A formalism for multi-level emergent behaviours in designed component-based systems and agent-based simulations

  • Chih-Chun Chen
  • Sylvia B. Nagl
  • Christopher D. Clack
Part of the Understanding Complex Systems book series (UCS)

Summary

There currently exists no means of specifying or analysing specific emergent behaviours in designed multi-component systems. For this reason, important questions about the lower level mechanisms giving rise to emergent behaviours cannot be resolved.

We provide a compositional definition of behaviours in terms of complex events, which can be defined at multiple levels of abstraction and related hierarchically. Based on existing theories of emergence, we also distinguish complex events that constitute emergent behaviours and those that do not. We describe how such emergent behaviours can be analysed by decomposition in terms of their underlying mechanisms.

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References

  1. 1.
    Bankes, S.C.: Agent-based modelling - a revolution? PNAS 99, 7199–7200 (2002)CrossRefGoogle Scholar
  2. 2.
    Bonabeau, E., Dessalles, J.L.: Detection and emergence. Intellectica 2(25), 85–94 (1997)Google Scholar
  3. 3.
    Chen, C.-C., Nagl, S.B., Clack, C.D.: Specifying, detecting and analysing emergent behaviours in multi-level agent-based simulations. In: Proceedings of the Summer Simulation Conference, Agent-directed simulation. SCS (2007)Google Scholar
  4. 4.
    Dassow, J., Freund, R., Paun, G.: Cooperating array grammar systems. International Journal of Pattern Recognition Artificial Intelligence 9, 1029–1053 (1995)CrossRefGoogle Scholar
  5. 5.
    Deguet, J., Demazeau, Y., Magnin, L.: Elements about the emergence issue - a survey of emergence definitions. ComPlexUs 3, 24–31 (2006)CrossRefGoogle Scholar
  6. 6.
    Demazeau, Y.: Steps towards multi-agent oriented programming. In: First International Workshop on Multi Agent Systems, Boston, Mass (1997)Google Scholar
  7. 7.
    Dorigo, M., Tuci, E., Trianni, V., Gross, R., Nouyan, S., Ampatzis, C., Labella, T.H., O’Grady, R., Bonani, M., Mondada, F.: SWARM-BOT: Design and Implementation of Colonies of Self-assembling Robots, pp. 103–135 (2006)Google Scholar
  8. 8.
    Friedman, M.: Explanation and scientific undersatnding. Journal of Philosophy 71, 5–19 (1974)CrossRefGoogle Scholar
  9. 9.
    Gleizes, M.-P., Camps, V., George, J.-P., Capera, D.: Engineering systems which generate emergent functionalities. In: Weyns, D., Brueckner, S.A., Demazeau, Y. (eds.) EEMMAS 2007. LNCS, vol. 5049, pp. 58–75. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  10. 10.
    Johnson, J.: Hypernetworks for reconstructing the dynamics of multilevel systems. In: Proceedings of European Conference on Complex Systems (November 2006)Google Scholar
  11. 11.
    Johnson, J.: Multidimensional Events in Multilevel Systems, pp. 311–334. Physica-Verlag HD (2007)Google Scholar
  12. 12.
    Kim, J.: Downward causation. In: Emergence or reduction?, vol. 1, pp. 119–138. Walter de Gruyter & Co. (1992)Google Scholar
  13. 13.
    Kubik, A.: Toward a formalization of emergence. Artificial Life 9, 41–66 (2003)CrossRefGoogle Scholar
  14. 14.
    Parisey, N., Beurton-Aimar, M., Lales, C., Strandh, R., Mazat, J.P.: Towards modelling the q cycle by multi agent systems. In: ECAL 2005 (2005)Google Scholar
  15. 15.
    Ryan, A.: Emergence is coupled to scope, not level. Nonlinear Sciences (2007)Google Scholar
  16. 16.
    Salmon, W.: Scientific explanation and the causal structure of the world. Princeton University Press, Princeton (1984)Google Scholar
  17. 17.
    Sawyer, R.K.: Simulating emergence and downward causation in small groups. In: Moss, S., Davidsson, P. (eds.) Multi Agent Based Simulation: Proceedings of the Second International Workshop on Multi-Agent Based Simulation (MABS 2001), pp. 49–67. Springer, Heidelberg (2001)Google Scholar
  18. 18.
    Shalizi, C.: Causal Architecture, Complexity and Self-Organization in Time Series and Cellular Automata. PhD thesis, University of Michigan (2001)Google Scholar
  19. 19.
    Shalizi, C.R.: Methods and Techniques of Complex Systems Science: An Overview, pp. 33–114. Springer, New York (2006)CrossRefGoogle Scholar
  20. 20.
    Sudeikat, J., Renz, W.: Toward systemic mas development: Enforcing decentralised self-organisation by composition and refinement of archetype dynamics. In: Engineering Environment-Mediated Multiagent Systems (EEMAS 2007). LNCS. Springer, Heidelberg (2007)Google Scholar
  21. 21.
    Walker, D.C., Southgate, J., Hill, G., Halcombe, M., Hose, D.R., Wood, S.M., Neil, M., Smallwood, R.H.: The epitheliome - agent-based modelling of the social behaviour of cells. BioSystems 76, 89–100 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Chih-Chun Chen
    • 1
  • Sylvia B. Nagl
    • 2
  • Christopher D. Clack
    • 1
  1. 1.Department of Computer ScienceUniversity College London 
  2. 2.Department of Oncology and BiochemistryUniversity College London 

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