Designing Adaptive Systems Using Teleo-Reactive Agents

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8780)

Abstract

Although adaptivity is a central feature of agents and multi-agent systems (MAS), there is no precise definition of it in the literature. What does it mean for an agent or for a MAS to be adaptive? How can we reason about and measure the ability of agents and MAS to adapt? How can we systematically design adaptive systems? In this paper, we provide a formal definition of adaptivity, and a framework for designing adaptive systems aimed at addressing these issues.

The definition of adaptivity, based on Dijkstra’s notion of self stabilisation, is independent of any particular mechanism for ensuring adaptivity, and any particular specification notation. The framework for designing adaptive systems is similarly independent of both implementation mechanisms and specification notation. It is based on the paradigm of teleo-reactive agents proposed by Nilsson: a paradigm in which agents move towards their goal in the presence of a continually changing environment.

References

  1. 1.
    Anceaume, E., Défago, X., Potop-Butucaru, M., Roy, M.: A framework for proving the self-organization of dynamic systems. CoRR, abs/1011.2312 (2010)Google Scholar
  2. 2.
    Artikis, A.: A formal specification of dynamic protocols for open agent systems. CoRR, abs/1005.4815 (2010)Google Scholar
  3. 3.
    Böcker, J., Schulz, B., Knoke, T., Fröhleke, N.: Self-optimization as a framework for advanced control systems. In: Industrial Electronics Conference (IECON 2006), pp. 4671–4675. IEEE (2006)Google Scholar
  4. 4.
    Bruni, R., Corradini, A., Gadducci, F., Lluch Lafuente, A., Vandin, A.: A conceptual framework for adaptation. In: de Lara, J., Zisman, A. (eds.) FASE 2012. LNCS, vol. 7212, pp. 240–254. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  5. 5.
    Bucchiarone, A., Lafuente, A.L., Marconi, A., Pistore, M.: A formalisation of adaptable pervasive flows. In: Laneve, C., Su, J. (eds.) WS-FM 2009. LNCS, vol. 6194, pp. 61–75. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  6. 6.
    Dastani, M., Hindriks, K.V., Meyer, J.-J.C. (eds.): Specification and Verification of Multi-agent Systems. Springer, Heidelberg (2010)MATHGoogle Scholar
  7. 7.
    de Alfaro, L., Henzinger, T.A.: Interface automata. In: Symposium on Foundations of Software Engineering, pp. 109–120. ACM Press (2001)Google Scholar
  8. 8.
    Dijkstra, E.W.: Self-stabilizing systems in spite of distributed control. Commun. ACM 17, 643–644 (1974)CrossRefMATHGoogle Scholar
  9. 9.
    d’Inverno, M., Luck, M.: Development and application of a formal agent framework. In: International Conference on Formal Engineering Methods (ICFEM’97), pp. 222–231. IEEE Press (1997)Google Scholar
  10. 10.
    Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Natural Computing Series. Springer, Heidelberg (2003)CrossRefMATHGoogle Scholar
  11. 11.
    Ellis, C.A.: Team automata for groupware systems. In: Hayne, S., Prinz, W. (eds.) International ACM SIGGROUP Conference on Supporting Group Work: The Integration Challenge, pp. 415–424. ACM Press (1997)Google Scholar
  12. 12.
    Georgiadis, I., Magee, J., Kramer. J.: Self-organising software architectures for distributed systems. In: Workshop on Self-healing Systems (WOSS ’02), pp. 33–38 (2002)Google Scholar
  13. 13.
    Gouda, M.G., Herman, T.: Adaptive programming. IEEE Trans. Softw. Eng. 17(9), 911–921 (1991)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Gruer, P., Hilaire, V., Koukam, A., Cetnarowicz, K.: A formal framework for multi-agent systems analysis and design. Expert Syst. Appl. 23(4), 349–355 (2002)CrossRefGoogle Scholar
  15. 15.
    Gubisch, G., Steinbauer, G., Weiglhofer, M., Wotawa, F.: A teleo-reactive architecture for fast, reactive and robust control of mobile robots. In: Nguyen, N.T., Borzemski, L., Grzech, A., Ali, M. (eds.) IEA/AIE 2008. LNCS (LNAI), vol. 5027, pp. 541–550. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  16. 16.
