A Belief Augmented Frame Computational Trust Model

Colin Keng-Yan Tan, National University of Singapore

We present a novel trust model based on BAF-Logic, a system of reasoning that was originally developed for Belief Augmented Frames (BAF), to perform inexact reasoning over knowledge represented as Minsky frames and augmented with twin belief values that measure an Agent’s degree of belief for and against a proposition. By applying BAF-Logic to trust modeling, we are not only able to model trust based on statistical measures, but also with propositional logic, thus enabling an Agent to evaluate another Agent’s trustworthiness not only based on experience and reputation, but also based on logical arguments for and against trusting that other Agent. We present an extended example demonstrating how this model may be applied, followed by a discussion, and finally we conclude this paper with suggestions for further work.


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