Abstract
Pathfinding in uniform-cost grid environments is a problem commonly found in application areas such as robotics and video games. The state-of-the-art is dominated by hierarchical pathfinding algorithms which are fast and have small memory overheads but usually return suboptimal paths. In this paper we present a novel search strategy, specific to grids, which is fast, optimal and requires no memory overhead. Our algorithm can be described as a macro operator which identifies and selectively expands only certain nodes in a grid map which we call jump points. Intermediate nodes on a path connecting two jump points are never expanded. We prove that this approach always computes optimal solutions and then undertake a thorough empirical analysis, comparing our method with related works from the literature. We find that searching with jump points can speed up A*by an order of magnitude and more and report significant improvement over the current state of the art.
| Original language | English |
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| Title of host publication | Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence |
| Place of Publication | Menlo Park, Calif |
| Publisher | Association for the Advancement of Artificial Intelligence (AAAI) |
| Pages | 1114-1119 |
| Number of pages | 6 |
| Volume | 2 |
| ISBN (Print) | 9781577355090 |
| Publication status | Published - 2011 |
| Externally published | Yes |
| Event | AAAI Conference on Artificial Intelligence 2011 - Hyatt Regency, San Francisco, United States of America Duration: 7 Aug 2011 → 11 Aug 2011 Conference number: 25th http://www.aaai.org/Conferences/AAAI/aaai11.php |
Conference
| Conference | AAAI Conference on Artificial Intelligence 2011 |
|---|---|
| Abbreviated title | AAAI 2011 |
| Country/Territory | United States of America |
| City | San Francisco |
| Period | 7/08/11 → 11/08/11 |
| Internet address |