Artificial Intelligence: A Modern Approach
3rd Edition
ISBN: 9780136042594
Author: Stuart Russell, Peter Norvig
Publisher: Prentice Hall
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Chapter 5, Problem 7E
Explanation of Solution
Assertion
- Consider a MIN node whose children are terminal nodes.
- If MIN plays suboptimally, then the value of the node is greater than or equal to the value it would have if MIN played optimally...
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Students have asked these similar questions
Describe how the minimax and alpha–beta algorithms change for two-player, non-zero-sum games in which each player has a distinct utility function and both utility functions are known to both players. If there are no constraints on the two terminal utilities, is it possible for any node to be pruned by alpha–beta? What if the player’s utility functions on any state differ by at most a constant k
, making the game almost cooperative?
Consider the same house rent prediction problem where you are supposed to predict price
of a house based on just its area. Suppose you have n samples with their respective areas,
x(1), x(2), ... , x(n), their true house rents y(1), y(2),..., y(n). Let's say, you train a linear regres-
sor that predicts f(x()) = 00 + 01x(e). The parameters 6o and 0, are scalars and are learned
by minimizing mean-squared-error loss with L2-regularization through gradient descent with
a learning rate a and the regularization strength constant A. Answer the following questions.
1. Express the loss function(L) in terms of x), y@), n, 0, 01, A.
2. Compute L
3. Compute
4. Write update rules for 6, and O1
Which of the following statement is TRUE about overfitting problems?
It is impossible for regression models to have overfitting problems.
Increasing the depth of tree might cause overfitting problems in decision tree learning.
Overfitting problems can be reduced by decreasing the value of k in k-NN algorithm.
If a model has high training set error and low testing set error, the model overfits.
Chapter 5 Solutions
Artificial Intelligence: A Modern Approach
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- Consider the following training data set Y No. Of C1 No of C2 F 0. 10 F 4 2 2 F 6. Compute a two-level decision tree using the greedy approach described in the class. Use the classification error rate as the criterion for splitting. What is the overall error rate of the induced tree? Compute the generalization error rate of the tree using the optimistic approach and pessimisticarrow_forwardConsider the same house rent prediction problem where you are supposed to predict price of a house based on just its area. Suppose you have n samples with their respective areas, x(¹), x(²),...,x(n), their true house rents y(¹), y(2),..., y(n). Let's say, you train a linear regres- sor that predicts f(x)) = 0 + 0₁x). The parameters, and 0₁ are scalars and are learned by minimizing mean-squared-error loss with L1-regularization through gradient descent with a learning rate a and the regularization strength constant A. Answer the following questions. 1. Express the loss function(L) in terms of x(i),y(i), n, 00, 01, X. 2. Compute L 200 ƏL 3. Compute 20₁ 4. Write update rules for 0o and 0₁ Hint: d|w| dw undefined -1 w>0 w=0 w <0arrow_forwardAlgorithm for Alpha-beta pruning using minimax.Minimax-Alpha-Beta(v, α, β)in: node v; alpha value α; beta value βout: utility value of node varrow_forward
- Calculate the optimal value of the decision parameter p in the Bresenham's circle drawing algorithm. The stepwise procedure for implementing Bresenham's algorithm for circle drawing is delineated.arrow_forwardB- Consider the following scoring function for heuristic search: score (node) W x g(node) + (1-W) x h(node) where 0≤ W≤1 Which search algorithm do you get with W set to 0? Which search algorithm do you get with W set to 1? If h(node) is an admissible heuristic, for what range of W values is the above scoring function guaranteed to produce an admissible search strategy? Explain your answer.arrow_forward8. 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:arrow_forward
- Correct answer will be upvoted else downvoted. Computer science. deck is called arranged if the front qualities are in expanding request and the back qualities are in diminishing request. That is, if ai<ai+1 and bi>bi+1 for all 1≤i<n. To flip a card I implies trading the upsides of simulated intelligence and bi. You should flip some subset of cards (perhaps, none), then, at that point, put every one of the cards in any request you like. What is the base number of cards you should flip to sort the deck? Input The main line contains a solitary integer n (1≤n≤2⋅105) — the number of cards. The following n lines depict the cards. The I-th of these lines contains two integers ai,bi (1≤ai,bi≤2n). Each integer somewhere in the range of 1 and 2n shows up precisely once. Output In case it is difficult to sort the deck, output "- 1". In any case, output the base number of flips needed to sort the deck.arrow_forwardn = 9. sign and Analysis of Algorithms (3rd ed.) [Levitin 2011-10-09].pdf ✓ 1 2 3 zoom O 4 O 5. How would you modify the dynamic programming algorithm for the coin- collecting problem if some cells on the board are inaccessible for the robot? Apply your algorithm to the board below, where the inaccessible cells are shown by X's. How many optimal paths are there for this board? 1 3 4 5 6 8.1 Three Basic Examples 2 X O 5 XXX 2 O Xo X O Search Fri May 12 291 6. Rod-cutting problem Design a dynamic programming algorithm for the fol- lowing problem. Find the maximum total sale price that can be obtained by cutting a rod of n units long into integer-length pieces if the sale price of a piece i units long is p; for i = 1, 2, ..., n. What are the time and space efficiencies of your algorithm? 7. Shortest-path counting A chess rook can move horizontally or vertically to any square in the same row or in the same column of a chessboard. Find the number of shortest paths by which a rook can move…arrow_forwardP(M|D)P(D) given P(D|M) = solve the following p(M) а. Draw the probability tree for the situation. b. Draw the reverse tree for the situation.arrow_forward
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