Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
An adaptation of Relief for attribute estimation in regression
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
A robust agent design for dynamic SCM environments
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
Agent Mertacor: A robust design for dealing with uncertainty and variation in SCM environments
Expert Systems with Applications: An International Journal
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Supply Chain Management (SCM) environments are often dynamic markets providing a plethora of information, either complete or incomplete. It is, therefore, evident that such environments demand intelligent solutions, which can perceive variations and act in order to achieve maximum revenue. To do so, they must also provide some sophisticated mechanism for exploiting the full potential of the environments they inhabit. Advancing on the way autonomous solutions usually deal with the SCM process, we have built a robust and highly-adaptable mechanism for efficiently dealing with all SCM facets, while at the same time incorporating a module that exploits data mining technology in order to forecast the price of the winning bid in a given order and, thus, adjust its bidding strategy. The paper presents our agent, Mertacor, and focuses on the forecasting mechanism it incorporates, aiming to optimal agent efficiency.