Abstract:
This paper reports a research aimed to design a confidence measure for an agent who learns and uses probabilistic models of other agents' behavior. If the agent has several alternative models of a particular opponent, she can use the confidence values to combine the models or choose among them. The measure has been inspired by the research on universal prediction, and based on the self-information loss function. It was verified through some simple experiments with simulated software agents.

Keywords: multiagent systems, meta-uncertainty, confidence, machine learning, user modeling, self-information loss function.

Computational Intelligence Group @ Technical University of Clausthal
Human Media Interaction Group @ University of Twente
Computer Science Group @ University of Gdansk	Last modified 2003-08-19