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Computación y Sistemas
versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546
Resumen
FILIBERTO, Yaima; BELLO, Rafael y NOWE, Ann. A New Method For Personnel Selection Based On Ranking Aggregation Using A Reinforcement Learning Approach. Comp. y Sist. [online]. 2018, vol.22, n.2, pp.537-546. Epub 21-Ene-2021. ISSN 2007-9737. https://doi.org/10.13053/cys-22-2-2353.
In this paper propose a new approach to the problem of aggregating rankings for obtaining an overall ranking. This is also referred to as the aggregation ranking in the personnel selection problem. Our approach is based on a distance measure between the individual and the overall ranking, and looks for the solution that minimizes the disagreement between the input rankings and the resulting aggregation. The method uses a reinforcement learning approach to build the aggregation and its performance and comparison with other approaches shows promising results.
Palabras llave : Aggregating rankings; personnel selection; reinforcement learning.