Improving MPGAA for extended visibility ranges

Carlos Hernández, Jorge A. Baier

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

Resumen

Multipath Generalized Adaptive A (MPGAA) is an A-based incremental search algorithm for dynamic terrain that can outperform D for the (realistic) case of limited visibility ranges. A first contribution of this paper is a brief analysis studying why MPGAA has poor performance for extended visibility ranges, which concludes that MPGAA carries out an excessive number of heuristic updates. Our second contribution is a method to reduce the number of heuristic updates that preserves optimality. Finally, a third contribution is a variant of MPGAA, MPGAA-back, which we show outperforms MPGAA and D on a wide range of dynamic grid pathfinding scenarios, and visibility ranges.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 27th International Conference on Automated Planning and Scheduling, ICAPS 2017
EditorialAAAI press
Páginas149-153
Número de páginas5
ISBN (versión digital)9781577357896
EstadoPublicada - 2017
Evento27th International Conference on Automated Planning and Scheduling, ICAPS 2017 - Pittsburgh, Estados Unidos
Duración: 18 jun 201723 jun 2017

Conferencia

Conferencia27th International Conference on Automated Planning and Scheduling, ICAPS 2017
PaísEstados Unidos
CiudadPittsburgh
Período18/06/1723/06/17

Áreas temáticas de ASJC Scopus

  • Inteligencia artificial
  • Informática aplicada
  • Gestión y sistemas de información

Huella Profundice en los temas de investigación de 'Improving MPGAA<sup>∗</sup> for extended visibility ranges'. En conjunto forman una huella única.

  • Citar esto

    Hernández, C., & Baier, J. A. (2017). Improving MPGAA for extended visibility ranges. En Proceedings of the 27th International Conference on Automated Planning and Scheduling, ICAPS 2017 (pp. 149-153). AAAI press.