Title
Robustness analysis for decision under uncertainty with rule-based preference model
Abstract
We introduce Robust Ordinal Regression to decision under uncertainty.We propose an integrated framework for robustness analysis with the rule-based preference model.We formulate the procedures for deriving a univocal classification of acts.We account for different types of indirect preference information.We consider group decision under uncertainty with Dominance-based Rough Set Approach. We consider decision under uncertainty as a multi-attribute classification problem where a set of acts is described by outcomes gained with given probabilities. The Decision Maker (DM) provides desired classification for a small subset of reference acts. Such preference information is structured using Dominance-based Rough Set Approach (DRSA), and the resulting lower approximations of the quality class unions are used as an input for construction of an aggregate preference model. We induce all minimal-cover sets of rules being compatible with the non-ambiguous assignment examples, and satisfying some additional requirements that may be imposed by the DM. Applying such compatible instances of the preference model on a set of all acts, we draw conclusions about the certainty of recommendation assured by different minimal-cover sets of rules. In particular, we analyze the diversity of class assignments, assignment-based preference relations, and class cardinalities. Then, we solve an optimization problem to get a¿univocal (precise) classification for all acts, taking into account the robustness concern. This optimization problem admits incorporation of additional indirect and imprecise preferences in form of desired class cardinalities and assignment-based pairwise comparisons. Finally, we extend the proposed approach to group decision under uncertainty. We present a set of indicators and outcomes giving an insight into the spaces of consensus and disagreement between the DMs.
Year
DOI
Venue
2016
10.1016/j.ins.2015.07.062
Information Sciences: an International Journal
Keywords
Field
DocType
Decision under uncertainty,Classification,Dominance-based rough set approach,Robustness analysis,Univocal recommendation,Group decision
Pairwise comparison,Mathematical optimization,Rule-based system,Cardinality,Rough set,Robustness (computer science),Ordinal regression,Artificial intelligence,Optimization problem,Machine learning,Dominance-based rough set approach,Mathematics
Journal
Volume
Issue
ISSN
328
C
0020-0255
Citations 
PageRank 
References 
3
0.38
27
Authors
3
Name
Order
Citations
PageRank
MiłOsz KadzińSki11756.46
Roman Slowinski25561516.06
Salvatore Greco33977266.79