Skip to main content
Log in

A brief introduction to agent mining

  • Published:
Autonomous Agents and Multi-Agent Systems Aims and scope Submit manuscript


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.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.


  1. Agent Mining Special Interest Group.

  2. Cao, L. (Ed.). (2009) Data mining and multiagent integration. Springer, Berlin

    Google Scholar 

  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): 1–5

    Google Scholar 

  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): 1007–1021

    Article  Google Scholar 

  5. Cao, L., Gorodetsky, V., Liu, J., Weiss, G., & Yu, P. S. (Eds.) (2009b). Agents and data mining interaction. LNCS (Vol. 5680). Berlin: Springer.

  6. Cao L., Gorodetsky V., Mitkas P. (2009c) Agent mining: The synergy of agents and data mining. IEEE Intelligent Systems 24(3): 64–72

    Article  Google Scholar 

  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.

  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.

  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).

  10. Davies W. (1994). Agent-based data-mining.

  11. Giannella, C., Bhargava, R., & Kargupta, H. (2004). Multi-agent Systems and distributed data mining. Lecture Notes in Computer Science 1–15.

  12. Gorodetsky, V., Liu, J., & Skormin, V. (Eds.) (2005). Autonomous intelligent systems: Multi-agents and data mining. LNCS (Vol. 3505). Berlin: Springer.

  13. Gorodetsky, V., Zhang, C., Skormin, V., & Cao, L. (Eds.) (2007). Autonomous intelligent systems: Multi-agents and data mining. LNCS (Vol. 4476). Berlin: Springer.

  14. Hu J., Wellman M. P. (2003) Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research 4: 1039–1069

    MathSciNet  Google Scholar 

  15. Mohammadian M. (2003) Intelligent agents for data mining and information retrieval. Idea Group Publishing, Hershey

    Book  Google Scholar 

  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).

  17. Symeonidis A., Mitkas P. (2005) Agent intelligence through data mining. Springer, Berlin

    MATH  Google Scholar 

  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).

  19. Tuyls, K., & Weiss, G. (2012). Multiagent learning: Basics, challenges, and prospects, AI Magazine 33.

  20. Weiss, G. A. (1998). Multiagent perspective of parallel and distributed machine learning. In Proceedings of Agents ’98 (pp 226–230).

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Longbing Cao.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cao, L., Weiss, G. & Yu, P.S. A brief introduction to agent mining. Auton Agent Multi-Agent Syst 25, 419–424 (2012).

Download citation

  • Published:

  • Issue Date:

  • DOI: