Argumentation graphs with constraint-based reasoning for collaborative expertise

Abstract Collaborative processes are very important in telemedicine domain since they allow for making right decisions in complex situations with multidisciplinary staff. When modelling these collaborative processes, some inconsistencies can appear. In semantic modelling (conceptual graphs), these inconsistencies are verified using constraints. In this work, collaborative processes are represented using an argumentation system modelled in a conceptual graph formalism where inconsistencies could be particular bad attack relation between arguments. To overcome these inconsistencies, two solutions are proposed. The first one is to weight the arguments evolving in the argumentation system on the basis of the competencies of the health professionals and the credibility of the sources justifying their advice (arguments), and the second one is to model some law concepts as constraints in order to check their compliance of the collaborative process.

[1]  Marie-Laure Mugnier,et al.  On generalization/specialization for conceptual graphs , 1995, J. Exp. Theor. Artif. Intell..

[2]  John F. Sowa,et al.  Conceptual Structures: Information Processing in Mind and Machine , 1983 .

[3]  Bernard Grabot,et al.  Robust competence assessment for job assignment , 2014, Eur. J. Oper. Res..

[4]  Huan Neng Chiu,et al.  A fuzzy multi-criteria decision making approach for solving a bi-objective personnel assignment problem , 2009, Comput. Ind. Eng..

[5]  Mamadou Bilo Doumbouya,et al.  Argumentative reasoning and taxonomic analysis for the identification of medical errors , 2015, Eng. Appl. Artif. Intell..

[6]  Mamadou Bilo Doumbouya,et al.  Argumentation and graph properties , 2016, Inf. Process. Manag..

[7]  M. Daigne,et al.  NetScoring : critères de qualité de l'information de santé sur l'Internet , 1997 .

[8]  Leon van der Torre,et al.  Preference-based argumentation: Arguments supporting multiple values , 2008, Int. J. Approx. Reason..

[9]  Martin Cohen,et al.  A Domain Specific Expert System Model for Diagnostic Consultation in Psychiatry , 2011, 2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing.

[10]  Bernard Moulin,et al.  A taxonomy of argumentation models used for knowledge representation , 2010, Artificial Intelligence Review.

[11]  Michael Wooldridge,et al.  Weighted argument systems: Basic definitions, algorithms, and complexity results , 2011, Artif. Intell..

[12]  Marie-Laure Mugnier,et al.  Graph-based Knowledge Representation - Computational Foundations of Conceptual Graphs , 2008, Advanced Information and Knowledge Processing.

[13]  David J. Barnes,et al.  Formulating partner selection criteria for agile supply chains: A Dempster-Shafer belief acceptability optimisation approach , 2010 .

[14]  Perry L. Miller,et al.  Expert System Knowledge Acquisition for Domains of Medical Workup: An Augmented Transition Network Model , 1986 .

[15]  Phan Minh Dung,et al.  On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming and n-Person Games , 1995, Artif. Intell..

[16]  E. Ketteler,et al.  Competency champions in the clinical competency committee: a successful strategy to implement milestone evaluations and competency coaching. , 2014, Journal of surgical education.

[17]  Mao-Jiun J. Wang,et al.  Personnel placement in a fuzzy environment , 1992, Comput. Oper. Res..

[18]  Casey C. Bennett,et al.  Expert Systems in Mental Health Care , 2016 .

[19]  Madalina Croitoru,et al.  Logical, graph based knowledge representation with CoGui , 2010 .

[20]  Trevor J. M. Bench-Capon,et al.  Audiences in argumentation frameworks , 2007, Artif. Intell..

[21]  Gerd A. Kullak-Ublick,et al.  3.5 Clinical Decision Support Systems , 2012 .

[22]  Claudette Cayrol,et al.  A Reasoning Model Based on the Production of Acceptable Arguments , 2002, Annals of Mathematics and Artificial Intelligence.

[23]  Mamadou Bilo Doumbouya,et al.  Combining conceptual graphs and argumentation for aiding in the teleexpertise , 2015, Comput. Biol. Medicine.

[24]  Sanjay Modgil,et al.  Reasoning about preferences in argumentation frameworks , 2009, Artif. Intell..

[25]  Srdjan Vesic,et al.  A new approach for preference-based argumentation frameworks , 2011, Annals of Mathematics and Artificial Intelligence.

[26]  Jean-Rémi Bourguet,et al.  Contribution aux méthodes d'argumentation pour la prise de décision. Application à l'arbitrage au sein de la filière céréalière. (Contribution to the methods of argumentation for decision making. Application to arbitration within the cereal industry) , 2010 .

[27]  Mamadou Bilo Doumbouya,et al.  A framework for decision making on teleexpertise with traceability of the reasoning , 2015 .

[28]  Madalina Croitoru,et al.  A quantitative preference-based structured argumentation system for decision support , 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[29]  Bernard Kamsu-Foguem,et al.  Knowledge reuse integrating the collaboration from experts in industrial maintenance management , 2013, Knowl. Based Syst..

[30]  Bernard Kamsu-Foguem,et al.  Conceptual graph operations for formal visual reasoning in the medical domain , 2014 .

[31]  E. Shortliffe.  Clinical decision-support systems , 1990 .

[32]  Leila Amgoud,et al.  Argumentation frameworks as constraint satisfaction problems , 2011, Annals of Mathematics and Artificial Intelligence.

[33]  S. Yurdakul,et al.  An Overview to Ethical Problems in Telemedicine Technology , 2013 .

[34]  R. Hollander.  Information constraints in medical encounters , 1984, Journal of bioethics.

[35]  David Sánchez,et al.  An ontology-based measure to compute semantic similarity in biomedicine , 2011, J. Biomed. Informatics.

[36]  Youssef Amghar,et al.  Conceptual framework for document semantic modelling: an application to document and knowledge management in the legal domain , 2003, Data Knowl. Eng..

[37]  Pierre Marquis,et al.  Constrained Argumentation Frameworks , 2006, KR.