Abstract
Unlike the classic Trading Agent competition (tac), where participants enter trading strategies into a market, the tac Market Design Competition (cat) allows participants to create rules for their own double auction market and set fees for traders, which they embody in agents known as specialists. Although the generalisation properties of traders when the specialist (i.e., the market mechanism) is fixed have been assessed, generalisation properties of specialists have not. It is unclear whether and how a specialist might (intentionally or unintentionally) favour certain trading strategies. We present an empirical analysis of specialists’ generalisation abilities in various trading environments. Our results show that specialists can be sensitive to a number of factors, including the other trading and specialist strategies in the environment.
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Gerding, E., McBurney, P., Niu, J., Parsons, S., Phelps, S.: Overview of CAT: A market design competition. Technical Report ULCS-07-006 Version 1.1, Department of Computer Science, University of Liverpool, Liverpool, UK (2007)
Gode, D.K., Sunder, S.: Allocative efficiency of markets with zero-intelligence traders: Market as a partial substitute for individual rationality. Journal of Political Economy 101(1), 119–137 (1993)
Cliff, D.: Minimal-intelligence agents for bargaining behaviors in market-based environments. Technical Report HPL-97-91, Hewlett-Packard Research Laboratories, Bristol, UK (1997)
Erev, I., Roth, A.E.: Predicting how people play games: Reinforcement learning in experimental games with unique, mixed strategy equilibria. American Economic Review 88(4), 848–881 (1998)
Gjerstad, S., Dickhaut, J.: Price formation in double auctions. Games and Economic Behavior 22(1), 1–29 (1998)
Robbins, H.: Some aspects of the sequential design of experiments. Bulletin of the American Mathematical Society 58(5), 527–535 (1952)
Niu, J., Cai, K., Gerding, E., McBurney, P., Parsons, S.: Characterizing effective auction mechanisms: Insights from the 2007 TAC market design competition. In: Padgham, L., et al. (eds.) 7th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2008), NY, USA. ACM Press, New York (2008)
Petric, A., Podobnik, V., Grguric, A., Zemljic, M.: Designing an effective e-market: an overview of the CAT agent. In: Ketter, W. (ed.) Proceedings of 2008 Workshop on Trading Agent Design and Analysis (TADA 2008), Chicago, USA (2008)
Vytelingum, P., Vetsikas, I.A., Shi, B., Jennings, N.R.: IAMwildCat: The winning strategy for the TAC market design competition. In: Ghallab, M., et al. (eds.) 18th European Conference on AI (ECAI-2008), Patras, Greece. IOS Press, Amsterdam (2008)
Niu, J., Cai, K., McBurney, P., Parsons, S.: An analysis of entries in the first TAC market design competition. In: Jain, L., et al. (ed.) IEEE-WIC-ACM International Conference on Intelligent Agent Technology (IAT 2008), Sydney, Australia (2008)
Moses, L.E.: Think and Explain with Statistics. Addison-Wesley Publ. Co., Reading (1986)
Devroye, L.: Non-Uniform Random Variate Generation. Springer, New York (1986)
Vetsikas, I.A., Selman, B.: A principled study of the design tradeoffs for autonomous trading agents. In: AAMAS ’03: Proceedings of the second international joint conference on Autonomous agents and multiagent systems, pp. 473–480. ACM Press, New York (2003)
Wellman, M., Reeves, D., Lochner, K., Cheng, S., Suri, R.: Approximate strategic reasoning through hierarchical reduction of large symmetric games. In: Proceedings of the Twentieth National Conference on Artificial Intelligence, Pittsburgh, Pennsylvania, USA. AAAI, Menlo Park (2005)
Niu, J., Cai, K., Parsons, S., Sklar, E.: Some preliminary results on competition between markets for automated traders. In: Collins, J. (ed.) Proceedings of the AAAI 2007 Workshop on Trading Agent Design and Analysis (TADA 2007), Vancouver, Canada (2007)
Chong, S.Y., Tino, P., Yao, X.: Measuring generalization performance in co-evolutionary learning. IEEE Transactions on Evolutionary Computation 12(4), 479–505 (2008)
Marks, R.E.: Validating simulation models: a general framework and four applied examples. Journal of Computational Economics 30(3), 265–290 (2007)
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Robinson, E., McBurney, P., Yao, X. (2010). How Specialised Are Specialists? Generalisation Properties of Entries from the 2008 and 2009 TAC Market Design Competitions. In: David, E., Gerding, E., Sarne, D., Shehory, O. (eds) Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets. AMEC TADA 2009 2009. Lecture Notes in Business Information Processing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15117-0_13
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DOI: https://doi.org/10.1007/978-3-642-15117-0_13
Publisher Name: Springer, Berlin, Heidelberg
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