A dynamic adaptive calibration of the CLONALG immune algorithm

María Cristina Riff, Elizabeth Montero

Producción científica: Contribución a los tipos de informe/libroContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

The control of parameters during the execution of bio-inspired algorithms is an open research area. In this paper, we propose a new parameter control strategy for the immune algorithm CLONALG. Our approach is based on reinforcement learning ideas. We focus our attention on controlling the number of clones and the number of selected cells which follow a mutation process for improvement. Their values allow a trade-off between intensification and diversification of the search. Our approach provides an efficient and low cost adaptive technique for parameter control. We use instances of the Travelling Salesman Problem that has been tackled before by using CLONALG. The results obtained are very encouraging.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009
Páginas187-193
Número de páginas7
DOI
EstadoPublicada - 1 dic. 2009
Evento2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009 - Klagenfurt, Austria
Duración: 24 sep. 200926 sep. 2009

Serie de la publicación

NombreProceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009

Conferencia

Conferencia2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009
País/TerritorioAustria
CiudadKlagenfurt
Período24/09/0926/09/09

Áreas temáticas de ASJC Scopus

  • Inteligencia artificial
  • Informática aplicada
  • Software
  • Ingeniería de control y sistemas

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