Argumentation Theory and Decision Aiding

Ouerdane, Wassila; Maudet, Nicolas; Tsoukiàs, Alexis

doi:10.1007/978-1-4419-5904-1_7

Cited by 30 publications

(20 citation statements)

References 107 publications

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“…Explanatory functions were originally developed for expert systems and in the field of artificial intelligence in order to improve human-computer interaction and communication (Amgoud and Prade, 2006;Geldermann, 2010;Ouerdane et al, 2010). One possibility to provide the explanations is by NLG techniques (Holtzman, 1988;Silver, 1991a;Reiter and Dale, 1997).…”

Section: Literature Overview On Mcda Dsss With Explanatory Functionsmentioning

confidence: 99%

A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making

Wulf

Bertsch

2017

Expert Systems with Applications

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A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making Abstract Multi-Criteria Decision Analysis (MCDA) enables decision makers (DM) and decision analysts (DA) to analyse and understand decision situations in a structured and formalised way. With the increasing complexity of decision support systems (DSSs), it becomes challenging for both expert and novice users to understand and interpret the model results. Natural language generation (NLG) techniques are used in various DSSs to cope with this challenge as they reduce the cognitive effort to achieve understanding of decision situations. However, NLG techniques in MCDA have so far mainly been developed for deterministic decision situations or one-dimensional sensitivity analyses. In this paper, a concept for the generation of textual explanations for a multi-dimensional preferential sensitivity analysis in MCDA is developed. The key contribution is a NLG approach that provides detailed explanations of the implications of preferential uncertainties in Multi-Attribute Value Theory (MAVT). It generates a report that assesses the influences of simultaneous or separate variations of inter-criteria and intra-criteria preferential parameters determined within the decision analysis. We explore the added value of the natural language report in an online survey. Our results show that the NLG approach is particularly beneficial for difficult interpretational tasks. IntroductionWith the aim of enabling transparent and systematic support in complex decision situations, Multi-Criteria Decision Analysis (MCDA) represents a formalised framework for the analysis of different decision alternatives (Stewart, 1992;Geldermann et al., 2009). While such decision support approaches are aimed at providing guidance to decision makers (DMs), their increasing mathematical complexity often hinders a straightforward understanding and traceability on the part of the DMs. Consequently, a lot of cognitive effort is required in order to analyse, interpret and derive adequate implications from the obtained model results which is particularly challenging for novice users (Spiegelhalter and KnillJones, 1984;Henrion and Druzdzel, 1991;Gregor and Benbasat, 1999). DMs consider such models as a 'black box', so they mistrust or even reject them (Brans and Mareschal, 1994;Bell et al., 2003), which leads to a gap between available information on the one hand and processible information on the other hand.To compensate for this, further explanations of decision analysis results promote understanding of the decision situation and thus help to increase trust and acceptability of the 3 system (Greer et al., 1994;Greef and Neerincx, 1995;Dhaliwal and Benbasat, 1996;Gregor and Benbasat, 1999;Parikh et al., 2001;Geldermann, 2010). The use of natural language generation (NLG) techniques to generate such explanations automatically based on the model results has been proposed, for instance, by Pap...

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Section: Literature Overview On Mcda Dsss With Explanatory Functionsmentioning

confidence: 99%

A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making

Wulf

Bertsch

2017

Expert Systems with Applications

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“…We believe that they can be enriched mutually, as can be seen in some recent research (Amgoud et al 2007;Fox et al 2007;Ouerdane et al 2010;Labreuche 2011;Van der Weide 2011;Muller and Hunter 2012;Longo et al 2012;Labreuche et al 2012;Kaci and Labreuche 2014). However these works have mainly concentrated on explanations in automatic decision systems or on decisions in contexts not involving public participation or argumentation on the basis of unstructured texts.…”

Section: Introductionmentioning

confidence: 90%

Value-based argumentation for policy decision analysis: methodology and an exploratory case study of a hydroelectric project in Québec

Tremblay

Abi‐Zeid

2015

Ann Oper Res

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In many countries, development projects that may have a substantial impact on the environment are submitted to a public evaluation process within which citizens use argumentation to express and justify their positions regarding a project. These justifications typically refer to various values. Subsequently, a public commission in charge of the evaluation process arrives at a conclusion. But how are the arguments of the various participants taken into account? How do values influence the commission's recommendation? In order to arrive to an understanding of a commission's decision process, we focus on the argumentative nature of the process and apply a methodology combining content analysis and a value-based argumentative framework. This methodology was illustrated using a case study of a hydroelectric project in Québec. First, we analysed a corpus of unstructured texts produced during public hearings and extracted the arguments and values of the participants. We then used a computational model to obtain the commission's possible hypothetical decisions which we compared with the commission's actual conclusion. Furthermore, we identified some preference elements of the commission, and we partially explained their attitude towards conflicting and incoherent arguments. Finally, based on our experience, we formulated some conclusions regarding the ability and promise of argumentative methods to support decision making in a participatory context.

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“…Argument schemes are forms of arguments that capture stereotypical patterns of humans reasoning, especially defeasible ones. Different approaches have investigated the use of argument schemes to decision-making (Ouerdane et al 2010). They greatly extend our understanding of the construction of argument schemes for action.…”

Section: A Hierarchical Structure Of Argumentsmentioning

confidence: 99%

Multiple criteria decision aiding: a dialectical perspective

Ouerdane

2010

4OR-Q J Oper Res

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This is a summary of the Ouerdane's PhD thesis supervised by Alexis Tsoukiàs and Nicolas Maudet and defended on 01 December 2009 at the Université Paris-Dauphine, Paris. The thesis is written in English and is available from the author upon request. This work has the aim to investigate the different ways to use argumentation theory in a decision context. More precisely within multi-criteria evaluation models. The principal aim is to meet the needs in terms of explanations and revision during a decision process.

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Argumentation Theory and Decision Aiding

Cited by 30 publications

References 107 publications

A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making

A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making

Value-based argumentation for policy decision analysis: methodology and an exploratory case study of a hydroelectric project in Québec

Multiple criteria decision aiding: a dialectical perspective

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