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Wolfgang Ketter, Elena Kryzhnyaya, Steven Damer, Colin McMillen, Amrudin Agovic, John Collins, and Maria Gini. Design and Analysis of the MinneTAC-03 Supply-Chain Trading Agent. Technical Report 04-016, University of Minnesota, Dept of Computer Science and Engineering, 2004.
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MinneTAC is an agent designed to compete in the Supply-Chain Trading Agent Competition. It is also designed to support the needs of a group of researchers, each of whom is interested in different decision problems related to the competition scenario. The design of MinneTAC breaks out each basic behavior into a separate, configurable component. Dependencies between components are almost non-existent. This design allows each user to focus on a single problem and work independently, and it allows multiple user to tackle the same problem in different ways. This paper describes the design of MinneTAC and evaluates its effectiveness in support of our research agenda, and in its competitiveness in the TAC-SCM game environment. We also describe two sales strategies used by MinneTAC. 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.
@TechReport{Ketter04tr,
author = "Wolfgang Ketter and Elena Kryzhnyaya and Steven Damer
and Colin McMillen and Amrudin Agovic and John Collins
and Maria Gini",
title = "Design and Analysis of the {MinneTAC-03 Supply-Chain
Trading Agent}",
year = "2004",
abstract = " MinneTAC is an agent designed to compete in the
Supply-Chain Trading Agent Competition. It is also designed to
support the needs of a group of researchers, each of whom is
interested in different decision problems related to the competition
scenario. The design of MinneTAC breaks out each basic behavior into
a separate, configurable component. Dependencies between components
are almost non-existent. This design allows each user to focus on a
single problem and work independently, and it allows multiple user
to tackle the same problem in different ways. This paper describes
the design of MinneTAC and evaluates its effectiveness in support of
our research agenda, and in its competitiveness in the TAC-SCM game
environment. We also describe two sales strategies used by
MinneTAC. 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.",
institution = "University of Minnesota, Dept of Computer Science
and Engineering",
number = "04-016",
address = "Minneapolis, MN",
bib2html_pubtype = {Unrefereed},
bib2html_rescat = {Trading Agents: Supply-Chain Management},
}
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