Meeting Minutes - 18 February 2009

Today I discussed the main results of my master's thesis, in which I try to incorporate procurement information into an economic regime model based on sales information. This model is used in the MinneTAC agent, which is an artifical trading agent that competes in the TAC SCM game.

First, I gave a brief description of the TAC SCM game, after which I introduced the regime model as it is currently used in the MinneTAC agent. Then, I introduced a new procurement variable, i.e., offer prices, after which I elaborated on both regime identification and regime prediction. Finally, I discussed some experimental results.

During the last part of the presentation where I introduced some experimental results, we had a discussion on the causes of these results. As it seems, implementing procurement information into the regime model does not lead to better performance of the MinneTAC agent in TAC SCM games. In fact, the agent gets more orders from customers, but generates lower profits. Other competitors seem to take advantage of the situation, since their profits increase when MinneTAC uses the new regime model.

A suggested cause is the fact that there could be a delay regarding the procurement information. Procurement information might be a leading indicator for regimes, so perhaps creating a regime model based on the sales price of yesterday and the procurement offer price of for instance three days earlier could improve the performance of the agent. However, this is dependent on the cost allocation of the agent. Furthermore, there is a lack of adaptivity in the regime model and therefore, the model cannot adjust properly during a game. Finally, regime information is not used for price setting in the experiments discussed today. Establishing this connection between regimes and price setting could improve the overall results as well.

Frederik