    Güdemann, M., Nafz, F., Ortmeier, F., Seebach, H., Reif, W.: A specification and construction paradigm for organic computing systems. In: IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2008), pp. 233–242. IEEE Computer Society Press (2008)Google Scholar
  17. 17.
    Hölzl, M., Wirsing, M.: Towards a system model for ensembles. In: Agha, G., Danvy, O., Meseguer, J. (eds.) Formal Modeling: Actors, Open Systems, Biological Systems. LNCS, vol. 7000, pp. 241–261. Springer, Heidelberg (2011) Google Scholar
  18. 18.
    Hunter, A., Delgrande, J.P.: Iterated belief change: a transition system approach. In: International Joint Conference on Artificial Intelligence (IJCAI05), pp. 460–465 (2005)Google Scholar
  19. 19.
    Lynch, N., Tuttle, M.: An introduction to Input/Output automata. CWI Q. 2(3), 219–246 (1989)MathSciNetMATHGoogle Scholar
  20. 20.
    Mitchell, T.: Machine Learning. McGraw Hill, New York (1997)MATHGoogle Scholar
  21. 21.
    Mohyeldin, E., Fahrmair, M., Sitou, W., Spanfelner, B.: A generic framework for context aware and adaptation behaviour of reconfigurable systems. In: IEEE International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC05). IEEE Press (2005)Google Scholar
  22. 22.
    Nafz, F., Ortmeier, F., Seebach, H., Steghöfer, J.-P., Reif, W.: A universal self-organization mechanism for role-based organic computing systems. In: González Nieto, J., Reif, W., Wang, G., Indulska, J. (eds.) ATC 2009. LNCS, vol. 5586, pp. 17–31. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  23. 23.
    Nilsson, N.: Teleo-reactive programs for agent control. J. Artif. Intell. Res. 1, 139–158 (1994)Google Scholar
  24. 24.
    Nilsson, N.: Teleo-reactive programs and the triple-tower architecture. Electron. Trans. Artif. Intell. 5, 99–110 (2001)Google Scholar
  25. 25.
    Polani, D.: Foundations and formalizations of self-organization. In: Prokopenko, M. (ed.) Advances in Applied Self-organizing Systems. Advanced Information and Knowledge Processing, pp. 19–37. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  26. 26.
    Sanders, J.W., Smith, G.: Assuring adaptive behaviour in self-organising systems. In: Self-Organising and Self-Adaptive Systems Workshop (SASOW 2010), pp. 172–177. IEEE Computer Society Press (2010)Google Scholar
  27. 27.
    Sanders, J.W., Smith, G.: Emergence and refinement. Formal Aspects Comput. 24(1), 45–65 (2012)MathSciNetCrossRefMATHGoogle Scholar
  28. 28.
    Smith, G.: The Object-Z Specification Language. Kluwer, Norwell (2000)CrossRefMATHGoogle Scholar
  29. 29.
    Smith, G., Sanders, J.W., Winter, K.: Reasoning about adaptivity of agents and multi-agent systems. In: International Conference on Engineering of Complex Computer Systems (ICECCS 2012). IEEE Computer Society Press (2012)Google Scholar
  30. 30.
    Smith, G., Winter, K.: Incremental development of multi-agent systems in Object-Z. In: Software Engineering Workshop (SEW-35). IEEE Computer Society Press (2012)Google Scholar
  31. 31.
    Smith, J.B.: Collective Intelligence in Computer-Based Collaboration. Lawrence Erlbaum Associates, Hillsdale (1994)Google Scholar
  32. 32.
    Spivey, J.M.: The Z Notation: A Reference Manual, 2nd edn. Prentice-Hall International, Englewood Cliffs (1992)Google Scholar
  33. 33.
    Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)Google Scholar
  34. 34.
    ter Beek, M., Ellis, C., Kleijn, J., Rozenberg, G.: Synchronizations in team automata for groupware systems. Comput. Support. Coop. Work: J. Collab. Comput. 12(1), 21–69 (2003)CrossRefGoogle Scholar
  35. 35.
    Valiant, L.: A theory of the learnable. Commun. ACM 27, 1134–1142 (1984)CrossRefMATHGoogle Scholar
  36. 36.
    Wooldridge, M.: An Introduction to Multiagent Systems. Wiley, New York (2002)Google Scholar
  37. 37.
    Zambonelli, F., Omicini, A.: Challenges and research directions in agent-oriented software engineering. Auton. Agent. Multi-Agent Syst. 9(3), 253–283 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneAustralia
  2. 2.African Institute for Mathematical Sciences (AIMS)Cape TownSouth Africa
  3. 3.Department of Mathematical SciencesStellenbosch UniversityStellenboschSouth Africa

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