Intelligent Trading Agents
Intelligent Trading Agents that Facilitate Decision Making in Multi-Agent Marketplaces using Preference Modeling
(duration: 11/2008 - 04/2013)
Modern business networks and markets are highly dynamic and exhibit a high degree of uncertainty. Business managers thus often have to make complex strategic, tactical, and operational decisions; ranging from the macroscopic (i.e. which markets should we enter and when?) to the microscopic (i.e. which products should be packed on which pallet?).
This project aims to design, build and assess an intelligent multi-agent system that can support people in making such complex business decisions. The software agents must mimic human decision making behaviour in an electronic market or auction environment.
We define learning agents as software entities that carry out some set of operations on behalf of a user or another program with some degree of independence or autonomy. Agents improve their performance by learning from experience and in so doing employ some knowledge or representation of the user's goals or needs. The application will be aimed at the logistics domain, specifically supply chain management.
Eric van Heck (ERIM, Erasmus University)
Hans Abbink (Almende)