| Revue: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560163 |
| ISSN: | 1405-5546 |
| Autores: | Filiberto, Yaima1 Bello, Rafael2 Nowe, Ann3 |
| Instituciones: | 1University of Camaguey, Camaguey. Cuba 2Universidad Central "Marta Abreu" de Las Villas, Santa Clara, Villa Clara. Cuba 3Vrije Universiteit Brussel, Brussel. Bélgica |
| Año: | 2018 |
| Periodo: | Abr-Jun |
| Volumen: | 22 |
| Número: | 2 |
| Paginación: | 537-546 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | 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. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial |
| Keyword: | Aggregating rankings, Personnel selection, Reinforcement learning, Artificial intelligence |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
