a) What is the Dynamic Programming recurrence formula for the 0/1 knapsack? Show the subproblem overlapping of the following 0/1 knapsack problem? Max Weight of Bag = 7 kg Item Weight Benefit 1 3 12 2 4 15 3 3 20 4 6 25
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Q: Consider the 0-1 knapsack problem with the Capacity C = 8 and 5 items as shown in the table. Find…
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A: Knapsack problem is a name to a family of combinatorial optimization problems.
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Q: 1. Consider the knapsack problem with the capacity C= 8 and 5 items with weights 3, 6, 2, 5, 3. a)…
A: The answer given as below:
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- 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? You need to provide 1) a modified recurrence relation, 2) a pseudo code description of the algorithm, and 3) a table that stores solutions to the subproblems.Problem 4: Let S = {s1, s2, . . . , sn} and T = {t1, t2, . . . , tm}, n ≤ m, be two sets of integers. (i) Describe a deterministic algorithm that checks whether S is a subset of T. What is the running time of your algorithm? (ii) Devise an algorithm that uses a hash table of length n to test whether S is a subset of T. What is the expected running time of your algorithm?Using the code in the picture (Phyton 3): Find the Recurrence relation for foo(a, b) when b > 0 (Follow the format) T(n) = ___ T ( ___ / ___ ) + O ( ___ ) What is the worst-case time complexity of foo(a, b)? What is the worst-case auxiliary space complexity of foo(a,b)?
- Write a recurrence that would be used in dynamic programming for thefollowing problem: Given a rod of length n and an array A of prices thatcontain all prices of all the pieces smaller than n. Determine the maximumvalue obtained by cutting up the rod and selling the pieces. Note that youcould sell the rod at its original length without cutting it.Given the following code snippet, find the following:1) Recurrence relation of func (x,y) when x>0 and length of y is n. Express in the form below:T(x,n) = T(?) + O(?)For 2-3, consider worst-case scenario and initial value of y as [1]2) Time complexity of func (x,y)3) Space Complexity and Auxiliary Space Complexity of func (x,y)Implement the algorithm for an optimal parenthesization of a matrix chain product as dis-cussed in the class.Use the following recursive function as part of your program to print the outcome, assumethe matrixes are namedA1, A2, ..., An.PRINT-OPTIMAL-PARENS(s, i, j){if (i=j) thenprint “A”i else{print “(”PRINT-OPTIMAL-PARENS(s,i,s[i, j])PRINT-OPTIMAL-PARENS(s, s[i, j] + 1, j)print “)”} }a- Test your algorithm for the following cases:1. Find and print an optimal parenthesization of a matrix-chain product whose sequenceof dimensions is<5,10,3, X,12,5,50, Y,6>.2. Find and print an optimal parenthesization of a matrix-chain product whose sequenceof dimensions is<5,10,50,6, X,15,40,18, Y,30,15, Z,3,12,5>. 3. Find and print an optimal parenthesization of a matrix-chain product whose sequenceof dimensions is<50,6, X,15,40,18, Y,5,10,3,12,5, Z,40,10,30,5>. X=10 Y=20 Z=30
- ) Show that ∀xP(x) ∧ ∃xQ(x) is logically equivalent to ∀x∃y(P(x) ∧ P(y)) The quantifiers have the same non empty domain. I know that to prove a proposition is logically equivalent to another one, I have to show that ∀xP(x) ∧ ∃xQ(x) ↔ ∀x∃y(P(x) ∧ P(y)) Which means I have to prove that (∀xP(x) ∧ ∃xQ(x)) → ∀x∃y(P(x) ∧ P(y)) ∧ ∀x∃y(P(x) ∧ P(y)) → (∀xP(x) ∧ ∃xQ(x)) I don't know the answer, so I saw the textbook answer. It says (1) Suppose that ∀xP(x) ∧ ∃xQ(x) is true. Then P(x) is true for all x and there is an element y for which Q(y) is true. I get this part. Because P(x) ∧ Q(x) is true for all x and there is a y for which Q(y) is true, ∀x∃y(P(x) ∧ P(y)) is true. Emm... I think ∀x∃y(P(x) ∧ P(y)) is true because ∀x only affects P(x) and ∃y only affects P(y) since their alphabets are different. So, it has the exact same meaning as ∀xP(x) ∧ ∃yQ(y). And since the domains are the same, ∀xP(x) ∧ ∃yQ(y) is actually equal to ∀xP(x) ∧ ∃xQ(x). But the textbook states that "P(x) ∧ Q(x) is…r problem that lends itself to a dynamic programming solution is finding the longest common substring in two strings. For example, in the words“raven” and “havoc”, the longest common substring is “av”.Let’s look first at the brute force solution to this problem. Given two strings,A and B, we can find the longest common substring by starting at the firstcharacter of A and comparing each character to the characters in B. When anonmatch is found, move to the next character of A and start over with thefirst character of B, and so on.There is a better solution using a dynamic programming algorithm. Thealgorithm uses a two-dimensional array to store the results of comparisons ofthe characters in the same position in the two strings. Initially, each elementof the array is set to 0. Each time a match is found in the same position of thetwo arrays, the element at the corresponding row and column of the array isincremented by 1, otherwise the element is set to 0.To reproduce the longest common…Given the following code snippet, find the following:1) Recurrence relation of func (x,y) when x>0 and length of y is n.T(x,n) = T(_) + O(_) (Just fill in the blanks)For 2-3, consider worst-case scenario and initial value of y as [1]2) Time complexity of func (x,y)3) Auxiliary Space Complexity of func (x,y)
- Correct answer will be upvoted else downvoted. Computer science. way from block u to obstruct v is a grouping u=x0→x1→x2→⋯→xk=v, where there is a street from block xi−1 to hinder xi for each 1≤i≤k. The length of a way is the amount of lengths over all streets in the way. Two ways x0→x1→⋯→xk and y0→y1→⋯→yl are unique, if k≠l or xi≠yi for some 0≤i≤min{k,l}. Subsequent to moving to another city, Homer just recalls the two exceptional numbers L and R yet fails to remember the numbers n and m of squares and streets, separately, and how squares are associated by streets. Be that as it may, he accepts the number of squares ought to be no bigger than 32 (in light of the fact that the city was little). As the dearest companion of Homer, if it's not too much trouble, let him know whether it is feasible to see as a (L,R)- constant city or not. Input The single line contains two integers L and R (1≤L≤R≤106). Output In case it is difficult to track down a (L,R)- consistent city…Suppose you want to solve the following equality 2a + b + 3c + 4d + 6e = 45 What is the chromosome phenotype? What is the fitness function? What is the fitness value of a, b, c, d, e = (The first five numbers of university ID)? (hint if ID= 437818854 then a=1, b=8, c=8, d=5, e=4)Answer the following: This problem exercises the basic concepts of game playing, using tic-tac-toe (noughts and crosses) as an example. We define Xn as the number of rows, columns, or diagonals with exactly n X’s and no O’s. Similarly, On is the number of rows, columns, or diagonals with just n O’s. The utility function assigns +1 to any position with X3=1 and −1 to any position with O3=1. All other terminal positions have utility 0. For nonterminal positions, we use a linear evaluation function defined as Eval(s)=3X2(s)+X1(s)−(3O2(s)+O1(s)). a. Show the whole game tree starting from an empty board down to depth 2 (i.e., one X and one O on the board), taking symmetry into account. b. Mark on your tree the evaluations of all the positions at depth 2. c .Using the minimax algorithm, mark on your tree the backed-up values for the positions at depths 1 and 0, and use those values to choose the best starting move. Provide original solutions including original diagram for part a!