Title: Confidence Measure for a Learning Agent
Author: Wojciech Jamroga, Parlevink Group, University of Twente; Institute of Mathematics, University of Gdansk

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.

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