Heuristic Search之Greedy Best First Search

    • Greedy Best-First Search
    • example
    • Whats wrong with GBFS
    • Compare to Uniform-Cost Search
    • 参考资料
    • CodeGBFS

本篇文章介绍Greedy Best Fisrt Search算法。实现GBFS算法时使用了上篇文章介绍的优先队列。下篇文章将尝试介绍著名的A star算法。

  • use heuristic function as evaluation function: f(n) = h(n)
  • always expands the node that is closest to the goal node
  • eats the largest chunk out of the remaining distance, hence, “greedy”

The following example is “Touring in Romania”, which is an actual problem for making a plan travelling from Arad to Bucharest, the aim that we use the lowest cost.

Heuristic Search之Greedy Best First Search_第1张图片

example

Touring in Romania: Heuristic

  • HSLD(n) = straight-line distance to Bucharest straight-line distance: Euclidean distance
  • distance to Bucharest because our goal is to be in Bucharest

Heuristic Search之Greedy Best First Search_第2张图片

[table]

  • HSLD(Bucharest) = 0
  • HSLD(Fagaras) = 176 < 211 driving distance
  • HSLD(n) cannot be computed from the problem description, it represents
    additional information

Heuristic Search之Greedy Best First Search_第3张图片

What’s wrong with GBFS?

for this problem: search proceeds straight to the goal node:

  • minimal search cost
  • but not the optimal path
  • UCS: numbers start from 0 and increase – tendency to expand earlier nodes –
    breadth-first tendency
  • UCS的介绍
  • GBFS: number start from high and decreases – tendency to expand later nodes
    – depth-first tendency

参考资料

  1. 数据结构与算法分析
  2. 大话数据结构
  3. AI planning 课程资料
  4. AI planning Vedio

Code(GBFS)

Path Found:

Arad(366)–>Sibiu(253)–>Fagaras(176)–>Bucharest(0).

package cn.edu.gdut.java.test;

import java.util.HashMap;
import java.util.Map;
import java.util.PriorityQueue;

/**
 * Created by HuGuodong on 2017/10/26.
 */

public class Graph {


    private Map graph;


    /**
     * test main
     *
     * @param args
     */
    public static void main(String[] args) {
        GBFS("Arad", "Bucharest");

    }

    /**
     * algorithm: Greedy Best First Search
     * Greedy Best-First Search
     * use heuristic function as evaluation function: f(n) = h(n)
     * always expands the node that is closest to the goal node
     * eats the largest chunk out of the remaining distance, hence, “greedy”
     * @param start start node
     * @param end   end node
     */
    public static void GBFS(String start, String end) {
        Graph roads = new Graph();
        roads.init();
        AdjList adjList = roads.graph.get(start);
        System.out.println("Greedy Best First Search Starts!");
        AdjNode startNode = findNode(adjList, start);
        System.out.print("start from node: \n" + start + "(" + startNode.cost + ")" + "-->");
        int totalCost = 0;
        while (adjList.size() > 0) {
            AdjNode nextNode = adjList.poll();
            int nodeCost = nextNode.cost;
            totalCost += nodeCost;

            System.out.print(nextNode.name + "(" + nodeCost + ")-->");
            adjList = roads.graph.get(nextNode.name);

            if (isExist(adjList, end)) {
                int lastNodeCost = adjList.poll().cost;
                totalCost += lastNodeCost;
                System.out.println(end + "(" + lastNodeCost + ").");
                System.out.println("find path! \ntotal cost is : " + totalCost);
                return;
            }
        }
    }

    /**
     * init Touring in Romania road map
     */
    public void init() {
        graph = new HashMap<>();

        String name = "Arad";
        int cost = 366;
        AdjList adjList = new AdjList();
        adjList.add(new AdjNode("Arad", 366));
        adjList.add(new AdjNode("Zerind", 374));
        adjList.add(new AdjNode("Sibiu", 253));
        adjList.add(new AdjNode("Timisoara", 329));
        graph.put(name, adjList);

        name = "Sibiu";
        adjList = new AdjList();
        adjList.add(new AdjNode("Fagaras", 176));
        adjList.add(new AdjNode("Rimnicu", 193));
        adjList.add(new AdjNode("Rimnicu", 380));
        graph.put(name, adjList);

        name = "Fagaras";
        adjList = new AdjList();
        adjList.add(new AdjNode("Sibiu", 253));
        adjList.add(new AdjNode("Bucharest", 0));
        graph.put(name, adjList);
    }

    /**
     * whether the node name is in the adjlist
     *
     * @param adjList
     * @param name
     * @return
     */
    public static boolean isExist(AdjList adjList, String name) {
        for (AdjNode n :
                adjList) {
            if (n.name.equals(name)) {
                return true;
            }
        }
        return false;
    }

    /**
     * find a node by name
     *
     * @param adjList
     * @param name
     * @return
     */
    public static AdjNode findNode(AdjList adjList, String name) {
        for (AdjNode n :
                adjList) {
            if (n.name.equals(name)) {
                return n;
            }
        }
        return null;
    }

}

/**
 * adjacent list
 * priority queue
 */
class AdjList extends PriorityQueue {

}

/**
 * adjacent node
 */
class AdjNode implements Comparable {
    String name;
    int cost;

    public AdjNode(String name, int cost) {
        this.name = name;
        this.cost = cost;
    }

    @Override
    public int compareTo(AdjNode o) {
        return Integer.compare(cost, o.cost);
    }

    @Override
    public String toString() {
        return "AdjNode{" +
                "name='" + name + '\'' +
                ", cost=" + cost +
                '}';
    }
}

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