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private Function<Node, Double> heuristic; public GBFS(Function<Node, Double> heuristic) { this.heuristic = heuristic; } public Node search(Node start, Predicate<Node> endPredicate) { //Check if the start node is the endPredicate if (endPredicate.test(start)) return start; //The queue containing all the nodes we have to search for StablePriorityQueue<Double, Node> nodeQueue = new StablePriorityQueue<>(); //Add the start node as the head. The priority does not matter since we remove it anyway. nodeQueue.add(new Pair<>(heuristic.apply(start), start)); //Adjacent, definition from the handbook.pdf contain all neighbors. //That means, that we would search in a node which we already searched for at another position. //Because of the insertion and lookup time O(1) in both situations, we chose the HashSt. HashSet<Node> checkedNodes = new HashSet<>(); //Insert the start node into the hashset, since we are using it checkedNodes.add(start); //Repeat till we have no element in the queue left. while (nodeQueue.size() > 0) { Pair<Double, Node> currentNode = nodeQueue.remove(); if (endPredicate.test(currentNode.s)) return currentNode.s; //Nothing found. Add all it's children else currentNode.s.adjacent().stream() //Get the stream .filter(node -> !checkedNodes.contains(node)) //Filter only the nodes we did not visit yet. .forEach(node -> { nodeQueue.add(new Pair<>(heuristic.apply(node), node)); //Add the node to the priority queue to search for the result. checkedNodes.add(node); //Add the node to the hashset, so that we do not search for that again. }); } //We cant reach that state, but just in case return null. return null; } |