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Using inconsistency measures for estimating reliability

Abstract : Any decision taken by an agent requires some knowledge of its environment. Communication with other agents is a key issue for assessing the overall quality of its own knowledge. This assessment is a challenge itself as the agent may receive information from unknown agents. The aim of this paper is to propose a framework for assessing the reliability of unknown agents based on communication. We assume that information is represented through logical statements and logical inconsistency is the underlying notion of reliability assessment. In our context, assessing consists of ranking the agents and representing reliability through a total preorder. The overall communication set is first evaluated with the help of inconsistency measures. Next, the measures are used for assessing the contribution of each agent to the overall inconsistency of the communication set. After stating the postulates specifying the expected properties of the reliability preorder, we show through a representation theorem how these postulates and the contribution of the agent are interwoven. We also detail how the properties of the inconsistency measures influence the properties of the contribution assessment. Finally we describe how to aggregate different reliability preorders, each of them may be based on different inconsistency measures.
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Laurence Cholvy, Laurent Perrussel, Jean-Marc Thévenin. Using inconsistency measures for estimating reliability. International Journal of Approximate Reasoning, Elsevier, 2017, 89, pp.41-57. ⟨10.1016/j.ijar.2016.10.004⟩. ⟨hal-01407484⟩

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