Real-time adaptive A* with depression avoidance

Carlos Hernández, Jorge A. Baier

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferencia

Resumen

Real-time search is a well known approach to solving search problems under tight time constraints. Recently, it has been shown that LSS-LRTA*, a well-known real-time search algorithm, can be improved when search is actively guided away of depressions. In this paper we investigate whether or not RTAA* can be improved in the same manner. We propose aRTAA* and daRTAA*, two algorithms based on RTAA* that avoid heuristic depressions. Both algorithms outperform RTAA* on standard path-finding tasks, obtaining better quality solutions when the same time deadline is imposed on the duration of the planning episode. We prove, in addition, that both algorithms have good theoretical properties.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011
Páginas193-194
Número de páginas2
EstadoPublicada - 2011
Evento4th International Symposium on Combinatorial Search, SoCS 2011 - Barcelona, Espana
Duración: 15 jul 201116 jul 2011

Otros

Otros4th International Symposium on Combinatorial Search, SoCS 2011
PaísEspana
CiudadBarcelona
Período15/07/1116/07/11

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    Hernández, C., & Baier, J. A. (2011). Real-time adaptive A* with depression avoidance. En Proceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011 (pp. 193-194)