---
title: "Scaling up WA* with Commitment and Diversity"
authors:
  - "David Furcy"
  - "Sven Koenig"
doi: ""
url: "https://ijcai.org/proceedings/2005/284"
pdf: "https://ijcai.org/proceedings/2005/0284.pdf"
venue: "Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence"
year: 2005
pages: "1521-1521"
track: ""
keywords:
---

# Scaling up WA* with Commitment and Diversity

David Furcy, Sven Koenig

*Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence*, pages 1521-1521.

## 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.