I need some help with my A* algorithm implementation. When I run the algorithm it does find the goal, but the path is definately not the shortest :-P
Here is my code, please help me spot the bugs! I think it might be the reconstruct path that is my problem but I'm not sure.
public class Pathfinder {
public List<Node> aStar(Node start, Node goal, WeightedGraph graph) {
Node x, y;
int tentative_g_score;
boolean tentative_is_better;
FScoreComparator comparator = new FScoreComparator();
List<Node> closedset = new ArrayList<Node>();
Queue<Node> openset = new PriorityQueue<Node>(10, comparator);
openset.add(start);
start.g_score = 0;
start.h_score = heuristic_cost_estimate(start, goal);
start.f_score = start.h_score;
while (!openset.isEmpty()) {
x = openset.peek();
if (x == goal) {
return reconstruct_path(goal);
}
x = openset.remove();
closedset.add(x);
for (Edge e : graph.adj(x)) {
if (e.v == x) {
y = e.w;
} else {
y = e.v;
}
if (closedset.contains(y) || y.illegal) {
continue;
}
tentative_g_score = x.g_score + e.weight;
if (!openset.contains(y)) {
openset.add(y);
tentative_is_better = true;
} else if (tentative_g_score < y.g_score) {
tentative_is_better = true;
} else {
tentative_is_better = false;
}
if (tentative_is_better) {
y.g_score = tentative_g_score;
y.h_score = heuristic_cost_estimate(y, goal);
y.f_score = y.g_score + y.h_score;
y.parent = x;
}
}
}
return null;
}
private int heuristic_cost_estimate(Node start, Node goal) {
return Math.abs(start.x - goal.x) + Math.abs(start.y - goal.y);
}
private List<Node> reconstruct_path(Node current_node) {
List<Node> result = new ArrayList<Node>();
while (current_node != null) {
result.add(current_node);
current_node = current_node.parent;
}
return result;
}
private class FScoreComparator implements Comparator<Node> {
public int compare(Node n1, Node n2) {
if (n1.f_score < n2.f_score) {
return 1;
} else if (n1.f_score > n2.f_score) {
return -1;
} else {
return 0;
}
}
}
}
Thanks to everyone for all the great answers! My A* algorithm now works perfectly thanks to you guys! :-)
This was my first post and this forum is really amazing!
Here A* Search Algorithm comes to the rescue. What A* Search Algorithm does is that at each step it picks the node according to a value-'f' which is a parameter equal to the sum of two other parameters – 'g' and 'h'. At each step it picks the node/cell having the lowest 'f', and process that node/cell.
To summarize, A* gives an optimal solution if the heuristic is admissable (meaning it never overestimates the cost).
A* is an informed search algorithm, or a best-first search, meaning that it is formulated in terms of weighted graphs: starting from a specific starting node of a graph, it aims to find a path to the given goal node having the smallest cost (least distance travelled, shortest time, etc.).
Admissibility. A search algorithm is admissible if it is guaranteed to find a minimal path to a solution whenever such a solution exists. Breadth first search is admissible, because it looks at every state at level n before considering any state at level n+1.
You are changing the priority of an element in the PriorityQueue
after having inserted it. This isn't supported, as the priority queue isn't aware that an object has changed. What you can do is remove and re-add the object when it changes.
The priority is changed in the line: y.f_score = y.g_score + y.h_score;
. This line happens after adding y
to the priority queue. Note that simply moving the line openset.add(y);
to after calculating the cost won't be enough, since y
may have been added in a previous iteration.
It also isn't clear from your code whether the heuristic you used is admissible. If it isn't it will also cause you to get suboptimal paths.
Finally, a performance note: The contains
method on ArrayList
and PriorityQueue
takes linear time to run, which will make the running time of your implememtation non-optimal. You can improve this by adding boolean properties to the nodes to indicate if they are in the closed/open sets, or by using a set data structure.
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