Abstract argumentation frameworks to promote fairness and rationality in multi-experts multi-criteria decision making

. Bistarelli, S., Ceberio, M., Henderson, J. A., & Santini, F. Volume 100. Abstract argumentation frameworks to promote fairness and rationality in multi-experts multi-criteria decision making, pages 7–19. Springer International Publishing, 2018.

Paper doi abstract bibtex

In this work, we propose to model Multi-Experts Multi-CriteriaDecision-Making (MEMCDM) problems using Abstract Argumentation Frameworks. We specifically design our model so as to ensure fairness and rationality in the decision-making process. For instance, when, of two expert’s decisions, one is unfair, we impose an attack between these two decisions, forcing one of the two decisions out of the argumentation network’s resulting extensions. Similarly, we specifically put irrational decisions in opposition to force one out. In doing so, we aim to enable the prediction of decisions that are themselves fair and rational. Our model is illustrated on a toy example.

@inbook{
	11391_1417228,
	author = {Bistarelli, Stefano and Ceberio, Martine and Henderson, Joel A. and Santini, Francesco},
	title = {Abstract argumentation frameworks to promote fairness and rationality in multi-experts multi-criteria decision making},
	year = {2018},
	publisher = {Springer International Publishing},
	volume = {100},
	booktitle = {Studies in Systems, Decision and Control},
	abstract = {In this work, we propose to model Multi-Experts Multi-CriteriaDecision-Making (MEMCDM) problems using Abstract Argumentation Frameworks. We specifically design our model so as to ensure fairness and rationality in the decision-making process. For instance, when, of two expert’s decisions, one is unfair, we impose an attack between these two decisions, forcing one of the two decisions out of the argumentation network’s resulting extensions. Similarly, we specifically put irrational decisions in opposition to force one out. In doing so, we aim to enable the prediction of decisions that are themselves fair and rational. Our model is illustrated on a toy example.},
	keywords = {Computer Science (miscellaneous); Decision Sciences (miscellaneous); 2001; Automotive Engineering; Control and Systems Engineering; Control and Optimization; Social Sciences (miscellaneous)},
	url = {www.springer.com/series/13304},
	doi = {10.1007/978-3-319-61753-4_2},	
	pages = {7--19}
}

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