alignments of two
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- Let M be the PDA defined by Q = {q, qo, 91, 92}, E= {a,b}, T = {a}, F := {q , q1}. 8(10, a , Zo) = {(q, Zo)} d(q, a, Zo) = {(q , aZo)} б(а, а, а) %3 {(q, аа)} 8(q, b , a) = {(q1,e)} d(q1, b, a) = {(q1,e)} 8(q1, b, Zo) = {(q2, e)} b) Trace all computations of the strings aab, abb, aba in M. c) Show that aaabb, aaab E L(M ).Consider the two versions of Quicksort that are based on the following: (i) Median selection algorithm using the linear-time select method; (ii) The randomized pivot selection algorithm Which of the two algorithms has a faster worst-case asymptotic behavior? Which of the two algorithms has a faster average-case performance? Provide empirical evidence of your answer by writing the corresponding programs for each and conducting experimental evaluation. Your experimental results should provide evidence of your answer. For this you need to run an adequate number of experiments on a variety of array/list sizes (use large randomly generated lists of integers).Problem 8: Optimal Binary Search Tree Find the optimal binary search tree (BST) for the following keys and frequencies: Key: 1 2 3 4 5 6 7 Frequencies: 3 5 9 2 11 13 16
- I need to construct a optimal binary search tree (OBST). I am using Python to create this code. I already started creating the binary search tree. I need help trying to implement the optimal binary search tree. I did the class and then I did the insertion next to add the nodes. There needs to be at least 20 nodes. After that, I'm stuck. Not sure what code is needed to add for optimal cost. Criteria from my assignment: Contains at minimum 20 nodes. All paths must have a cost between 1-15. You must use each cost at least once with the remaining costs of your choice in the same range. All nodes must be able to communicate with all other nodes (does not have to be a direct path) Each node can only connect to, at maximum, 5 other nodes. The cost of an extra hop is 1 1/2 times the cost of the second path and 2 times the cost of a third path. Any path greater than 3 is at the same cost as the third. This is what is required for us in the assignment. My Code in Python: class BST:def…8. A school is creating class schedules for its students. The students submit their requested courses and then a program will be designed to find the optimal schedule for all students. The school has determined that finding the absolute best schedule cannot be solved in a reasonablo time. Instead they have decided to use a simpler algorithm that produces a good but non-optimal schedule in a more reasonable amount of time. Which principle does this decision best demonstrate? O A Unreasonable algorithms may sometimes also be undecidable O B. Heuristics can be used to solve some problems for which no reasonable algorithm exsts O C. efficiency Two algorithms that solve the same problem must also have the same O B. Approximate solutions are often identical to optimal solutionsThis characteristic is met by a problem if it is feasible to develop an optimum solution for it by first creating optimal solutions for its subproblems. a) Subproblems that overlap; b) substructure that's optimum; c) memorization; d) greedy
- 5.1. Trace the operation of Greedy Best-First Search, applied to the problem of getting to the goal state G from state S given below, for the following heuristic function: h,(N) = sum of the (Manhattan) distances of every tile to its goal position 341 25 876 State S 432 16 578 State GThis characteristic is met by a problem if it is feasible to develop an optimum solution for it by first creating optimal solutions for its subproblems. a) Subproblems that overlap; b) substructure that's optimum; c) memorization; d) greedyQuestion 1: Which of the following standard algorithms is not Dynamic Programming based. 01 02 03 04 1. Bellman-Ford Algorithm for single source shortest path 2. Floyd Warshall Algorithm for all pairs shortest paths 3. 0-1 Knapsack problem 4. Prim's Minimum Spanning Tree
