Combinatorial Information Market Design
Information Systems Frontiers
A stochastic programming approach to scheduling in TAC SCM
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Walverine: a Walrasian trading agent
Decision Support Systems - Special issue: Decision theory and game theory in agent design
Controlling a supply chain agent using value-based decomposition
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
CMieux: adaptive strategies for competitive supply chain trading
ICEC '06 Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet
Designing a successful trading agent for supply chain management
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Empirical game-theoretic analysis of the TAC Supply Chain game
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Decision-theoretic bidding based on learned density models in simultaneous, interacting auctions
Journal of Artificial Intelligence Research
Price prediction in a trading agent competition
Journal of Artificial Intelligence Research
Bidding for customer orders in TAC SCM
AAMAS'04 Proceedings of the 6th AAMAS international conference on Agent-Mediated Electronic Commerce: theories for and Engineering of Distributed Mechanisms and Systems
Data Mining-Driven Analysis and Decomposition in Agent Supply Chain Management Networks
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Forecasting market prices in a supply chain game
Electronic Commerce Research and Applications
The 2007 procurement challenge: A competition to evaluate mixed procurement strategies
Electronic Commerce Research and Applications
Multiagent bayesian forecasting of structural time-invariant dynamic systems with graphical models
International Journal of Approximate Reasoning
Intelligent ethical wealth planner: a multi-agent approach
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
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Future market conditions can be a pivotal factor in making business decisions. We present and evaluate methods used by our agent, Deep Maize, to forecast market prices in the Trading Agent Competition Supply Chain Management Game. As a guiding principle we seek to exploit as many sources of available information as possible to inform predictions. Since information comes in several different forms, we integrate well-known methods in a novel way to make predictions. The core of our predictor is a nearest-neighbors machine learning algorithm that identifies historical instances with similar economic indicators. We augment this with an online learning procedure that transforms the predictions by optimizing a scoring rule. This allows us to select more relevant historical contexts using additional information available during individual games. We also explore the advantages of two different representations for predicting price distributions. One uses absolute prices, and the other uses statistics of price time series to exploit local stability. We evaluate these methods using both data from the 2005 tournament final round and additional simulations. We compare several variations of our predictor to one another and a baseline predictor similar to those used by many other tournament agents. We show substantial improvements over the baseline predictor, and demonstrate that each element of our predictor contributes to improved performance.