Heuristic search: It denotes a technique to reach goal state by choosing best promising state. It leads to goal state and this search is identified as heuristic search. The heuristic values are chosen for each node. It denotes that node that has low heuristic value is been chosen over another nodes. Goal: The objective is to find state sequence that would lead to final state. The numbers are been ordered from initial state that is unordered and it follows the productions. The count of tiles that are out of place denotes heuristic in problem. Algorithm for creating search tree: The algorithm is shown below: Step 1: Construct parent node by taking initial node Step 2: Check whether the node signifies a final state. Step 3: If step 2 fails, make child nodes that are possible states and could be attain by moving empty tile in parent nodes. Find heuristic value of states. Select node that has low heuristic value and move to step 2. Step 4: If step 2 is true, then algorithm constructed search tree. Stop construction of tree further.

Question

Want to see the full answer?

Answer 1

Question

Chapter 11, Problem 29CRP

Program Plan Intro

Heuristic search:

It denotes a technique to reach goal state by choosing best promising state.

It leads to goal state and this search is identified as heuristic search.

The heuristic values are chosen for each node.

It denotes that node that has low heuristic value is been chosen over another nodes.

Goal:

The objective is to find state sequence that would lead to final state.

The numbers are been ordered from initial state that is unordered and it follows the productions.

The count of tiles that are out of place denotes heuristic in problem.

Algorithm for creating search tree:

The algorithm is shown below:

Step 1:

Construct parent node by taking initial node

Step 2:

Check whether the node signifies a final state.

Step 3:

If step 2 fails, make child nodes that are possible states and could be attain by moving empty tile in parent nodes.

Find heuristic value of states.

Select node that has low heuristic value and move to step 2.

Step 4:

If step 2 is true, then algorithm constructed search tree.

Stop construction of tree further.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Students have asked these similar questions

Minimum Spanning Trees (MST): Finding a Minimum Spanning Tree for the following graph based on each of the following algorithm. You need to show the procedures step-by-step. You could directly draw the final MST but indicate the sequence of your search by writing a series of letters, i.e. (a), (b), (c)… under the edges of the MST. This type of answer is preferred. Or else, you need to draw a graph for each step separately. Kruskal’s algorithm. Prim’s algorithm (start with the node ‘ORD).

The Graph Data Structure is made up of nodes and edges. (A Tree Data Structure is a special kind of a Graph Data Structure). A Graph may be represented by an Adjacency Matrix or an Adjacency List. Through this exercise, you should be able to have a better grasp the Adjacency Matrix concept. You are expected to read about the Adjacency Matrix concept as well as the Adjacency List concept. Suppose the vertices A, B, C, D, E, F, G and H of a Graph are mapped to row and column indices(0,1,2,3,4,5,6,and 7) of a matrix (i.e. 2-dimensional array) as shown in the following table. Vertex of Graph Index in the 2-D Array Adjacency Matrix Representation of Graph A B 2 F 6. H 7 Suppose further, that the following is an Adjacency Matrix representing the Graph. 3 4 5. 6. 7 0. 1 1 1 1 01 1 01 1. 3 14 1 1 1 6. 1 Exercise: Show/Draw the Graph that is represented by the above Adjacency matrix. Upload the document that contains your result. (Filename: AdjacencyMatrixExercise.pdf) Notes: -The nodes of the…

Draw a tree with 14 vertices Draw a directed acyclic graph with 6 vertices and 14 edges Suppose that your computer only has enough memory to store 40000 entries. Which best graph data structure(s) – you can choose more than 1 -- should you use to store a simple undirected graph with 200 vertices, 19900 edges, and the existence of edge(u,v) is frequently asked? - Adjacency Matrix - Adjacency List - Edge List