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Information-based Reputation

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Abstract

Information-based agents use tools from information theory to evaluate their utterances and to build their world model. When embedded in a social network these agents measure the strength of information flow in this sense. This leads to a model of information-based reputation in which agents share opinions, and observe the way in which their opinions effect the opinions of others. A method is proposed that supports the deliberative process of combining opinions into a groups reputation. The reliability of agents as opinion givers are measured in terms of the extent to which their opinions differ from that of the group reputation. These reliability measures are used to form an a priori reputation estimate given the individual opinions of a set of independent agents.

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