Skip to main content
SpringerLink
Log in

Putting the agent in agent-based modeling

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

Abstract

One of the perquisites of a talk like this is that I get to expound on broad themes. AAMAS is a conference about agents and multiples of agents, so I probably ought to say something about agents. Of course, my position on agents is that I am all for them. Today I’d like to make a case for actually putting agents in agent-based models. I hope that by the end of the talk you have some idea about what I mean by this.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Notes

  1. www.concentricabm.com

  2. Cascade models of information transfer also feature interestingly in Couzin’s research on schooling fish [5].

  3. If a random stranger seems more trustworthy to you than any of your friends, that’s rather sad.

References

  1. Axelrod, R. (1986). An evolutionary approach to norms. American Political Science Review, 80, 1095–1111.

    Article  Google Scholar 

  2. Berdahl, A., Torney, C. J., Ioannou, C. C., Faria, J. J., & Couzin, I. D. (2013). Emergent sensing of complex environments by mobile animal groups. Science, 339, 574–576.

    Article  Google Scholar 

  3. Chakraborty, T., & Kearns, M. (2011). Market making and mean reversion. In Twelfth ACM Conference on Electronic Commerce (pp. 307–314).

  4. Chierichetti, F., Kleinberg, J., & Panconesi, A. (2012). How to schedule a cascade in an arbitrary graph. In Thirteenth ACM Conference on Electronic Commerce (pp. 355–368).

  5. Couzin, I. D., James, R., Mawdsley, D., Croft, D. P., & Krause, J. (2006). Social organization and information transfer in schooling fishes. In B. Culum, L. Kevin, & K. Jens (Eds.), Fish cognition and behavior, Chapter 9. Oxford: Blackwell.

    Google Scholar 

  6. Dandekar, P., Goel, A., Govindan, R., & Post, I. (2011). Liquidity in credit networks: A little trust goes a long way. In Twelfth ACM Conference on Electronic Commerce, San Jose (pp. 147–156).

  7. Dandekar, P., Goel, A., Wellman, M. P., & Wiedenbeck, B. (2015). Strategic formation of credit networks. ACM Transactions on Internet Technology, 15(1), 3.

    Article  Google Scholar 

  8. Easley, David, & Kleinberg, Jon. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. New York: Cambridge University Press.

    Book  MATH  Google Scholar 

  9. Gode, D. K., & Sunder, S. (1993). Allocative efficiency of markets with zero-intelligence traders: Market as a partial substitute for individual rationality. Journal of Political Economy, 101, 119–137.

    Article  Google Scholar 

  10. Greenwald, A., & Stone, P. (2001). The first international trading agent competition: Autonomous bidding agents. IEEE Internet Computing, 5(2), 52–60.

    Article  Google Scholar 

  11. Jordan, P. R., & Wellman, M. P. (2009). Designing the Ad Auctions game for the Trading Agent Competition. In IJCAI-09 Workshop on Trading Agent Design and Analysis, Pasadena, 2009.

  12. Jordan, P. R., Wellman, M. P., & Balakrishnan, G. (2010). Strategy and mechanism lessons from the first ad auctions trading agent competition. In Eleventh ACM Conference on Electronic Commerce, Cambridge, MA (pp. 287–296).

  13. Mahmoud, S., Griffiths, N., Keppens, J., & Luck, M. (2010). In Eighth European Workshop on Multi-Agent Systems: An analysis of norm emergence in Axelrod’s model.

  14. Martin, T., Schoenebeck, G., & Wellman, M. P. (2014). Characterizing strategic cascades on networks. In Fifteenth ACM Conference on Economics and Computation (pp. 113–130).

  15. Miller, J. H., & Page, S. E. (2007). Complex adaptive systems: An introduction to computational models of social life. Princeton: Princeton University Press.

    MATH  Google Scholar 

  16. Miller, N., Garnier, S., Hartnett, A. T., & Couzin, I. D. (2013). Both information and social cohesion determine collective decisions in animal groups. Proceedings of the National Academy of Sciences, 110, 5263–5268.

    Article  Google Scholar 

  17. Niazi, M., & Hussain, A. (2011). Agent-based computing from multi-agent systems to agent-based models: A visual survey. Scientometrics, 89, 479–499.

    Article  Google Scholar 

  18. Pardoe, D., Chakraborty, D., & Stone, P. (2010). TacTex09: A champion bidding agent for ad auctions. In Ninth International Conference on Autonomous Agents and Multi-Agent Systems (pp. 1273–1280), Toronto.

  19. Rand, W. M. (2014). The future applications of agent-based modeling in marketing. In L. Moutinho, E. Bigné, & A. K. Manrai (Eds.) The Routledge Companion to the Future of Marketing, Routledge, 2014.

  20. Schelling, T. C. (1971). Dynamic models of segregation. Journal of Mathematical Sociology, 1, 143–186.

    Article  Google Scholar 

  21. Schelling, T. C. (1978). Micromotives and macrobehavior. New York: Norton.

    Google Scholar 

  22. Tesfatsion, L. (2006). Agent-based computational economics: A constructive approach to economic theory. In L. Tesfatsion & K. L. Judd (Eds.), Handbook of agent-based computational economics. Amsterdam: Elsevier.

    Google Scholar 

  23. Wah, E., & Wellman, M. P. (2013). Latency arbitrage, market fragmentation, and efficiency: A two-market model. In Fourteenth ACM Conference on Electronic Commerce (pp. 855–872).

  24. Wah, E., Wright, M. D., & Wellman, M. P. (2016). Welfare effects of market making in continuous double auctions. Technical report, University of Michigan, 2016. Extended version of AAMAS-15 paper.

  25. Wellman, M. P. (2006). Methods for empirical game-theoretic analysis (extended abstract). In Twenty-First National Conference on Artificial Intelligence, Boston (pp. 1552–1555).

  26. Wellman, M. P., & Wurman, P. R. (1999). A trading agent competition for the research community. In IJCAI-99 Workshop on Agent-Mediated Electronic Trading, Stockholm, August 1999.

  27. Wiedenbeck, B., & Wellman, M. P. (2012). Scaling simulation-based game analysis through deviation-preserving reduction. In Eleventh International Conference on Autonomous Agents and Multi-Agent Systems (pp. 931–938).

  28. Wilensky, U. (1997). NetLogo segregation model. Technical report, Center for Connected Learning and Computer-Based Modeling, Northwestern University

Download references

Acknowledgments

I would like to thank first and foremost my students, present and past. I am particularly proud that many have emerged as successful independent researchers and practitioners active in this field. The wonderful academic environment I enjoy at the University of Michigan has a lot to do with that. I have also learned a great deal from a terrific set of collaborators over the years, and fertile research communities of which I would especially like to acknowledge those who have engaged in the TAC research games. Thanks to IFAAMAS and ACM SIGAI for this award, and this opportunity to share my thoughts with you today. Finally, thank you all for listening, and for clapping.

Author information

Authors and Affiliations

  1. Computer Science & Engineering, University of Michigan, Ann Arbor, USA

    Michael P. Wellman

Authors
  1. Michael P. Wellman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael P. Wellman.

Additional information

Edited transcript of a talk presented at the 13th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-14), in Paris, France, on receipt of the ACM/SIGAI Autonomous Agents Research Award.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wellman, M.P. Putting the agent in agent-based modeling. Auton Agent Multi-Agent Syst 30, 1175–1189 (2016). https://doi.org/10.1007/s10458-016-9336-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10458-016-9336-6

Keywords

Search

Navigation