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Forecasting market prices in a supply chain game

机译:在供应链博弈中预测市场价格

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Predicting the uncertain and dynamic future of market conditions on the supply chain, as reflected in prices, is an essential component of effective operational decision-making. We present and evaluate methods used by our agent, Deep Maize, to forecast market prices in the trading agent competition supply chain management game (TAC/SCM). We employ a variety of machine learning and representational techniques to exploit as many types of information as possible, integrating well-known methods in novel ways. We evaluate these techniques through controlled experiments as well as performance in both the main TAC/SCM tournament and supplementary Prediction Challenge. Our prediction methods demonstrate strong performance in controlled experiments and achieved the best overall score in the Prediction Challenge.
机译:预测价格所反映的供应链上市场状况的不确定性和动态未来,是有效运营决策的重要组成部分。我们介绍并评估代理商Deep Maize用来预测贸易代理商竞争性供应链管理游戏(TAC / SCM)中的市场价格的方法。我们采用各种机器学习和表示技术来利用尽可能多的信息,并以新颖的方式整合众所周知的方法。我们通过受控实验以及在主要TAC / SCM锦标赛和补充预测挑战赛中的表现来评估这些技术。我们的预测方法在受控实验中表现出出色的性能,并在“预测挑战赛”中获得了最佳总体得分。

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