Autonomous Agents and Multi-Agent Systems

, Volume 25, Issue 3, pp 419–424 | Cite as

A brief introduction to agent mining

Article

Abstract

Agent mining is an emerging interdisciplinary area that integrates multiagent systems, data mining and knowledge discovery, machine learning and other relevant areas. It brings new opportunities to tackling issues in relevant fields more efficiently by engaging together the individual technologies. It will also bring about symbiosis and symbionts that combine advantages from the corresponding constituent systems. In this editorial, we briefly introduce the concept of agent mining, the main areas of research, and challenges and opportunities in agent mining. Finally, we give an overview of the papers in this special issue.

Keywords

Agent mining Multiagent system Data mining Knowledge discovery Machine learning 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Agent Mining Special Interest Group. www.agentmining.org.
  2. 2.
    Cao, L. (Ed.). (2009) Data mining and multiagent integration. Springer, BerlinGoogle Scholar
  3. 3.
    Cao L., Zhang Z., Gorodetsky V., Zhang C. (2008) Editor’s introduction: Interaction between agents and data mining. International Journal of Intelligent Information and Database Systems, Interscience 2(1): 1–5Google Scholar
  4. 4.
    Cao L., Dai R., Zhou M. (2009a) Metasynthesis: M-space, M-interaction and M-computing for open complex giant systems. IEEE Transactions On Systems, Man, and Cybernetics: Part A 39(5): 1007–1021CrossRefGoogle Scholar
  5. 5.
    Cao, L., Gorodetsky, V., Liu, J., Weiss, G., & Yu, P. S. (Eds.) (2009b). Agents and data mining interaction. LNCS (Vol. 5680). Berlin: Springer.Google Scholar
  6. 6.
    Cao L., Gorodetsky V., Mitkas P. (2009c) Agent mining: The synergy of agents and data mining. IEEE Intelligent Systems 24(3): 64–72CrossRefGoogle Scholar
  7. 7.
    Cao, L., Bazzan, A., Gorodetsky, V., Mitkas, P., Weiss, G., & Yu, P. S. (Eds.) (2010). Agents and data mining interaction. LNCS (Vol. 5980). Berlin: Springer.Google Scholar
  8. 8.
    Cao, L., Bazzan, A., Symeonidis, A., Gorodetsky, V., Weiss, G., & Yu, P. S. (Eds.) (2011). Agents and data mining interaction. LNCS (Vol. 7103). Berlin: Springer.Google Scholar
  9. 9.
    Claus, C., & Boutilier, C. (1998). The dynamics of reinforcement learning in cooperative multi-agent systems. In Proceedings of the 15th international conference on artificial intelligence (pp 746–752).Google Scholar
  10. 10.
    Davies W. (1994). Agent-based data-mining. http://logic.stanford.edu/~davies/Papers/first-year-report.ps.
  11. 11.
    Giannella, C., Bhargava, R., & Kargupta, H. (2004). Multi-agent Systems and distributed data mining. Lecture Notes in Computer Science 1–15.Google Scholar
  12. 12.
    Gorodetsky, V., Liu, J., & Skormin, V. (Eds.) (2005). Autonomous intelligent systems: Multi-agents and data mining. LNCS (Vol. 3505). Berlin: Springer.Google Scholar
  13. 13.
    Gorodetsky, V., Zhang, C., Skormin, V., & Cao, L. (Eds.) (2007). Autonomous intelligent systems: Multi-agents and data mining. LNCS (Vol. 4476). Berlin: Springer.Google Scholar
  14. 14.
    Hu J., Wellman M. P. (2003) Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research 4: 1039–1069MathSciNetGoogle Scholar
  15. 15.
    Mohammadian M. (2003) Intelligent agents for data mining and information retrieval. Idea Group Publishing, HersheyCrossRefGoogle Scholar
  16. 16.
    Singh, S. P., Kearns, M. J., & Mansour, Y. (2000). Nash convergence of gradient dynamics in general-sum games. In UAI 00: Proceedings of the 16th conference on uncertainty in articial intelligence (pp 541–548).Google Scholar
  17. 17.
    Symeonidis A., Mitkas P. (2005) Agent intelligence through data mining. Springer, BerlinMATHGoogle Scholar
  18. 18.
    Tozicka, J., Rovatsos, M., & Pechoucek, M. (2007). A framework for agent-based distributed machine learning and data mining, In Proceedings of the 6th international joint conference on autonomous agents and multiagent systems (pp 1–8).Google Scholar
  19. 19.
    Tuyls, K., & Weiss, G. (2012). Multiagent learning: Basics, challenges, and prospects, AI Magazine 33.Google Scholar
  20. 20.
    Weiss, G. A. (1998). Multiagent perspective of parallel and distributed machine learning. In Proceedings of Agents ’98 (pp 226–230).Google Scholar

Copyright information

© The Author(s) 2012

Authors and Affiliations

  1. 1.Advanced Analytics InstituteUniversity of TechnologySydneyAustralia
  2. 2.Department of Knowledge EngineeringMaastricht UniversityMaastrichtThe Netherlands
  3. 3.Department of Computer ScienceUniversity of Illinois at ChicagoChicagoUSA

Personalised recommendations