Package org.jgrapht.alg.interfaces
Interface AStarAdmissibleHeuristic<V>
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- Type Parameters:
V
- vertex type
- All Known Implementing Classes:
ALTAdmissibleHeuristic
public interface AStarAdmissibleHeuristic<V>
Interface for an admissible heuristic used in A* search.- Author:
- Joris Kinable, Jon Robison, Thomas Breitbart
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Method Summary
All Methods Instance Methods Abstract Methods Default Methods Modifier and Type Method Description double
getCostEstimate(V sourceVertex, V targetVertex)
An admissible "heuristic estimate" of the distance from $x$, the sourceVertex, to the goal (usually denoted $h(x)$).default <E> boolean
isConsistent(Graph<V,E> graph)
Returns true if the heuristic is a consistent or monotone heuristic wrt the providedgraph
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Method Detail
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getCostEstimate
double getCostEstimate(V sourceVertex, V targetVertex)
An admissible "heuristic estimate" of the distance from $x$, the sourceVertex, to the goal (usually denoted $h(x)$). This is the good guess function which must never overestimate the distance.- Parameters:
sourceVertex
- the source vertextargetVertex
- the target vertex- Returns:
- an estimate of the distance from the source to the target vertex
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isConsistent
default <E> boolean isConsistent(Graph<V,E> graph)
Returns true if the heuristic is a consistent or monotone heuristic wrt the providedgraph
. A heuristic is monotonic if its estimate is always less than or equal to the estimated distance from any neighboring vertex to the goal, plus the step cost of reaching that neighbor. For details, refer to https://en.wikipedia.org/wiki/Consistent_heuristic. In short, a heuristic is consistent iffh(u)≤ d(u,v)+h(v)
, for every edge $(u,v)$, where $d(u,v)$ is the weight of edge $(u,v)$ and $h(u)$ is the estimated cost to reach the target node from vertex u. Most natural admissible heuristics, such as Manhattan or Euclidean distance, are consistent heuristics.- Type Parameters:
E
- graph edges type- Parameters:
graph
- graph to test heuristic on- Returns:
- true iff the heuristic is consistent wrt the
graph
, false otherwise
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