Skip to main content
SpringerLink
Log in

Convention Emergence in Partially Observable Topologies

  • Conference paper
  • First Online:
Autonomous Agents and Multiagent Systems (AAMAS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10642))

Included in the following conference series:

Abstract

In multi-agent systems it is often desirable for agents to adhere to standards of behaviour that minimise clashes and wasting of (limited) resources. In situations where it is not possible or desirable to dictate these standards globally or via centralised control, convention emergence offers a lightweight and rapid alternative. Placing fixed strategy agents within a population, whose interactions are constrained by an underlying network, has been shown to facilitate faster convention emergence with some degree of control. Placing these fixed strategy agents at topologically influential locations (such as high-degree nodes) increases their effectiveness. However, finding such influential locations often assumes that the whole network is visible or that it is feasible to inspect the whole network in a computationally practical time, a fact not guaranteed in many real-world scenarios. We present an algorithm, PO-Place, that finds influential nodes given a finite number of network observations. We show that PO-Place finds sets of nodes with similar reach and influence to the set of high-degree nodes and we then compare the performance of PO-Place to degree placement for convention emergence in several real-world topologies.

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

Access this chapter

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 EPUB and 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

References

  1. Borgs, C., Brautbar, M., Chayes, J., Khanna, S., Lucier, B.: The power of local information in social networks. In: Goldberg, P.W. (ed.) WINE 2012. LNCS, vol. 7695, pp. 406–419. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35311-6_30

    Chapter  Google Scholar 

  2. Brautbar, M., Kearns, M.J.: Local algorithms for finding interesting individuals in large networks. In: Proceedings of Innovation in Computer Science, pp. 188–199 (2010)

    Google Scholar 

  3. Chen, D.-B., Xiao, R., Zeng, A.: Predicting the evolution of spreading on complex networks. Sci. Rep. 4, 6108 (2014)

    Article  Google Scholar 

  4. Chen, W., Wang, Y., Yang, S.: Efficient influence maximization in social networks. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 199–208 (2009)

    Google Scholar 

  5. Delgado, J.: Emergence of social conventions in complex networks. Artif. Intell. 141(1–2), 171–185 (2002)

    Article  MathSciNet  Google Scholar 

  6. Delgado, J., Pujol, J.M., Sangüesa, R.: Emergence of coordination in scale-free networks. Web Intell. Agent Syst. 1(2), 131–138 (2003)

    Google Scholar 

  7. Franks, H., Griffiths, N., Anand, S.S.: Learning agent influence in MAS with complex social networks. Auton. Agents Multi-Agent Syst. 28(5), 836–866 (2014)

    Article  Google Scholar 

  8. Franks, H., Griffiths, N., Jhumka, A.: Manipulating convention emergence using influencer agents. Auton. Agents Multi-Agent Syst. 26(3), 315–353 (2013)

    Article  Google Scholar 

  9. Griffiths, N., Anand, S.S.: The impact of social placement of non-learning agents on convention emergence. In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, pp. 1367–1368 (2012)

    Google Scholar 

  10. Kandori, M.: Social norms and community enforcement. Rev. Econ. Stud. 59(1), 63–80 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  11. Kittock, J.: Emergent conventions and the structure of multi-agent systems. In: Lectures in Complex Systems: Proceedings of the 1993 Complex Systems Summer School, pp. 507–521 (1995)

    Google Scholar 

  12. Leskovec, J., Krevl, A.: SNAP Datasets: Stanford large network dataset collection, June 2014. http://snap.stanford.edu/data

  13. Marchant, J., Griffiths, N., Leeke, M.: Convention emergence and influence in dynamic topologies. In: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, pp. 1785–1786 (2015)

    Google Scholar 

  14. Marchant, J., Griffiths, N., Leeke, M., Franks, H.: Destabilising conventions using temporary interventions. In: Ghose, A., Oren, N., Telang, P., Thangarajah, J. (eds.) COIN 2014. LNCS (LNAI), vol. 9372, pp. 148–163. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25420-3_10

    Chapter  Google Scholar 

  15. Mihara, S., Tsugawa, S., Ohsaki, H.: Influence maximization problem for unknown social networks. In: Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 1539–1546 (2015)

    Google Scholar 

  16. Pei, S., Tang, S., Zheng, Z.: Detecting the influence of spreading in social networks with excitable sensor networks. PloS One 10(5), e0124848 (2015)

    Article  Google Scholar 

  17. Salazar, N., Rodriguez-Aguilar, J.A., Arcos, J.L.: Robust coordination in large convention spaces. AI Commun. 23(4), 357–372 (2010)

    MathSciNet  Google Scholar 

  18. Savarimuthu, B.T.R., Arulanandam, R., Purvis, M.: Aspects of active norm learning and the effect of lying on norm emergence in agent societies. In: Kinny, D., Hsu, J.Y., Governatori, G., Ghose, A.K. (eds.) PRIMA 2011. LNCS (LNAI), vol. 7047, pp. 36–50. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25044-6_6

    Chapter  Google Scholar 

  19. Sen, S., Airiau, S.: Emergence of norms through social learning. In: Proceedings of the 20th International Joint Conference on Artifical Intelligence, pp. 1507–1512 (2007)

    Google Scholar 

  20. Villatoro, D., Sabater-Mir, J., Sen, S.: Social instruments for robust convention emergence. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence, pp. 420–425 (2011)

    Google Scholar 

  21. Villatoro, D., Sen, S., Sabater-Mir, J.: Topology and memory effect on convention emergence. In: Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, pp. 233–240 (2009)

    Google Scholar 

  22. Walker, A., Wooldridge, M.: Understanding the emergence of conventions in multi-agent systems. In: International Conference on Multi-Agent Systems, pp. 384–389 (1995)

    Google Scholar 

  23. Wang, X., Su, Y., Zhao, C., Yi, D.: Effective identification of multiple influential spreaders by DegreePunishment. Phys. A: Stat. Mech. Appl. 461, 238–247 (2016)

    Article  Google Scholar 

  24. Young, H.P.: The economics of convention. J. Econ. Perspect. 10(2), 105–122 (1996)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Warwick, Coventry, UK

    James Marchant & Nathan Griffiths

Authors
  1. James Marchant
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nathan Griffiths
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to James Marchant .

Editor information

Editors and Affiliations

  1. University of Central Florida, Orlando, Florida, USA

    Gita Sukthankar

  2. IIIA-CSIC, Bellaterra, Spain

    Juan A. Rodriguez-Aguilar

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Marchant, J., Griffiths, N. (2017). Convention Emergence in Partially Observable Topologies. In: Sukthankar, G., Rodriguez-Aguilar, J. (eds) Autonomous Agents and Multiagent Systems. AAMAS 2017. Lecture Notes in Computer Science(), vol 10642. Springer, Cham. https://doi.org/10.1007/978-3-319-71682-4_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-71682-4_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71681-7

  • Online ISBN: 978-3-319-71682-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation