Skip to main content

An Environment-Based Methodology to Design Reactive Multi-agent Systems for Problem Solving

  • Conference paper
Book cover Environments for Multi-Agent Systems II (E4MAS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3830))

Included in the following conference series:

Abstract

Even if the multi-agent paradigm has been evolving for fifteen years, the development of concrete methods for problem solving remains a major challenge. This paper focuses on reactive multi-agent systems because they provide interesting properties such as adaptability and robustness. In particular, the role of the environment, which is effectively where the system computes and communicates, is studied. From this analysis a methodology to design or engineer reactive systems is introduced. Our approach is based on the representation of the problem’s constraints considered as perturbations to stabilize. Agents are then defined, in the second place, as a means of regulating the perturbations. Finally, the relevancy of our proposition is justified through the development of two solving models applied to real and complex problems.

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Arkin, R.C.: Behavior Based Robotics. MIT Press, Cambridge (1998)

    Google Scholar 

  2. Balch, T.: Hierarchic Social Entropy: An Information Theoretic Measure of Robot Group Diversity. Atonomous Robots 8(3) (July 2000)

    Google Scholar 

  3. Bernon, C., Gleizes, M.-P., Peyruqueou, S., Picard, G.: ADELFE, a methodology for adaptative multi-agent systems engineering. In: Petta, P., Tolksdorf, R., Zambonelli, F. (eds.) ESAW 2002. LNCS, vol. 2577, pp. 156–169. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  4. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Nature to Artificial Systems. Oxford University Press, New York (1999)

    MATH  Google Scholar 

  5. Buffet, O., Dutech, A., Charpillet, F.: Adaptive Combination of Behaviors in an Agent. In: Proceedings of the Fiveteenth European Conference on Artificial Intelligence (ECAI 2002), Lyon, France, pp. 48–52 (2002)

    Google Scholar 

  6. Camazine, S., Deneubourg, J.L., Franks, N.R., Sneyd, J., Theraulaz, G., Bonabeau, E.: Self-Organization in Biological Systems. Princeton studies in complexity. Princeton University Press, Princeton (2001)

    MATH  Google Scholar 

  7. Colorni, A., Dorigo, M., Maniezzo, V.: Distributed Optimization by Ant Colonies. In: Proceedings of ECAL 1991, European conference on artificial life, Paris, pp. 134–142. Elsevier, Amsterdam (1991)

    Google Scholar 

  8. Drogoul, A., Ferber, J., Jacopin, E.: Pengi: Applying Eco-Problem-Solving for Behavior Modelling in an Abstract Eco-System. In: Modelling and Simulation: Proceedings of ESM 1991, Simulation Councils, Copenhague, pp. 337–342 (1991)

    Google Scholar 

  9. Drogoul, A., Ferber, J.: From Tom-Thumb to the Dockers: Some Experiments with Foraging Robots. In: From Animals to Animats II, pp. 451–459. MIT Press, Cambridge (1993)

    Google Scholar 

  10. Drogoul, A., Dubreuil, C.: A Distributed Approach to N-Puzzle Solving. In: Proceedings of the Distributed Artificial Intelligence Workshop, Seattle (United-States) (1993)

    Google Scholar 

  11. Ealet, F., Collin, B., Sella, G., Garbay, C.: Multi-agent architecture for scene interpretation. In: SPIE 2000 on Enhanced and synthetic vision, Orlando, USA (2000)

    Google Scholar 

  12. Chapelle, J., Simonin, O., Ferber, J.: How Situated Agents can Learn to Cooperate by Monitoring their Neighbors’ Satisfaction. In: Proc. 15th European Conference on Artificial Intelligence, pp. 68–72 (2002)

    Google Scholar 

  13. Ferber, J., Jacopin, E.: The framework of ECO-problem solving. In: Demazeau, Y., Müller, J.-P. (eds.) Decentralized AI 2. North-Holland, Amsterdam (1991)

    Google Scholar 

  14. Ferber, J.: Multi-Agent System: An Introduction to Distributed Artificial Intelligence. Addison Wesley Longman, Harlow (1999)

    Google Scholar 

  15. Ferrand, N., Demazeau, Y., Baeijs, C.: Systèmes multi-agents réactifs pour la résolution de problèmes spatialisés. Revue d‘Intelligence Artificielle, Numéro Spécial sur l‘IAD et les SMA 12(1), 37–72 (1998)

    Google Scholar 

  16. Gechter, F., Charpillet, F.: Vision Based Localisation for a Mobile Robot. In: 12th IEEE International Conference on Tools with Artificial Intelligence ICTAI 2000, pp. 229–236 (2000)

    Google Scholar 

  17. Gechter, F., Chevrier, V., Charpillet, F.: A Reactive Multi-Agent System for Localization and Tracking in Mobile. In: 16th IEEE International Conference on Tools with Artificial Intelligence - ICTAI 2004, pp. 431–435 (2004)

    Google Scholar 

  18. Gechter, F., Chevrier, V., Charpillet, F.: Localizing and Tracking Targets with a Reactive Multi-Agent System. In: Second European Workshop on Multi-Agent Systems - EUMAS 2004 (2004)

    Google Scholar 

  19. Hull, C.: Principles of Behavior. Appleton-Century-Crofts, New York (1943)

    Google Scholar 

  20. Kanada, Y., Hirokawa, M.: Stochastic Problem Solving by Local Computation based on Self-Organization Paradigm. In: IEEE 27th Hawaii International Conference on System Sciences, pp. 82–91 (1994)

    Google Scholar 

  21. Kennedy, J., Eberhart, R.C.: Swarm Intelligence. Morgan Kaufmann Publisher, San Francisco (2001)

    Google Scholar 

  22. Khatib, O.: Real-Time Obstacle Avoidance for Manipulators and Mobile Robots. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 500–505 (1985)

