Abstract
An autonomous trading agent is a complex piece of software that must operate in a competitive economic environment and support a research agenda. We describe the structure of decision processes in the MinneTAC trading agent, focusing on the use of evaluators -- configurable, composable modules for data analysis and prediction that are chained together at runtime to support agent decision-making. Through a set of examples, we show how this structure supports sales and procurement decisions, and how those decision process can be modified in useful ways by changing evaluator configurations.
| Original language | English |
|---|---|
| Title of host publication | AAAI Spring Symposium on Architectures for Intelligent Theory-Based Agents |
| Pages | 7-12 |
| Number of pages | 6 |
| Volume | SS-08-02 |
| Publication status | Published - 2008 |
| Externally published | Yes |