We describe two sales strategies used by our agent, MinneTAC, for the 2003 Supply Chain Management Trading Agent Competition (TAC SCM). Both strategies estimate, as the game progresses, the probability of receiving a customer order for different prices and compute the expected profit. Offers are made to maximize the expected profit on each order. The main difference between the two strategies is in how the probability of receiving an order and the offer prices are computed. The first strategy works well in high-demand games, the second was developed to improve performance in low-demand games. We empirically analyze the effect of the discount given by suppliers on orders received the first day of the game, and we show that in high-demand games there is a strong correlation between the offers an agent receives from suppliers on the first day of the game and the agent's performance in the game.
|Title of host publication||Workshop: Trading Agent Design and Analysis at Third Int'l Conf. on Autonomous Agents and Multi-Agent Systems|
|Number of pages||8|
|Publication status||Published - 2004|