    Google Scholar 

  23. Kwok, C., Fox, D., Meila, M.: Real-Time Particle Filters. Proceedings of the IEEE 92(2) (2004); Special Issue on Sequential State Estimation

    Google Scholar 

  24. Lucidarme, P., Simonin, O., Liegeois, A.: Implementation and Evaluation of a Satisfaction/Altruism Based Architecture for Multi-Robot Systems. In: Proc. IEEE Int. Conf. on Robotics and Automation, pp. 1007–1012 (2002)

    Google Scholar 

  25. Mamei, M., Zambonelli, F.: Motion Coordination in the Quake 3 Arena Environment: a Field-based Approach. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2004. LNCS (LNAI), vol. 3374, pp. 264–278. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  26. Mamei, M., Zambonelli, F.: Programming stigmergic coordination with the TOTA middleware. In: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, pp. 415–422. ACM Press, New York (2005)

    Chapter  Google Scholar 

  27. Mataric, M.J.: Designing and Understanding Adaptative Group Behavior. Adaptive Behavior 4(1), 51–80 (1995)

    Article  Google Scholar 

  28. Müller, J.-P., Parunak, H.V.D.: Multi-Agent systems and manufacturing. In: IFAC/INCOM 1998, Nancy/Metz (1998)

    Google Scholar 

  29. Jean, M.R.: Emergence et SMA. In: La Colle-sur-Loup, Quinqueton, Thomas, Trousse (eds.) 5eme Journées Francophones sur l’Intelligence Artificielle Distribuée et les Systèmes Multi-Agents, AFCET, AFIA, pp. 323–342 (1997)

    Google Scholar 

  30. Padgham, L., Winikoff, M.: Promotheus: A Methodology for Developing Intelligent Agents. In: Giunchiglia, F., Odell, J.J., Weiss, G. (eds.) AOSE 2002. LNCS, vol. 2585, pp. 174–185. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  31. Parunak, H.V.D.: Go to the Ant: Engineering Principles from Natural Agent Systems. Annals of Operations Research 75, 69–101 (1997)

    Article  MATH  Google Scholar 

  32. Parunak, H.V.D., Brueckner, S.: Entropy and Self-Organization in Multi-Agent Systems. In: Fifth International Conference on Autonomous Agents, pp. 124–130 (2001)

    Google Scholar 

  33. Parunak, H.V.D., Brueckner, S., Sauter, J.: Digital Pheromones for Coordination of Unmanned Vehicles. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2004. LNCS (LNAI), vol. 3374, pp. 246–263. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  34. Ramos, V., Almeida, F.: Artificial Ant Colonies in Digital Image Habitats. In: A Mass Behaviour Effect Study on Pattern Recognition ANTS 2000, Brussels Belgique, pp. 113–116 (2000)

    Google Scholar 

  35. Simonin, O., Ferber, J.: Modeling Self Satisfaction and Altruism to handle Action Selection and Reactive Cooperation. In: Proceedings SAB 2000 The Sixth International Conference on the Simulation of Adaptative Behavior, vol. 2, pp. 314–323 (2000)

    Google Scholar 

  36. Simonin, O., Liégeois, A., Rongier, P.: An Architecture for Reactive Cooperation of Mobile Distributed Robots. In: Parker, L.E., Bekey, G., Barhen, J. (eds.) DARS 2000 5th International Symposium on Distributed Autonomous Robotic Systems in Distributed Autonomous Robotic Systems 4, pp. 35–44. Springer, Heidelberg (2000)

    Google Scholar 

  37. Simonin, O.: Construction of Numerical Potential Fields with Reactive Agents. In: AAMAS 2005 proceedings The Fourth International Joint Conference on Autonomous Agents and Multi Agent System, ACM-SIGART, pp. 1351–1352 (2005)

    Google Scholar 

  38. Steels, L.: Cooperation between distributed agents through self-organization. In: Workshop on Multi-Agent Cooperation, pp. 3–13. North Holland, Cambridge (1989)

    Google Scholar 

  39. Weiner, N.: Cybernetics, or Control and Communication in Animals and Machines. Wiley, New York (1948)

    Google Scholar 

  40. Welch, G., Bishop, G.: An introduction to the kalman filter. Technical Report TR 95-041, Computer Science, University of North California at Chapel Hill, Chapel Hill, NC (2003)

    Google Scholar 

  41. Weyns, D., Steegmans, E., Holvoet, T.: Towards Active Perception. Situated Multi-Agent Systems Applied Artificial Intelligence 18(9-10), 867–883 (2004)

    Article  Google Scholar 

  42. Weyns, D., Parunak, V., Michel, F., Holvoet, T., Ferber, J.: Environments for Multiagent Systems, State of the art and research challenges. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2004. LNCS (LNAI), vol. 3374, pp. 1–47. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  43. Wooldridge, M., Jennings, N.R., Kinny, D.: The Gaia Methodology for Agent-Oriented Analysis and Design. Autonomous Agents and Multi-Agent Systems 3, 285–312 (2000)

    Article  Google Scholar 

  44. Zambonelli, F., Jennings, N.R., Wooldridge, M.: Developing multiagent systems: The Gaia Methodology. Transactions on Software Engineering and Methodology 3(12) (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Simonin, O., Gechter, F. (2006). An Environment-Based Methodology to Design Reactive Multi-agent Systems for Problem Solving. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds) Environments for Multi-Agent Systems II. E4MAS 2005. Lecture Notes in Computer Science(), vol 3830. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11678809_3

Download citation

  • DOI: https://doi.org/10.1007/11678809_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32614-4

  • Online ISBN: 978-3-540-32615-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics