Abstract
A key step in the evaluation of an intelligent agent (either autonomous or human) is determining the agent’s success as compared to other agents designed to participate in the same environment. Such comparisons are the basis for the Trading Agent Competition (TAC), in which autonomous trading agents compete in simulated market scenarios. TAC servers and agents alike are highly specialized, and typically require teams of developers as TAC simulations tend to be rather complex. In this work, we present a client-server infrastructure that is capable of simulating not just one complex market and its corresponding set of agents, but a wide space of markets and potentially more robust agents. Supported market mechanisms include both user-designed auctions and a configurable set of auctions whose basic building blocks are commonly-studied (e.g., first-price, second-price, simultaneous, sequential auctions). Our so-called Java Auction Configuration Kit (JACK) is intended to facilitate research on the interplay between a variety of auction mechanisms and a variety of agent strategies (both autonomous and human) by simplifying the orchestration of auction simulation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Dorsey, R., Razzolini, L.: Explaining overbidding in first price auctions using controlled lotteries. Experimental Economics 6(2), 123–140 (2003)
Isaac, R.M.: Just who are you calling risk averse? Journal of Risk and Uncertainty 20(2), 177–187 (2000)
Kagel, J.H., Levin, D., Hall, A.: Auctions: A survey of experimental research, 1995-2008. In: Handbook of Experimental Economics, vol. 2 (2008)
Greenwald, A.: The 2002 trading agent competition: An overview of agent strategies. AI Magazine (April 2003)
Wellman, M.P., Greenwald, A., Stone, P.: Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition. MIT Press (2007)
Jordan, P.R., Kiekintveld, C., Wellman, M.P.: Empirical game-theoretic analysis of the tac supply chain game. In: AAMAS 2007: Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 1–8. ACM, New York (2007)
Mason, W., Suri, S.: Conducting behavioral research on Amazons Mechanical Turk. Behavior Research Methods 44(1), 1–23 (2011)
Vorobeychik, Y., Kiekintveld, C., Wellman, M.P.: Empirical mechanism design: Methods, with application to a supply-chain scenario. In: Seventh ACM Conference on Electronic Commerce, pp. 306–315 (2006)
Fischbacher, U.: z-Tree: Zurich toolbox for ready-made economic experiments. Experimental Economics 10(2), 171–178 (2007)
Larson, N., Elmaghraby, W.: Procurement auctions with avoidable fixed costs: An experimental approach (2011)
Cox, J.C., Swarthout, J.T.: EconPort: Creating and maintaining a knowledge commons. Technical report, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University (2005)
Wurman, P.R., Wellman, M.P., Walsh, W.E.: The Michigan Internet AuctionBot: A configurable auction server for human and software agents. In: Second International Conference on Autonomous Agents, pp. 301–308 (1998)
Eriksson, J., Finne, N., Janson, S.: Evolution of a supply chain management game for the trading agent competition. AI Communications (2000)
Collins, J., Arunachalam, R., Sadeh, N., Eriksson, J., Finne, N., Janson, S.: The Supply Chain Management Game for the 2007 Trading Agent Competition. Technical report, Carnegie Mellon University (2006)
Jordan, P.R., Wellman, M.P.: Designing an ad auctions game for the trading agent competition. In: David, E., Gerding, E., Sarne, D., Shehory, O. (eds.) AMEC 2009. LNBIP, vol. 59, pp. 147–162. Springer, Heidelberg (2010)
Wurman, P.R., Wellman, M.P., Walsh, W.E.: A parametrization of the auction design space. Games and Economic Behavior 35, 304–338 (2001)
Krishna, V.: Auction Theory, 2nd edn. Academic Press (2010)
Reeves, D.M., Wellman, M.P., MacKie-Mason, J.K., Osepayshvili, A.: Exploring bidding strategies for market-based scheduling. Decision Support Systems 39(1), 67–85 (2005)
Yoon, D.Y., Wellman, M.P.: Self-confirming price prediction for bidding in simultaneous second-price sealed-bid auctions. In: IJCAI 2011 Workshop on Trading Agent Design and Analysis (2011)
van Heck, E., Ketter, W.: Software Agents Supporting Decision-Makers in Complex Flower Business Networks. Liber Amicorum In Memoriam of Prof. Dr. Ir. Jo van Nunen (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Goff, T., Greenwald, A., Hilliard, E., Ketter, W., Loomis, A., Sodomka, E. (2013). JACK: A Java Auction Configuration Kit. In: David, E., Kiekintveld, C., Robu, V., Shehory, O., Stein, S. (eds) Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets. AMEC TADA 2012 2012. Lecture Notes in Business Information Processing, vol 136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40864-9_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-40864-9_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40863-2
Online ISBN: 978-3-642-40864-9
eBook Packages: Computer ScienceComputer Science (R0)