Monitoring Group Behavior in Goal-Directed Agents Using Co-efficient Plan Observation

  • Jan Sudeikat
  • Wolfgang Renz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4405)


Purposeful, time– and cost–oriented engineering of Multi–Agent Systems (MAS) requires developers to understand the relationships between the numerous behaviors exhibited by individual agents and the resulting global MAS behavior. While development methodologies have drawn attention to verification and debugging of single agents, software producing organizations need to validate that the MAS, as a cooperative system exhibiting group behavior, is behaving as expected. Recent research has proposed techniques to infer mathematical descriptions of macroscopic MAS behavior from microscopic reactive and adaptive agent behaviors. In this paper, we show how similar descriptions can be adjusted to MAS composed of goal–directed agent architectures. We argue that goal–hierarchies found in Requirements Engineering and Belief Desire Intention (BDI) architectures are suitable data structures to facilitate a stochastic modeling approach. To enable monitoring of agent behaviors, we introduce an enhancement to the well-known capability concept for BDI agents. So-called co–efficient capabilities are a novel approach to modularize crosscutting concerns in BDI agent implementations. A case study applies co–efficient plan observation to exemplify and confirm our modeling approach.


Multiagent System Agent Behavior Agent Type Average Occupation Number Initial Delay Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Jennings, N.R.: Building complex, distributed systems: the case for an agent-based approach. Comms. of the ACM 44(4), 35–41 (2001)CrossRefMathSciNetGoogle Scholar
  2. 2.
    Wolf, T.D., Holvoet, T.: Emergence and self-organisation: a statement of similarities and differences. In: Proc. of ESOA’04, pp. 96–110 (2004)Google Scholar
  3. 3.
    Guerin, S.: Peeking into the black-box: Some art and science to visualizing agent-based models. In: Proceedings of the 2004 Winter Simulation Conference (2004)Google Scholar
  4. 4.
    Ndumu, D.T., et al.: Visualising and debugging distributed multi-agent systems. In: Proc. of AGENTS ’99, pp. 326–333 (1999)Google Scholar
  5. 5.
    Szekely, P., Rogers, C.M., Frank, M.: Interfaces for understanding multi-agent behavior. In: Proc. of the 6th int. conf. on Intel. user interfaces, pp. 161–166 (2001)Google Scholar
  6. 6.
    Lam, D.N., Barber, K.S.: Comprehending agent software. In: Proc. of the 4th int. joint conf. on autonomous agents and multiagent systems (AAMAS ’05) (2005)Google Scholar
  7. 7.
    Yamins, D.: Towards a theory of ”local to global” in distributed multi-agent systems (i). In: Proc. of AAMAS ’05, pp. 183–190. ACM Press, New York (2005)CrossRefGoogle Scholar
  8. 8.
    Bratman, M.: Intentions, Plans, and Practical Reason. Harvard Univ. Press, Cambridge (1987)Google Scholar
  9. 9.
    Rao, A.S., Georgeff, M.P.: BDI-agents: from theory to practice. In: Proceedings of the First Int. Conference on Multiagent Systems (1995)Google Scholar
  10. 10.
    Georgeff, M.P., Lansky, A.L.: Reactive reasoning and planning: an experiment with a mobile robot. In: Proc. of AAAI 87, Seattle, Washington, pp. 677–682 (1987)Google Scholar
  11. 11.
    Pokahr, A., Braubach, L., Lamersdorf, W.: A flexible BDI architecture supporting extensibility. In: The 2005 IEEE/WIC/ACM Int. Conf. on IAT-2005 (2005)Google Scholar
  12. 12.
    Bresciani, P., et al.: Tropos: An agent-oriented software development methodology. Journal of Autonomous Agents and Multi-Agent Systems (2004)Google Scholar
  13. 13.
    Padgham, L., Winikoff, M.: Developing Intelligent Agent Systems: A Practical Guide. John Wiley and Sons, Chichester (2004)Google Scholar
  14. 14.
    Lerman, K., Galstyan, A.: A general methodology for mathematical analysis of multiagent systems. USC Inf. Sciences Tech.l Report ISI-TR-529 (2001)Google Scholar
  15. 15.
    Lerman, K., Galstyan, A.: Automatically modeling group behavior of simple agents. In: Agent Modeling Workshop, AAMAS-04, New York, NY (2004)Google Scholar
  16. 16.
    Lerman, K., et al.: Analysis of dynamic task allocation in multi-robot systems. Int. J. of Robotics Research 25, 225–241 (2006)CrossRefGoogle Scholar
  17. 17.
    Parnas, D.L.: On the criteria to be used in decomposing systems into modules. Commun. ACM 15, 1053–1058 (1972)CrossRefGoogle Scholar
  18. 18.
    Elrad, T., Filman, R.E., Bader, A.: Aspect-oriented programming: Introduction. Commun. ACM 44, 29–32 (2001)CrossRefGoogle Scholar
  19. 19.
    Lamersdorf, W., Braubach, L., Pokahr, A.: Extending the Capability Concept for Flexible BDI Agent Modularization. In: Bordini, R.H., et al. (eds.) PROMAS 2005. LNCS (LNAI), vol. 3862, pp. 139–155. Springer, Heidelberg (2006)Google Scholar
  20. 20.
    Busetta, P., et al.: Structuring BDI agents in functional clusters. In: Jennings, N.R. (ed.) ATAL 1999. LNCS, vol. 1757, pp. 277–289. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  21. 21.
    Lerman, K., Martinoli, A., Galstyan, A.: A Review of Probabilistic Macroscopic Models for Swarm Robotic Systems. In: Şahin, E., Spears, W.M. (eds.) Swarm Robotics 2004. LNCS, vol. 3342, pp. 143–152. Springer, Heidelberg (2005)Google Scholar
  22. 22.
    Van Kampen, N.G.: Stochastic Processes in Physics and Chemistry. Elsevier, Amsterdam (2001)zbMATHGoogle Scholar
  23. 23.
    van Lamsweerde, A.: Goal-oriented requirements engineering: A guided tour. In: Proc. RE’01 - Int. Joint Conference on Requirements Engineering (2001)Google Scholar
  24. 24.
    Van Lamsweerde, A.: Goal-oriented requirements engineering: A roundtrip from research to practice. In: Proc. of RE’04 (Invited Keynote Paper), pp. 4–8 (2004)Google Scholar
  25. 25.
    Lamersdorf, W., et al.: Goal Representation for BDI Agent Systems. In: Bordini, R.H., et al. (eds.) PROMAS 2004. LNCS (LNAI), vol. 3346, pp. 44–65. Springer, Heidelberg (2005)Google Scholar
  26. 26.
    Lamersdorf, W., et al.: Augmenting BDI Agents with Deliberative Planning Techniques. In: Bordini, R.H., et al. (eds.) PROMAS 2006. LNCS (LNAI), vol. 4411, pp. 113–127. Springer, Heidelberg (2007)Google Scholar
  27. 27.
    Pokahr, A., Braubach, L., Lamersdorf, W.: A bdi architecture for goal deliberation. In: Proc. of AAMAS ’05, pp. 1295–1296 (2005)Google Scholar
  28. 28.
    Simari, G., Parsons, S.: On the relationship between mdps and the bdi architecture. In: Proc. of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (2006)Google Scholar
  29. 29.
    Padgham, L., Winikoff, M., Poutakidis, D.: Adding debugging support to the prometheus methodology. Engin. Applications of Art. Intel. 18, 173–190 (2005)CrossRefGoogle Scholar
  30. 30.
    Kiczales, G., et al.: Aspect-Oriented Programming. In: Aksit, M., Matsuoka, S. (eds.) ECOOP 1997. LNCS, vol. 1241, pp. 220–242. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  31. 31.
    Padgham, L., Lambrix, P.: Agent capabilities: Extending bdi theory. In: Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence, pp. 68–73 (2000)Google Scholar
  32. 32.
    Pokahr, A., et al.: Jadex Tool Guide - Release 0.93. Distributed Systems Group, University of Hamburg, Germany (2005)Google Scholar
  33. 33.
    Garcia, A., et al.: Engineering multi-agent systems with aspects and patterns. Journal of the Brazilian Computer Society 8, 57–72 (2002)CrossRefGoogle Scholar
  34. 34.
    Robbes, R., Bouraqadi, N., Stinckwich, S.: An aspect-based multi-agent system. In: Research Track of the ESUG 2004 Smalltalk Conference, öthen (Anhalt), Germany (2004)Google Scholar
  35. 35.
    de Lucena, C.J.P., et al.: Aspects in Agent-Oriented Software Engineering: Lessons Learned. In: Müller, J.P., Zambonelli, F. (eds.) AOSE 2005. LNCS, vol. 3950, pp. 231–247. Springer, Heidelberg (2006)Google Scholar
  36. 36.
    Garcia, A., Chavez, C., Choren, R.: Enhancing agent–oriented models with aspects. In: AAMAS ’06: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems, ACM Press, New York (2006)Google Scholar
  37. 37.
    Garcia, A., Chavez, C., Choren, R.: An aspect–oriented modeling framework for designing multi–agent systems. In: Padgham, L., Zambonelli, F. (eds.) AOSE VII / AOSE 2006. LNCS, vol. 4405, Springer, Heidelberg (2007)CrossRefGoogle Scholar
  38. 38.
    Ferber, J.: Multi-Agent Systems. Addison-Wesley, Reading (1999)Google Scholar
  39. 39.
    Sudeikat, J., Renz, W.: On the redesign of self–organizing multi–agent systems. International Transactions on Systems Science and Applications (Special Issue on SOAS’06) 2, 81–89 (2006)Google Scholar
  40. 40.
    Sudeikat, J., et al.: Validation of bdi agents. In: Bordini, R.H., et al. (eds.) PROMAS 2006. LNCS (LNAI), vol. 4411, Springer, Heidelberg (2007)CrossRefGoogle Scholar
  41. 41.
    Sudeikat, J., Renz, W.: Mesoscopic Modeling of Emergent Behavior - A Self-organizing Deliberative Minority Game. In: Brueckner, S.A., et al. (eds.) ESOA 2005. LNCS (LNAI), vol. 3910, pp. 167–181. Springer, Heidelberg (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jan Sudeikat
    • 1
  • Wolfgang Renz
    • 1
  1. 1.Multimedia Systems Lab, Faculty of Engineering and Computer Science, Hamburg University of Applied Sciences, Berliner Tor 7, 20099 HamburgGermany

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