We present a new algorithm called A*+BFHS for solving problems with unit-cost operators where A* and IDA* fail due to memory limitations and/or the existence of many distinct paths between the same pair of nodes. A*+BFHS is based on A* and breadth-first heuristic search (BFHS). A*+BFHS combines advantages from both algorithms, namely A*'s node ordering, BFHS's memory savings, and both algorithms' duplicate detection. On easy problems, A*+BFHS behaves the same as A*. On hard problems, it is slower than A* but saves a large amount of memory. Compared to BFIDA*, A*+BFHS reduces the search time and/or memory requirement by several times on a variety of planning domains
Although the heuristic search algorithm A* is well-known to be optimally efficient, this result expl...
In the past few years, new very successful bidirectional heuristic search algorithms have been propo...
We present a new algorithm to reduce the space complexity of heuristic search. It is most effective ...
Breadth-first heuristic search (BFHS) is a classic algorithm for optimally solving heuristic search ...
AbstractRecent work shows that the memory requirements of A* and related graph-search algorithms can...
Recent work shows that the memory requirements of A * and related graph-search algorithms can be red...
Heuristic search is a successful approach to cost-optimal planning. Bidirectional heuristic search a...
This paper describes a new admissible tree search algorithm called Iterative Threshold Search (ITS)...
This paper describes a new admissible tree search algorithm called Iterative Threshold Search (ITS)....
This paper describes a new admissible tree search algorithm called Iterative Threshold Search (ITS)....
This paper examines the following statements about heuristic search, which are commonly held to be t...
Although the heuristic search algorithm A * is well-known to be optimally efficient, this result exp...
AbstractRecent work shows that the memory requirements of A* and related graph-search algorithms can...
Heuristic search is a fundamental technique for solving problems in artificial intelligence. However...
We present an algorithm that exploits the complimentary benefits of best-first search (BFS) and dept...
Although the heuristic search algorithm A* is well-known to be optimally efficient, this result expl...
In the past few years, new very successful bidirectional heuristic search algorithms have been propo...
We present a new algorithm to reduce the space complexity of heuristic search. It is most effective ...
Breadth-first heuristic search (BFHS) is a classic algorithm for optimally solving heuristic search ...
AbstractRecent work shows that the memory requirements of A* and related graph-search algorithms can...
Recent work shows that the memory requirements of A * and related graph-search algorithms can be red...
Heuristic search is a successful approach to cost-optimal planning. Bidirectional heuristic search a...
This paper describes a new admissible tree search algorithm called Iterative Threshold Search (ITS)...
This paper describes a new admissible tree search algorithm called Iterative Threshold Search (ITS)....
This paper describes a new admissible tree search algorithm called Iterative Threshold Search (ITS)....
This paper examines the following statements about heuristic search, which are commonly held to be t...
Although the heuristic search algorithm A * is well-known to be optimally efficient, this result exp...
AbstractRecent work shows that the memory requirements of A* and related graph-search algorithms can...
Heuristic search is a fundamental technique for solving problems in artificial intelligence. However...
We present an algorithm that exploits the complimentary benefits of best-first search (BFS) and dept...
Although the heuristic search algorithm A* is well-known to be optimally efficient, this result expl...
In the past few years, new very successful bidirectional heuristic search algorithms have been propo...
We present a new algorithm to reduce the space complexity of heuristic search. It is most effective ...