Dissertation, Centre of Advanced Spatial Analysis, University of London (2000)

    Google Scholar 

  31. Page, B., Kreutzer, W.: The Java Simulation Handbook: Simulating Discrete Event Systems with UML and Java. Shaker, Aachen (2005)

    Google Scholar 

  32. Railsback, S.F., Lytinen, S.L., Jackson, S.K.: Agent-based simulation platforms: review and development recommendations. Simulation 82(9), 609–623 (2006)

    Article  Google Scholar 

  33. Samuelson, D.A., Macal, C.M.: Agent-based simulation comes of age. Oper. Res./Manage. Sci. Today 33(4), 34 (2006)

    Google Scholar 

  34. Schelling, T.C.: Micromotives and Macrobehavior. Norton, New York (1978)

    Google Scholar 

  35. Smith, R.G.: The contract net protocol: high level communication and control in a distributed problem solver. IEEE Trans. Comput. C–29(12), 1104–1113 (1980)

    Article  Google Scholar 

  36. Tesfatsion, L.: Agent-based computational economics: growing economies from the bottom up. Artif. Life 8(1), 55–82 (2002)

    Article  MathSciNet  Google Scholar 

  37. Theodoropoulos, G., Minson, R., Ewald, R., Lees, M.: Simulation engines for multi-agent systems. In: Uhrmacher and Weyns [39], pp. 77–108

    Google Scholar 

  38. Troitzsch, K.: A multi-agent model of bilingualism in a small population. In: Coelho, H., Espinasse, B. (eds.) 5th Workshop on Agent-Based Simulation, pp. 38–43. SCS Publishing House, Erlangen (2004)

    Google Scholar 

  39. Uhrmacher, A.M., Weyns, D. (eds.): Multi-Agent Systems: Simulation and Applications. CRC Press/Taylor and Francis, Boca Raton (2009)

    Google Scholar 

  40. Weyns, D., Holvoet, T.: Model for situated multi-agent-systems with regional synchronization. In: Jardim-Goncalves, R., Cha, J., Steiger-Garcao, A. (eds.) Enhanced Interoperable Systems: Proceedings of the 10th International Conference on Concurrent Engineering (ISPE CE 2003), Madeira, Portugal, 26–30 July, pp. 177–188 (2003)

    Google Scholar 

  41. Wilensky, U.: Netlogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston (1999). http://ccl.northwestern.edu/netlogo/

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ruth Meyer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Meyer, R. (2015). Event-Driven Multi-agent Simulation. In: Grimaldo, F., Norling, E. (eds) Multi-Agent-Based Simulation XV. MABS 2014. Lecture Notes in Computer Science(), vol 9002. Springer, Cham. https://doi.org/10.1007/978-3-319-14627-0_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-14627-0_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14626-3

  • Online ISBN: 978-3-319-14627-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics