Skip to main content

Emergent Specialization in Swarm Systems

  • Conference paper
  • First Online:
Intelligent Data Engineering and Automated Learning — IDEAL 2002 (IDEAL 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2412))

  • 1796 Accesses

Abstract

Distributed learning is the learning process of multiple autonomous agents in a varying environment, where each agent has only partial information about the global task. In this paper, we investigate the influence of different reinforcement signals (local and global) and team diversity (homogeneous and heterogeneous agents) on the learned solutions. We compare the learned solutions with those obtained by systematic search in a simple case study in which pairs of agents have to collaborate in order to solve the task without any explicit communication. The results show that policies which allow teammates to specialize find an adequate diversity of the team and, in general, achieve similar or better performances than policies which force homogeneity. However, in this specific case study, the achieved team performances appear to be independent of the locality or globality of the reinforcement signal.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

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.

Similar content being viewed by others

References

  1. Bonabeau, E., Dorigo, M., Théraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York (1999)

    MATH  Google Scholar 

  2. Parrish, J.K., Hamner, W.M., eds.: Animal Groups in Three Dimensions. Cambridge University Press, New York (1997)

    Google Scholar 

  3. Martinoli, A., Mondada, F.: Collective and cooperative group behaviours: Biologically inspired experiments in robotics. In Khatib, O., Salisbury, J.K., eds.: Proceedings of the Fourth International Symposium on Experimental Robotics (1995). Lecture Notes in Control and Information Sciences, Vol. 223. Springer-Verlag, Berlin (1997) 3–10

    Google Scholar 

  4. Ijspeert, A.J., Martinoli, A., Billard, A., Gambardella, L.M.: Collaboration through the exploitation of local interactions in autonomous collective robotics: The stick pulling experiment. Autonomous Robots 11 (2001) 149–171

    Article  MATH  Google Scholar 

  5. Lerman, K., Galstyan, A., Martinoli, A., Ijspeert, A.J.: A macroscopic analytical model of collaboration in distributed robotic systems. Artificial Life 7 (2001) 375–393

    Article  Google Scholar 

  6. Versino, C., Gambardella, L.M.: Learning real team solutions. In Weiß, G., ed.: Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Artificial Intelligence, Vol. 1221. Springer-Verlag, Berlin (1997) 40–61

    Google Scholar 

  7. Murciano, A., del R. Millán, J., Zamora, J.: Specialization in multi-agent systems through learning. Biological Cybernetics 76 (1997) 375–382

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Li, L., Martinoli, A., Abu-Mostafa, Y.S. (2002). Emergent Specialization in Swarm Systems. In: Yin, H., Allinson, N., Freeman, R., Keane, J., Hubbard, S. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2002. IDEAL 2002. Lecture Notes in Computer Science, vol 2412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45675-9_43

Download citation

  • DOI: https://doi.org/10.1007/3-540-45675-9_43

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44025-3

  • Online ISBN: 978-3-540-45675-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics