Skip to main content

EGTAOnline: An Experiment Manager for Simulation-Based Game Studies

  • Conference paper
Multi-Agent-Based Simulation XIII (MABS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7838))

Abstract

Empirical game-theoretic analysis (EGTA) is a promising methodology for studying complex strategic scenarios through agent-based simulation. One challenge of utilizing this methodology is that it can require tremendous amounts of computation. Constructing the payoff matrix for a game of even moderate complexity entails significant data gathering and management concerns. We present EGTAOnline, an experiment management system that simplifies the application of the EGTA methodology to large games. We describe the architecture of EGTAOnline, explain why such a tool is practically important, and discuss avenues of research that are suggested through the use of EGTAOnline.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /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
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 72.00
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  • Alberts, S., Keenan, M.K., D’Souza, R.M.: Data-parallel techniques for simulating a mega-scale agent-based model of systemic inflammatory response syndrome on graphics processing units. Simulation 88(8), 895–907 (2012)

    Article  Google Scholar 

  • Bononi, L., Bracuto, M., D’Angelo, G., Donatiello, L.: Concurrent replication of parallel and distributed simulations. In: 19th Workshop on Principles of Advanced and Distributed Simulation, Monterey, CA, pp. 234–243 (2005)

    Google Scholar 

  • Cassell, B.-A., Wellman, M.P.: Asset pricing under ambiguous information: An empirical game-theoretic analysis. Computational and Mathematical Organization Theory 18, 445–462 (2012)

    Article  Google Scholar 

  • Cassell, B.-A., Alperovich, T., Wellman, M.P., Noble, B.: Access point selection under emerging wireless technologies. In: Sixth Workshop on the Economics of Networks, Systems, and Computation, San Jose, CA (2011)

    Google Scholar 

  • Chen, C.-H., Lee, L.H.: Stochastic Simulation Optimization: An Optimal Computing Budget Allocation. World Scientific Publishing Co., Singapore (2011)

    Google Scholar 

  • Collins, J., Ketter, W., Pakanati, A.: An experiment management framework for TAC SCM agent evaluation. In: IJCAI 2009 Workshop on Trading Agent Design and Analysis, Pasadena, California, pp. 9–13 (2009)

    Google Scholar 

  • Dandekar, P., Goel, A., Wellman, M.P., Wiedenbeck, B.: Strategic formation of credit networks. In: 21st International Conference on World Wide Web, Lyon, France (2012)

    Google Scholar 

  • Frazier, G., Duong, Q., Wellman, M.P., Petersen, E.: Incentivizing responsible networking via introduction-based routing. In: McCune, J.M., Balacheff, B., Perrig, A., Sadeghi, A.-R., Sasse, A., Beres, Y. (eds.) Trust 2011. LNCS, vol. 6740, pp. 277–293. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  • Ghosh, M., Mukhopadhyay, N., Sen, P.K.: Sequential Estimation. John Wiley & Sons (1997)

    Google Scholar 

  • Jordan, P.R., Kiekintveld, C., Wellman, M.P.: Empirical game-theoretic analysis of the TAC supply chain game. In: Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, Honolulu, pp. 1188–1195 (2007)

    Google Scholar 

  • Jordan, P.R., Vorobeychik, Y., Wellman, M.P.: Searching for approximate equilibria in empirical games. In: Seventh International Conference on Autonomous Agents and Multiagent Systems, Estoril, Portugal, pp. 1063–1070 (2008)

    Google Scholar 

  • Lavenberg, S.S., Welch, P.D.: A perspective on the use of control variables to increase the efficiency of monte carlo simulations. Management Science 27(3), 322–335 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  • McKelvey, R.D., McLennan, A.M., Turocy, T.L.: Gambit: Software tools for game theory. Technical report, Version 0.2006.01.20 (2006), http://econweb.tamu.edu/gambit/

  • Mengistu, D., Davidsson, P., Lundberg, L.: Middleware support for performance improvement of MABS applications in the grid environment. In: Antunes, L., Paolucci, M., Norling, E. (eds.) MABS 2007. LNCS (LNAI), vol. 5003, pp. 20–35. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  • Nudelman, E., Wortman, J., Shoham, Y., Leyton-Brown, K.: Run the GAMUT: A comprehensive approach to evaluating game-theoretic algorithms. In: Third International Joint Conference on Autonomous Agents and Multiagent Systems, New York, pp. 880–887 (2004)

    Google Scholar 

  • Ólafsson, S., Kim, J.: Simulation optimization. In: Winter Simulation Conference, San Diego, pp. 79–84 (2002)

    Google Scholar 

  • Riley, P.F., Riley, G.F.: Spades: A distributed agent simulation environment with software-in-the-loop execution. In: 35th Winter Simulation Conference, New Orleans, pp. 817–825 (2003)

    Google Scholar 

  • Sheutz, M., Harris, J.J.: An overview of the SimWorld agent-based grid experimentation system. In: Large-Scale Computing Techniques for Complex System Simulations. John Wiley & Sons (2012)

    Google Scholar 

  • Vorobeychik, Y.: Probabilistic analysis of simulation-based games. ACM Transactions on Modeling and Computer Simulation 20(3) (2010)

    Google Scholar 

  • Vorobeychik, Y., Wellman, M.P.: Stochastic search methods for Nash equilibrium approximation in simulation-based games. In: Seventh International Conference on Autonomous Agents and Multiagent Systems, Estoril, Portugal, pp. 1055–1062 (2008)

    Google Scholar 

  • Wellman, M.P.: Methods for empirical game-theoretic analysis. In: 21st National Conference on Artificial Intelligence, Boston, pp. 1552–1555 (2006)

    Google Scholar 

  • Wellman, M.P., Reeves, D.M., Lochner, K.M., Cheng, S.-F., Suri, R.: Approximate strategic reasoning through hierarchical reduction of large symmetric games. In: 20th National Conference on Artificial Intelligence, Pittsburgh, pp. 502–508 (2005)

    Google Scholar 

  • Wellman, M.P., Sodomka, E., Greenwald, A.: Self-confirming price prediction strategies for simultaneous one-shot auctions. In: 28th Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA (2012)

    Google Scholar 

  • Wiedenbeck, B., Wellman, M.P.: Scaling simulation-based game analysis through deviation-preserving reduction. In: 11th International Conference on Autonomous Agents and Multiagent Systems, Valencia, pp. 931–938 (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cassell, BA., Wellman, M.P. (2013). EGTAOnline: An Experiment Manager for Simulation-Based Game Studies. In: Giardini, F., Amblard, F. (eds) Multi-Agent-Based Simulation XIII. MABS 2012. Lecture Notes in Computer Science(), vol 7838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38859-0_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38859-0_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38858-3

  • Online ISBN: 978-3-642-38859-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics