JACK: A Java Auction Configuration Kit
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.
Keywordstrading agents auctions simulation
Unable to display preview. Download preview PDF.
- 3.Kagel, J.H., Levin, D., Hall, A.: Auctions: A survey of experimental research, 1995-2008. In: Handbook of Experimental Economics, vol. 2 (2008)Google Scholar
- 4.Greenwald, A.: The 2002 trading agent competition: An overview of agent strategies. AI Magazine (April 2003)Google Scholar
- 5.Wellman, M.P., Greenwald, A., Stone, P.: Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition. MIT Press (2007)Google Scholar
- 8.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)Google Scholar
- 10.Larson, N., Elmaghraby, W.: Procurement auctions with avoidable fixed costs: An experimental approach (2011)Google Scholar
- 11.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)Google Scholar
- 12.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)Google Scholar
- 13.Eriksson, J., Finne, N., Janson, S.: Evolution of a supply chain management game for the trading agent competition. AI Communications (2000)Google Scholar
- 14.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)Google Scholar
- 17.Krishna, V.: Auction Theory, 2nd edn. Academic Press (2010)Google Scholar
- 19.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)Google Scholar
- 20.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)Google Scholar