@InProceedings{andrews09a,
  author =	 {James Andrews and Michael Benisch and Alberto
                  Sardinha and Norman Sadeh},
  title =	 {Using Information Gain to Analyze and Fine Tune the
                  Performance of Supply Chain Trading Agents},
  booktitle =	 {Agent-Mediated Electronic Commerce and Trading Agent
                  Design and Analysis},
  year =	 2009,
  abstract =	 {The Supply Chain Trading Agent Competition (TAC SCM)
                  was designed to explore approaches to dynamic supply
                  chain trading. During the course of each year’s
                  competition historical data is logged describing
                  more than 800 games played by different agents from
                  around the world. In this paper, we present analysis
                  that is focused on determining which features of
                  agent behavior, such as the average lead time
                  requested for supplies or the average selling price
                  offered on finished products, tend to differentiate
                  agents that win from those that do not. We present a
                  visual inspection of data from 16 games played in
                  one bracket of the 2006 TAC SCM semi-final
                  rounds. Plots of data from these games help isolate
                  behavioral features that distinguish top performing
                  agents in this bracket. We then introduce a metric
                  based on information gain to provide a more complete
                  analysis of the 80 games played in the 2006 TAC SCM
                  quarter-final, semi-final and final rounds. The
                  metric captures the amount of information that is
                  gained about an agent’s performance by knowing its
                  value for each of 20 different behavioral
                  features. Using this metric we find that, in the
                  final rounds of the 2006 competition, winning agents
                  distinguished themselves by their procurement
                  decisions, rather than their customer bidding
                  decisions. We also discuss how we used the analysis
                  presented in this paper to improve our entry for the
                  2007 competition, which was one of the six finalists
                  that year.},
  doi =		 {10.1007/978-3-540-88713-3}
}