1. Using inconsistency measures for estimating reliability
- Author
-
Jean-Marc Thévenin, Laurence Cholvy, Laurent Perrussel, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Office National d'Etudes et Recherches Aérospatiales - ONERA (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France), ONERA - The French Aerospace Lab [Toulouse], ONERA, Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, and Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
- Subjects
Preferences elicitation ,media_common.quotation_subject ,Context (language use) ,02 engineering and technology ,Inconsistency ,computer.software_genre ,Theoretical Computer Science ,03 medical and health sciences ,0302 clinical medicine ,Artificial Intelligence ,LOGIC ,0202 electrical engineering, electronic engineering, information engineering ,Quality (business) ,[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC] ,030212 general & internal medicine ,Set (psychology) ,Reliability (statistics) ,media_common ,Mathematics ,Logique en informatique ,Representation theorem ,Applied Mathematics ,Preorder ,Informatique et langage ,Intelligence artificielle ,Apprentissage ,INCONSISTENCY ,INFORMATIONS SOURCES ,Risk analysis (engineering) ,Ranking ,Logic - Reliability assessment ,RELIABILITY ,Key (cryptography) ,020201 artificial intelligence & image processing ,Data mining ,computer ,Software - Abstract
International audience; 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.; Cet article présente une méthode pour calculer la fiabilité relative de sources d'informations. En se basant sur les degrés d'inconsistance des informations rapportées par les agents, on définit la contribution de chaque agent dans l'inconsistance. Après avoir listé des postulats spécifiant les propriétés attendues d'un pré-ordre de fiabilité, on établit un théorème de représentation qui relie les postulats à cette fonction de contribution. Enfin, on décrit comment agréger différents pré-ordres de fiabilité.
- Published
- 2017
- Full Text
- View/download PDF