This contribution considers the choice of a coalition on the basis of its competence, with a constraint on the cost of the coalition itself. First of all, we consider a set C of competencies and assume that each expert is characterized by one or more of them.We define a suitable set function in order to evaluate the competence of each coalition. This set function turns out to be a non-additive measure, see [3, 5]. As a first proposal, competencies will be represented by Boolean quantities, meaning that an expert can only have or not have a certain competence. The extension to a degree of competence between zero and one is straightforward. Moreover, each coalition is associated with a cost that depends on its size and the cost of each expert. In this form, the optimization problem is that of maximizing the coalition competence by respecting a cost constraint. We describe some examples in order to clarify our contribution.We also propose a multi-objective approach where one will try to maximize competence and minimize cost. We compute the Pareto front and compare the results of the two approaches.

Competence-Based Coalition Choice, a Non-additive Approach

Giove Silvio
2023-01-01

Abstract

This contribution considers the choice of a coalition on the basis of its competence, with a constraint on the cost of the coalition itself. First of all, we consider a set C of competencies and assume that each expert is characterized by one or more of them.We define a suitable set function in order to evaluate the competence of each coalition. This set function turns out to be a non-additive measure, see [3, 5]. As a first proposal, competencies will be represented by Boolean quantities, meaning that an expert can only have or not have a certain competence. The extension to a degree of competence between zero and one is straightforward. Moreover, each coalition is associated with a cost that depends on its size and the cost of each expert. In this form, the optimization problem is that of maximizing the coalition competence by respecting a cost constraint. We describe some examples in order to clarify our contribution.We also propose a multi-objective approach where one will try to maximize competence and minimize cost. We compute the Pareto front and compare the results of the two approaches.
2023
Applications of Artificial Intelligence and Neural Systems to Data Science
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5056502
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