AbstractC. Hernandez, X. Sun, S. Koenig and P. Meseguer. Tree Adaptive A*. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 123-130, 2011.
Abstract: Incremental heuristic search algorithms can solve sequences of similar search problems potentially faster than heuristic search algorithms that solve each search problem from scratch. So far, there existed incremental heuristic search algorithms (such as Adaptive A*) that make the h-values of the current A* search more informed, which can speed up future A* searches, and incremental heuristic search algorithms (such as D* Lite) that change the search tree of the current A* search to the search tree of the next A* search, which can be faster than constructing it from scratch. In this paper, we present Tree Adaptive A*, which applies to goal-directed navigation in unknown terrain and builds on Adaptive A* but combines both classes of incremental heuristic search algorithms in a novel way. We demonstrate experimentally that it can run faster than Adaptive A*, Path Adaptive A* and D* Lite, the top incremental heuristic search algorithms in the context of goal-directed navigation in unknown grids. Errata: The statement 'Figure 4(h) shows that the fifth A* search of Tree-AA* terminates already when it is about to expand F5' should read 'Figure 4(h) shows that the sixth A* search of Tree-AA* terminates already when it is about to expand E5'.
Download the paper in pdf.
Many publishers do not want authors to make their papers available electronically after the papers have been published. Please use the electronic versions provided here only if hardcopies are not yet available. If you have comments on any of these papers, please send me an email! Also, please send me your papers if we have common interests.
This page was automatically created by a bibliography maintenance system that was developed as part of an undergraduate research project, advised by Sven Koenig.