package aima.core.search.uninformed; import java.util.Comparator; import aima.core.search.framework.GraphSearch; import aima.core.search.framework.Node; import aima.core.search.framework.PrioritySearch; import aima.core.search.framework.QueueSearch; /** * Artificial Intelligence A Modern Approach (3rd Edition): Figure 3.14, page * 84.
*
* *
 * function UNIFORM-COST-SEARCH(problem) returns a solution, or failure
 *   node <- a node with STATE = problem.INITIAL-STATE, PATH-COST = 0
 *   frontier <- a priority queue ordered by PATH-COST, with node as the only element
 *   explored <- an empty set
 *   loop do
 *      if EMPTY?(frontier) then return failure
 *      node <- POP(frontier) // chooses the lowest-cost node in frontier
 *      if problem.GOAL-TEST(node.STATE) then return SOLUTION(node)
 *      add node.STATE to explored
 *      for each action in problem.ACTIONS(node.STATE) do
 *          child <- CHILD-NODE(problem, node, action)
 *          if child.STATE is not in explored or frontier then
 *             frontier <- INSERT(child, frontier)
 *          else if child.STATE is in frontier with higher PATH-COST then
 *             replace that frontier node with child
 * 
* * Figure 3.14 Uniform-cost search on a graph. The algorithm is identical to the * general graph search algorithm in Figure 3.7, except for the use of a * priority queue and the addition of an extra check in case a shorter path to a * frontier state is discovered. The data structure for frontier needs to * support efficient membership testing, so it should combine the capabilities * of a priority queue and a hash table. * * @author Ciaran O'Reilly * @author Ruediger Lunde * */ public class UniformCostSearch extends PrioritySearch { public UniformCostSearch() { this(new GraphSearch()); } public UniformCostSearch(QueueSearch search) { super(search, createPathCostComparator()); } private static Comparator createPathCostComparator() { return new Comparator() { public int compare(Node node1, Node node2) { return (new Double(node1.getPathCost()).compareTo(new Double(node2 .getPathCost()))); } }; } }