The Hierarchical Hidden Markov Model: Analysis and Applications
Machine Learning
Time Series Analysis: Forecasting and Control
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A new polynomial-time algorithm for linear programming
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Optimal Dynamic Pricing for Perishable Assets with Nonhomogeneous Demand
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Information Systems Research
Models for Supply Chains in E-Business
Management Science
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Management Science
Price prediction and insurance for online auctions
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Botticelli: a supply chain management agent designed to optimize under uncertainty
ACM SIGecom Exchanges
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ACM SIGecom Exchanges
Pricing for customers with probabilistic valuations as a continuous knapsack problem
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
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AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
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Agent Mertacor: A robust design for dealing with uncertainty and variation in SCM environments
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Flexible decision control in an autonomous trading agent
Electronic Commerce Research and Applications
INFORMS Journal on Computing
Data-Mining-Enhanced Agents in Dynamic Supply-Chain-Management Environments
IEEE Intelligent Systems
TacTex-05: a champion supply chain management agent
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Efficient statistical methods for evaluating trading agent performance
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Detecting and forecasting economic regimes in multi-agent automated exchanges
Decision Support Systems
Learning global models based on distributed data abstractions
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
On the memory complexity of the forward-backward algorithm
Pattern Recognition Letters
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Information Systems Research
A robust agent design for dynamic SCM environments
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
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Information Systems Research
Agent-assisted supply chain management: Analysis and lessons learned
Decision Support Systems
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Many enterprises that participate in dynamic markets need to make product pricing and inventory resource utilization decisions in real time. We describe a family of statistical models that addresses these needs by combining characterization of the economic environment with the ability to predict future economic conditions to make tactical (short-term) decisions, such as product pricing, and strategic (long-term) decisions, such as level of finished goods inventories. Our models characterize economic conditions, called economic regimes, in the form of recurrent statistical patterns that have clear qualitative interpretations. We show how these models can be used to predict prices, price trends, and the probability of receiving a customer order at a given price. These “regime” models are developed using statistical analysis of historical data and are used in real time to characterize observed market conditions and predict the evolution of market conditions over multiple time scales. We evaluate our models using a testbed derived from the Trading Agent Competition for Supply Chain Management, a supply chain environment characterized by competitive procurement, sales markets, and dynamic pricing. We show how regime models can be used to inform both short-term pricing decisions and long-term resource allocation decisions. Results show that our method outperforms more traditional short-and long-term predictive modeling approaches.