Skip to main content
SpringerLink
Log in
Book cover

International Workshop on Engineering Societies in the Agents World

ESAW 2007: Engineering Societies in the Agents World VIII pp 254–269Cite as

Tag Mechanisms Evaluated for Coordination in Open Multi-Agent Systems

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4995))

Abstract

Tags are arbitrary social labels carried by agents. When agents interact preferentially with those sharing the same Tag, groups are formed around similar Tags. This property can be used to achieve desired group coordination by evolving agent’s Tags through a group selection process. In this paper Tags performance is for the first time compared by simulation with alternative mechanisms for coordinated learning in multi-agent systems populations. We target open systems, hence we do not make costly assumptions on agent capabilities (rational or computational). It is a requirement that coordination strategies prove simple to implement and scalable. We build a simulator incorporating competition and cooperation scenarios modeled as one-shot repeated games between agents. Tags prove to be a very good coordination mechanism in both, cooperation building in competitive scenarios and agent behavior coordination in fully cooperative scenarios.

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

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Hales, D. (2000) Cooperation without Space or Memory: Tags, Groups and the Prisoner’s Dilemma. In Moss, S., Davidsson, P. (Eds.) Multi-Agent-Based

    Google Scholar 

  2. Sycara, K.: Multiagent Systems. AI Magazine 10(2), 79–93 (1998)

    Google Scholar 

  3. J. Holland. The effects of labels (Tags) on social interactions. Working Paper Santa Fe Institute 93-10-064 (1993)

    Google Scholar 

  4. Golder, S.A., Huberman, B.A.: The Structure of Collaborative Tagging Systems.Information Dynamics Lab, HP Labs (Visited November 24, 2005)

    Google Scholar 

  5. Riolo, R.: The efects of Tag-mediated selection of partners in evolving populations playing the iterated prisoners dilemma. Nature 414, 441–443 (2000)

    Article  Google Scholar 

  6. McDonald, A., Sen, S.: The Success and Failure of Tag Mediated Evolution of Cooperation. In: Tuyls, K., ’t Hoen, P.J., Verbeeck, K., Sen, S. (eds.) LAMAS 2005. LNCS (LNAI), vol. 3898, pp. 155–164. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  7. Arteconi, S., Hales, D., Babaoglu, O.: Greedy Cheating Liars and the Fools Who Believe Them. In: Brueckner, S.A., Hassas, S., Jelasity, M., Yamins, D. (eds.) ESOA 2006. LNCS (LNAI), vol. 4335. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  8. Hales, D.: From Selfish Nodes to Cooperative Networks – Emergent Link-based Incentives in Peer-to-Peer Networks. In: Proceedings of The Fourth IEEE International Conference on Peer-to-Peer Computing (p2p2004), Zurich, Switzerland, August 25-27, 2004. IEEE Computer Society Press, Los Alamitos (2004)

    Google Scholar 

  9. Hales, D., Patarin, S.: Feature: Computational Sociology for Systems In the Wild: The Case of BitTorrent. IEEE Distributed Systems Online 6(7) (2005)

    Google Scholar 

  10. Hales, D., Babaoglu, O.: Towards Automatic Social Bootstrapping of Peer-to-Peer Protocols. ACM SIGOPS Operating Systems Review (Special Issue on Self-Organizing Systems) 40(3) (July 2006)

    Google Scholar 

  11. Weikum, G., Triantafillou, P., Hales, D., Schindelhauer, C.: Towards Self-Organizing Query Routing and Processing for Peer-to-Peer WebSearch. In: Proceedings of the European Conference on Complex Systems (ECCS 2005), Paris, France, November 14, 2005. i6doc, Belgium (2005) (in press)

    Google Scholar 

  12. Chao, I., Ardaiz, O., Sanguesa, R.: Tag Mechanisms Applied to Open Grid Virtual Organizations Management. In: Anthony, R., Butler, A., Ibrahim, M., Eymann, T., Veit, D.J. (eds.) Proceedings of the Joint Smart Grid Technologies (SGT) and Engineering Emergence for Autonomic Systems (EEAS) Workshop, Dublin, Ireland, pp. 22–29 (2006)

    Google Scholar 

  13. Mollona, E., Hales, D.: Modeling Firm Skill-Set Dynamics as a Complex System. In: Proceedings of the European Conference on Complex Systems (ECCS 2005), Paris, France, November 14, i6doc, Belgium (in press, 2005)

    Google Scholar 

  14. Next Generation Grids Expert Group Report 3, Future for European Grids: GRIDs and Service Oriented Knowledge Utilities

    Google Scholar 

  15. Howley, E., O’Riordan, C.: The Emergence of Cooperation among Agents using Simple Fixed Bias Tagging. In: IEEE Congress on Evolutionary Computation, September 2-5 (2005)

    Google Scholar 

  16. Hales, D.: The Evolution of Specialization in Groups. In: Lindemann, G., Moldt, D., Paolucci, M. (eds.) RASTA 2002. LNCS (LNAI), vol. 2934. Springer, Heidelberg (2004)

    Google Scholar 

  17. The Emergence of Symbiotic Groups Resulting from Skill-Differentiation and Tags, Bruce Edmonds. JASSS 9(1), January 31(2006)

    Google Scholar 

  18. Zohar, A., Rosenschein, J.S.: Using Tags to Evolve Trust and Cooperation Between Groups. In: The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, Utrecht, July 2005, The Netherlands, pp. 1199–1200 (2005)

    Google Scholar 

  19. Floortje Alkemade, D.D.B., van Bragt, J.A.: La Poutré: Stabilization of Tag-mediated interaction by sexual reproduction in an evolutionary agent system. Inf. Sci. 170(1), 101–119 (2005)

    Article  Google Scholar 

  20. Cohen, M., Riolo, R., Axelrod, R.: The emergence of social organization in the Prisoner’s Dilemma: how context-preservation and other factors promote cooperation Santa Fe Institute Working Paper 99-01-002 (1999)

    Google Scholar 

  21. Hamilton, W.D.: Man and Beast: Comparitive Social Behaviour. In: Eisenberg, J.F., Dillon, W.S. (eds.). Smithsonian Press, Washington (1971)

    Google Scholar 

  22. Coalition Formation: Towards Feasible Solutions. Fundamenta Informaticae 63(2-3), 107–124 (2004)

    Google Scholar 

  23. Lerman, K., Shehory, O.: Coalition formation for large-scale electronic markets. In: Proc. of ICMAS 2000, Boston, MA, pp. 167–174 (2000)

    Google Scholar 

  24. Kraus, S., Shehory, O., Taase, G.: Coalition formation with uncertain heterogeneous information. In: Proc. Of AAMAS 2003, Melbourne, Australia, pp. 1–8 (2003)

    Google Scholar 

  25. Axelrod, R.: The Evolution of Cooperation. Science 211(4489), 1390–1396 (1981)

    Article  MathSciNet  Google Scholar 

  26. Nowak, M., Sigmund, K.: A strategy of winstay,lose-shift that outperforms tit-for-tat in the prisoner’sdilemma game. Nature 364, 56–58 (1993)

    Article  Google Scholar 

  27. Shoham, Y., Grenager, T., Powers, R.: Multi-agent reinforcement learning: A critical survey. Tech.rep., Stanford University (2003)

    Google Scholar 

  28. Wakano, J.Y., Yamamura, N.: A Simple Learning Strategy that Realizes Robust Cooperation Better than Pavlov in Iterated Prisoners’ Dilemma. J. Ethology 19, 9–15 (2001)

    Article  Google Scholar 

  29. Watkins, C.: Learning from Delayed Rewards, Thesis, University of Cambidge,England (1989)

    Google Scholar 

  30. de Cote, J.E.M., Lazaric, A., Restelli, M.: Learning to cooperate in multi-agent social dilemmas. In: AAMAS 2006, pp. 783–785 (2006)

    Google Scholar 

  31. Sandholm, T., Lesser, V.: Coalitions Among Computationally Bounded Agents. Artificial Intelligence, special issue on principles of multiagent systems 94(1) (1997)

    Google Scholar 

  32. Willensdorfer, M., Nowak, M.A.: Mutation in evolutionary games can increase average fitness at equilibrium. J. theor. Biol. 237, 355–362 (2005)

    Article  MathSciNet  Google Scholar 

  33. Bowling, M.: Convergence problems of general-sum multia-gent reinforcement learning. In: Proceedings of the Seventeenth International, Conference on Machine Learning, pp. 89–94 (2000)

    Google Scholar 

  34. Durfee, E.H., Rosenschein, J.S.: Distributed Problem Solving and Multi-Agent Systems: Comparisons and Examples. In: Proc. 13th Int’l Distributed Artificial Intelligence Workshop, pp. 94–104 (1994)

    Google Scholar 

  35. Chao, I., Ardaiz, O., Sanguesa, R.: A Group Selection Pattern for agent-based Virtual Organizations coordination in Grids. In: International Conference on Grid computing, High-Performance and Distributed Applications (GADA 2007), Vilamoura, Algarve, Portugal, November 29- 30 (2007)

    Google Scholar 

  36. Chao, I., Ardaiz, O., Sanguesa, R.: A Group Selection Pattern Optimizing Job Scheduling in Decentralized Grid Markets. Poster accepted to the International Conference on Grid computing, High-Performance and Distributed Applications (GADA 2007), Vilamoura, Algarve, Portugal, November 29 - 30 (2007)

    Google Scholar 

  37. Nowak, M.A.: Five rules for the evolution of cooperation. Science 314, 1560–1563 (2006)

    Article  Google Scholar 

  38. Gotts, N.M., Polhill, J.G., Law, A.N.R.: Agent-based simulation in the study of social dilemmas. Artificial Intelligence Review 19, 3–92 (2003)

    Article  Google Scholar 

  39. Eymann, T., Reinicke, M., Streitberger, W., Rana, O., Joita, L., Neumann, D., Schnizler, B., Veit, D., Ardaiz, O., Chacin, P., Chao, I., FreiTag, F., Navarro, L., Catalano, M., Gallegati, M., Giulioni, G., Schiaffino, R.C., Zini, F.: Catallaxy-based Grid Markets. In: Veit, D.J., Eymann, T., Jennings, N.R., Müller, J.P. (eds.) Multiagent and Grid Systems Issue: Smart Grid Technologies & Market Models, vol. 1(4), pp. 297–307 (2005)

    Google Scholar 

  40. Galstyan, A., Czajkowski, K., Lerman, K.: Resource Allocation in the Grid with Learning Agents. Journal of Grid Computing 3(1–2), 91–100 (2005)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Informatics Department, Polytechnic University of Catalonia, Spain

    Isaac Chao & Ramon Sanguesa

  2. Informatics Department, Public University of Navarra, Spain

    Oscar Ardaiz

Authors
  1. Isaac Chao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Oscar Ardaiz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ramon Sanguesa
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Alexander Artikis Gregory M. P. O’Hare Kostas Stathis George Vouros

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chao, I., Ardaiz, O., Sanguesa, R. (2008). Tag Mechanisms Evaluated for Coordination in Open Multi-Agent Systems. In: Artikis, A., O’Hare, G.M.P., Stathis, K., Vouros, G. (eds) Engineering Societies in the Agents World VIII. ESAW 2007. Lecture Notes in Computer Science(), vol 4995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87654-0_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-87654-0_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87653-3

  • Online ISBN: 978-3-540-87654-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation