Author :
Cazenave, Tristan
Author_Institution :
LAMSADE, Univ. Paris-Dauphine, Paris, France
Abstract :
Some shortest path problems that can be solved using the A* algorithm have a large branching factor due to the combination of multiple choices at each move. Multiple sequence alignment and multi-agent pathfinding are examples of such problems. If the search can be stopped after each choice instead of being stopped at each combination of choices, it takes much less memory and much less time. The goal of the paper is to show that Partial Move A* is much better than A* for these problems when the branching factor is large due to a large combination of choices at each move. When there is such a large combination of choices at each move, Partial Move A* can yield large memory gains and speedups over regular A*.
Keywords :
multi-agent systems; branching factor; memory gain; multi agent pathfinding; multiple sequence alignment; shortest path problem; Approximation algorithms; DNA; Dynamic programming; Heuristic algorithms; Indexes; Iterative algorithm; Memory management; A*; iterative deepening; multi-agent pathfinding; multiple sequence alignment; transposition table;
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2010 22nd IEEE International Conference on
Conference_Location :
Arras
Print_ISBN :
978-1-4244-8817-9
DOI :
10.1109/ICTAI.2010.79