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ABSTRACT
The critical resource that limits the application of best-first search is memory. We present a new class of best-first search algorithms that reduce the space complexity. The key idea is to store only the Open list of generated nodes, but not the Closed list of expanded nodes. The solution path can be recovered by a divide-and-conquer technique, either as a bidirectional or unidirectional search. For many problems, frontier search dramatically reduces the memory required by best-first search. We apply frontier search to breadth-first search of sliding-tile puzzles and the 4-peg Towers of Hanoi problem, Dijkstra's algorithm on a grid with random edge costs, and the A* algorithm on the Fifteen Puzzle, the four-peg Towers of Hanoi Problem, and optimal sequence alignment in computational biology.
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INDEX TERMS
Primary Classification:
I.
Computing Methodologies
I.2
ARTIFICIAL INTELLIGENCE
I.2.8
Problem Solving, Control Methods, and Search
Subjects:
Graph and tree search strategies
Keywords:
A* algorithm,
Dijkstra's algorithm,
Towers of Hanoi,
best-first search,
bidirectional search,
breadth-first search,
heuristic search,
sequence alignment,
sliding-tile puzzles
REVIEW
"Carlos Linares Lopez : Reviewer"
Currently, researchers are working to improve the performance of single-agent search algorithms in two ways: they are devising new ideas for deriving new search algorithms with lower asymptotic space complexities, and they are figuring out how to
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