Intelligent Trading Agents that Facilitate Decision Making in Multi-Agent Marketplaces using Preference Modeling
Duration: 11/2008 – 04/2013
Intelligent Trading Agents
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 is able to support people in making such complex business decisions. The software agents must mimic human decision making behaviour in an electronic market or auction environment.
Learning agents are defined 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.