In a solitaire game, we start from HTH to reach THT. We can flip the center coin at any time We can also flip either end coin if the other two cuins show the same tace. Using Backtracking technique with the strategy that flipping left coin before right coin and fipping right coin before centre coin, the state-spoce tree after step 1is shown in Figure K. What is the state-space tree after the second step? HTH HHH Figure. K HTH HTH HTH HTH HHH HHH HHH HHH HHT THH HTH HHT THH Figure. W Figure. X Figure, Y Figure. Z Select one Oa. Figure Y Ob. Figure Z e Figure X d. Figure W

In a solitaire game, we start from HTH to reach THT. We can flip the center coin at any time We can also flip either end coin if the other two cuins show the same tace. Using Backtracking technique with the strategy that flipping left coin before right coin and fipping right coin before centre coin, the state-spoce tree after step 1is shown in Figure K. What is the state-space tree after the second step? HTH HHH Figure. K HTH HTH HTH HTH HHH HHH HHH HHH HHT THH HTH HHT THH Figure. W Figure. X Figure, Y Figure. Z Select one Oa. Figure Y Ob. Figure Z e Figure X d. Figure W

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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You are given the following game tree. The top level is a maximizing level. A B D E F G 10 12 13 16 13 10 17 6 а. Give the values calculated by minimax for all the nodes labeled by letters in the tree. Do not use alpha-beta pruning. For example, the answer for node D is 12 so you will write D:12 and do the same for all the other nodes. b. Indicate which labeled nodes of the tree will be pruned by alpha-beta pruning.
For straight-line distance heuristic, draw the search tree after expansion of each node until the termination of the algorithm for: a) Greedy best-first search (label all node with their h values). What is the solution (list of visited cities) found by the algorithm? b) A* search (label all nodes with their f values). What is the solution (list of visited cities) found by the algorithm?
Describe in as few as one or as many as a few words as possible the differences between a decision tree and a random forest. In utilising the random forest technique, what are some ways that we may ensure that randomization will occur twice?
In a game tree, there are 2 players (Player 1 and Player 2). And they each have 2 options (Yes and No) and they each play three times sequentially - starting with player 1 first. How do you create the normal form from this game tree?
Question 8 Greedy best-fırst search is equivalent to A* search with all step costs set to 0. O True O False Question 9 If you had implemented Uniform Cost Search (the graph search version) in Programming Assignment 1, it would have found an optimal solution. (You may assume that the path costs are kept with the nodes on the frontier and explored lists and checked when comparing newly generated states to what has been seen before.) O True O False Question 10 A* search with an admissible heuristic always expands fewer nodes than depth-first search. O True O False
we concretize the game tree algorithms with an iterator abstraction.In this exercise use the following state changing functions instead:move(v) Iterates all the possible moves from node v of playerlabel(v) and returns nil when they are exhausted.apply(v, m) Returns the successor node of v for move m.cancel(u, m) Yields the parent node of u when move m is taken back.You can assume that a move is reversible (i.e. v = cancel(apply(v, m), m))
a. For the graph below, give the order in which Dijkstra’s Algorithm would visit each vertex, starting from vertex A. 3 2 B F A G 4 ( E 4 D H 4 b. Change one of the weights in the graph so that the shortest paths tree returned by Dijkstra's is not correct. Hint: we showed in class that Dijkstra’s returns the correct SPT as long as all edges are non- negative. Set the weight of the edge connecting vertex . and vertex to c. Suppose we use the following heuristic: h(A) = 2 h(B) = 2 h(C) = 20 h(D) = 2 h(E) = 6 h(F) = 2 h(G) = 0 2 %3D h(H) %3D Recall that A* is just Dijkstra’s algorithm, except that vertices are given a priority equal to the sum of their Dijkstra priority (distance from the source) plus the heuristic distance, and also that we quit when the target is visited. Give the path (not order visited) that A* returns from A to G, you may not need all of the blanks: _A_ 2.
Given: 13-Node Graph. Generate the A* from Node A to Node B. Solve the f(n) = g(n) + h(n) from Node A to Node B where n = Node RV. Give the value of f(n) based on the generated A* from Node A to Node B. A 71 Dz 75/ 118 T O 140 70 75 D 151 OM S 120 80 Straight-Line Distance to Node B A to B - 360 B to B-0 C to B-150 D to B-240 F to B-170 L to B-240 M to B-240 O to B-380 P to B-100 RV to B-190 S to B-250 T to B-325 Z to B-370 99 RV 97 146 C D 138 F e d P 101 211 B
Correct answer will be upvoted else Multiple Downvoted. Computer science. You are given n chains of lengths l1,l2,… ,ln. You intend to fabricate a tree utilizing some of them. Every vertex of the tree is either white or dark. The tree at first just has a white root vertex. All chains at first comprise just of white vertices. You can take one of the chains and interface any of its vertices to any white vertex of the tree with an edge. The chain turns out to be important for the tree. The two endpoints of this edge become dark. Each chain can be utilized close to once. A few chains can be left unused. The distance between two vertices of the tree is the number of edges on the most brief way between them. Assuming there is essentially k white vertices in the subsequent tree, the worth of the tree is the distance between the root and the k-th nearest white vertex. What's the base worth of the tree you can get? In case it is absolutely impossible to construct…
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8. Compute a two-level decision tree using the greedy approach described in this chapter. Use the classification error rate as the criterion for splitting. What is the overall error rate of the induced tree? Note: To determine the test condition at the root note, you first need to computer the error rates for attributes X, Y, and Z. For attribute X the corresponding counts are: c1 60 c2 60 1 40 40 For Y the coresponding counts are: c1 40 60 c2 60 40 For Z the conesponding counts are: c1 30 70 c2 70 30 1 following set of attributes and attributevalues: