k-order additive discrete fuzzy measures and their representation
Fuzzy Sets and Systems - Special issue on fuzzy measures and integrals
Alternative representations of discrete fuzzy measures for decision making
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - Special issue on fuzzy measures and integrals in subjective evaluation
The Choquet integral for the aggregation of interval scales in multicriteria decision making
Fuzzy Sets and Systems - Special issue: Preference modelling and applications
Uncertainty and Information: Foundations of Generalized Information Theory
Uncertainty and Information: Foundations of Generalized Information Theory
On the polytope of non-additive measures
Fuzzy Sets and Systems
Construction of aggregation functions from data using linear programming
Fuzzy Sets and Systems
On the structure of the k-additive fuzzy measures
Fuzzy Sets and Systems
On the robustness for the Choquet integral
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Learning monotone nonlinear models using the choquet integral
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Learning Choquet-Integral-Based Metrics for Semisupervised Clustering
IEEE Transactions on Fuzzy Systems
| Hi-index | 0.20 |
We study the problem of the Choquet integral maximization for the case when preferences of the decision maker do not define a unique capacity but rather some convex set. We introduce a robust version of the problem based on the minimax-regret criterion and construct a global optimization algorithm. It is shown that the decision rule based on regret minimization over a set of capacities is equivalent to maximization of the Choquet integral with respect to a certain capacity belonging to this set. We compare our method to various capacity identification approaches developed in the literature and provide a semantic interpretation in terms of information value.