Towards Consistency-Based Reliability Assessment - Archive ouverte HAL
Communication Dans Un Congrès Année : 2015

Towards Consistency-Based Reliability Assessment

Résumé

MOTIVATION : Merging information provided by several sources is an important issue and merging techniques have been extensively studied. When the reliability of the sources is not known, one can apply merging techniques such as majority or arbitration merging or distancebasedmerging for solving conflicts between information. At the opposite, if the reliability of the sources is known, either represented in a quantitative or in a qualitative way, then it can be used to manage contradictions: information provided by a source is generally weakened or ignored if it contradicts information provided by a more reliable source [1, 4, 6]. Assessing the reliability of information sources is thus crucial. The present paper addresses this key question. We adopt a qualitative point of view for reliability representation by assuming that the relative reliability of information sources is represented by a total preorder. This works considers that we have no information about the sources and in particular, we do not know if they are correct (i.e they provide true information) or not. We focus on a preliminary stage of observation and assessment of sources. We claim that during that stage the key issue is a consistency analysis of information provided by sources, whether it is the consistency of single reports or consistency w.r.t trusted knowledge or the consistency of different reports together. We adopt an axiomatic approach: first we give some postulates which characterize what this reliability preorder should be, then we define a generic operator for building this preorder in agreement with the postulates.
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Dates et versions

hal-01327078 , version 1 (06-06-2016)

Identifiants

  • HAL Id : hal-01327078 , version 1

Citer

Laurence Cholvy, Laurent Perrussel, William Raynaut, Jean-Marc Thévenin. Towards Consistency-Based Reliability Assessment. 14th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015), May 2015, Istanbul, Turkey. pp. 1643-1644. ⟨hal-01327078⟩
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