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Combining statistics and arguments to compute trust

We propose a method for constructing Dempster-Shafer belief functions modeling the trust of a given agent (the evaluator) in another (the target) by combining statistical information concerning the past behaviour of the target and arguments concerning the target's expected behaviour. These arguments are built from current and past contracts between evaluator and target. We prove that our method extends a standard computational method for trust that relies upon statistical information only. We observe experimentally that the two methods have identical predictive performance when the evaluator is highly "cautious", but our method gives a significant increase when the evaluator is not or is only moderately "cautious". Finally, we observe experimentally that target agents are more motivated to honour contracts when evaluated using our model of trust than when trust is computed on a purely statistical basis.