ML Anthology

Scaling up WA* with Commitment and Diversity

David Furcy, Sven Koenig
IJCAI 2005 pp. 1521-1522
/ijcai/2005/furcy2005ijcai-scaling/

Abstract

Weighted A * (WA*) is a popular search technique that scales up A * while sacrificing solution quality. Recently, researchers have proposed two variants of WA*: KWA* adds diversity to WA*, and MSC-WA * adds commitment to WA*. In this paper, we demonstrate that there is benefit in combining them. The resulting MSC-KWA * scales up to larger domains than WA*, KWA * and MSC-WA*, which is rather surprising since diversity and commitment at first glance seem to be opposing concepts. 1

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Text

Furcy and Koenig. "Scaling up WA* with Commitment and Diversity." International Joint Conference on Artificial Intelligence, 2005.

Markdown

[Furcy and Koenig. "Scaling up WA* with Commitment and Diversity." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/furcy2005ijcai-scaling/)

BibTeX

@inproceedings{furcy2005ijcai-scaling,
  title     = {{Scaling up WA* with Commitment and Diversity}},
  author    = {Furcy, David and Koenig, Sven},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2005},
  pages     = {1521-1522},
  url       = {https://mlanthology.org/ijcai/2005/furcy2005ijcai-scaling/}
}