Understanding how people design trading agents over time

As computerized agents are becoming more and more common, e-commerce becomes a major candidate for incorporation of automated agents. Thus, it is vital to understand how people design agents for online markets and how their design changes over time. This, in turn, will enable better design of agents for these environments. We focus on the design of trading agents for bilateral negotiations with unenforceable agreements. In order to simulate this environment we conducted an experiment with human subjects who were asked to design agents for a resource allocation game. The subjects' agents participated in several tournaments against each other and were given the opportunity to improve their agents based on their performance in previous tournaments. Our results show that, indeed, most subjects modified their agents' strategic behavior with the prospect of improving the performance of their agents, yet their average score significantly decreased throughout the tournaments and became closer to the equilibrium agents' score. In particular, the subjects modified their agents to break more agreements throughout the tournaments. In addition, the subjects increased their means of protection against deceiving agents.

[1]  Jianhua Ma,et al.  A Real Trading Model based Price Negotiation Agents , 2006, 20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06).

[2]  Pier Luca Lanzi,et al.  A statistical analysis of the trading agent competition 2001 , 2002, SECO.

[3]  E. Damme,et al.  Information, Strategic Behavior, and Fairness in Ultimatum Bargaining: An Experimental Study. , 1998, Journal of mathematical psychology.

[4]  Sarit Kraus,et al.  The influence of social dependencies on decision-making: initial investigations with a new game , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[5]  Colin Camerer,et al.  Measuring Social Norms and Preferences Using Experimental Games: A Guide for Social Scientists , 2002 .

[6]  R. Selten,et al.  Duopoly Strategies Programmed by Experienced Players , 1997 .

[7]  Peter Stone,et al.  The First International Trading Agent Competition: Autonomous Bidding Agents , 2005, Electron. Commer. Res..

[8]  Stefan Luckner,et al.  Automated Trading across E-Market Boundaries , 2006 .

[9]  Michael P. Wellman,et al.  The 2001 trading agent competition , 2002, Electron. Mark..

[10]  Theo Offerman,et al.  Cooperation in an Overlapping Generations Experiment , 1999, Games Econ. Behav..

[11]  James Andreoni,et al.  Why free ride?: Strategies and learning in public goods experiments , 1988 .

[12]  C. O'Riordan Iterated Prisoner ’ s Dilemma : A review , 2007 .

[13]  Larry Samuelson,et al.  Foundations of Human Sociality: A Review Essay , 2005 .