Consider the same maze shown above with the same start and goal nodes. Let the heuristic cost of every node to reach G be: Table of heuristic values hh(n) A 5.1 B 4.1 C 3.9 D 4 E 2.2
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- find the time efficiency using 5 steps plan: Graph Complete(A[0..n-1,0..n-1]) Input:Adjacency matrix (A[0..n-1,0..n-1]) output: 1(true) if n=1 return 1 else if not Graphcomplete (A[0..n-2,0..n-2]) return 0 else for j <--- 0 to n-2 do if A[n-1,j] =0 return 0 return 1Use of Matching for Edge ColouringEdges in a matching can share the same colour since matching in a graph is defined as the collection of non-adjacent edges. As a result, we can create an algorithm based on this idea using the below stages. 1. Input: G = (V, E)2. Output: Minimal edge coloring of G3. color ← 04. while G = ∅$5. find maximal matching M of G6. color all M vertices with color7. G ← G − M8. color ← color + 1implementation of PythonConsider a digraph with x vertices. What is the maximal finishing time (whatever the arcs are, considering ANY POSSIBLE digraph)? return the maximal finishing time for each case of vertices x = ...(i) x = 101(ii) x = 46(iii) x = 100(iv) x = 22
- I need to use Dijkstra’s algorithm to find the shortest path from a to z for the graph. Please helpThere are many applications of Shortest Path Algorithm. Consider the problem of solving a jumbled Rubik's Cube in the fewest number of moves. I claim that this problem can be solved using a Shortest Path Algorithm. Determine whether this statement is TRUE or FALSE. NOTE: if you want to check if this statement is TRUE, think about how the Rubik's Cube Problem can be represented as a graph. What are the vertices? Which pairs of vertices are connected with edges? What is your source vertex and what is your destination vertex? How would Dijkstra's Algorithm enable you to find the optimal sequence of moves to solve a jumbled cube in the fewest number of moves?Don't need to solve question 1. Use the graph in question 1 to solve question 3 part (a). Thanks!
- Consider navigating the maze shown below. N (М G 1. S 2. A 3. B 4. F 8. 5. H 6. D L 7. P (2 G 2 2 4 C E P 2 2 2 A S B FL The maze is represented as a graph with edge costs as shown on the edges. The edge cost is 1 for all edges where the cost is not shown. Let S be the initial state and G be the goal state. List the first 8 vertices expanded by Uniform Cost Search (enter the single letter label of a node). K 2 2 J 2 D HSuppose that you have a maze search problem. From each numbered square in the maze, youmay move that exact number of squares horizontally or vertically in a straight line. Startingat a particular square (e.g. the top-left corner), find a path to the goal square marked "G".3 4 1 3 1 3 3 3 G 2 3 1 2 2 3 4 2 3 3 3 4 1 4 3 2 Describe the State Space components of this problem. Then solve the problem using breadthirst search and the depth first search. Hint: Indicate the changes to the Open and ClosedQueues in solving this problem for each type of search.Consider navigating the maze shown below. 4. 1. S 2. A 3. 5. 6. 7. L N 8. M 2 2 4 C E 2 P 2 2 A G The maze is represented as a graph with edge costs as shown on the edges. The edge cost is 1 for all edges where the cost is not shown. Let S be the initial state and G be the goal state. List the first 8 vertices expanded by Uniform Cost Search (enter the single letter label of a node). S B K FL 2 J 2 2 D H