Q-1. Consider the Map Coloring Problem described below: Map Coloring Problem The following map is to be colored using 3 colors, i.e., red, green and blue (denoted by numbers 1,2,3). The constraint is that neighboring regions cannot have the same color. D E G B A Problem Formulation The problem can be formulated as follows: Initial state: A list of 7 random numbers in the range 1-3, e.g., (2,1,1,3,1,2,3) Operators: 1. Change the value of one of the numbers in the list. Goal state: A list of 7 numbers in the range 1-3 that satisfy all constraints Objective Function The problem has 9 constraints as defined below: A #B B #C C# D C# F C# G D# E D# F E #F F# G Objective function is defined as: f(n) = Number of constraints satisfied Write a Python program that to implement steepest-ascent hill climbing algorithm to solve the above problem. с

Q-1. Consider the Map Coloring Problem described below: Map Coloring Problem The following map is to be colored using 3 colors, i.e., red, green and blue (denoted by numbers 1,2,3). The constraint is that neighboring regions cannot have the same color. D E G B A Problem Formulation The problem can be formulated as follows: Initial state: A list of 7 random numbers in the range 1-3, e.g., (2,1,1,3,1,2,3) Operators: 1. Change the value of one of the numbers in the list. Goal state: A list of 7 numbers in the range 1-3 that satisfy all constraints Objective Function The problem has 9 constraints as defined below: A #B B #C C# D C# F C# G D# E D# F E #F F# G Objective function is defined as: f(n) = Number of constraints satisfied Write a Python program that to implement steepest-ascent hill climbing algorithm to solve the above problem. с

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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Using C++, code the following problem: In this problem, we are given a knapsack of fixed capacity C. We are also given a list of N objects, each having a weight W(I) and profit P(I). We can put any subset of the objects into the knapsack, as long as the total weight of our selection does not exceed C. The goal is to maximize the total profit, which is the sum of the profits of each object we put into the knapsack. Example: Input: C = 3 W: 1 2 3 P: 100 5 50 Selected Items: 1 2 Explanation: Possible selections that can be put in the knapsack are: 1 with profit 100 2 with profit 5 3 with profit 50 1 and 2 with profit 105 Note that in this problem, there is no need that the some of weights be exactly C. Hence, in this example, 1 is a valid solution but since the profit is lower than the maximum, is not the final answer. Input Format First line is C. Second line is the number of objects, N. The next N lines, each line contains two numbers: the first number is the weight of an…
Single Point based Search: Fair share problem: Given a set of N positive integers S={x1, x2, x3,…, xk,… xN}, decide whether S can be partitioned into two sets S0 and S1 such that the sum of numbers in S0 equals to the sum of numbers in S1. This problem can be formulated as a minimisation problem using the objective function which takes the absolute value of the difference between the sum of elements in S0 and the sum of elements in S1. Assuming that such a partition is possible, then the minimum for a given problem instance would have an objective value of 0. A candidate solution can be represented using a binary array r=[b1, b2, b3,…, bk,… bN], where bk is a binary variable indicating which set the k-th number in S is partitioned into, that is, if bk =0, then the k-th number is partitioned in to S0, otherwise (which means bk =1) the k-th number is partitioned in to S1. For example, given the set with five integers S={4, 1, 2, 2, 1}, the solution [0,1,0,1,1] indicates that S is…
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?
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
Suppose that a manufacturing company builds n different types of robots, sayrobots 1, 2, . . . , n. These robots are made from a common set of m types of materials, saymaterials 1, 2, . . . , m. The company has only a limited supply of materials for each year,the amount of materials 1, 2, . . . , m are limited by the numbers b1, b2, . . . , bm, respectively.Building robot i requires an aij amount from material j. For example, building robot 1requires a11 from material 1, a12 from material 2, etc. Suppose the profit made by sellingrobot i is pi. Write an integer linear program for maximizing the annual profit for thecompany
This problem exercises the basic concepts of game playing, using tic-tac-toe (noughtsand 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))."Mark on your tree the evaluations of all the positions at depth 2."
Artificial Intelligence - Adversarial Search 1. Consider the following three variants of minimax search: the simple version, alpha-beta search, anddepth-limited search, and consider the games of tic-tac-toe and chess. For the chess game, supposethat the Threefold Repetition Rule and the Fifty-Move Rule, and the similar rules if any, are notconsidered, i.e., the game will not terminate if the same position occurs multiple times. For eachcombination of minimax variant and game, answer the following question: can that minimax variantpossibly never terminate, in computing the best next move? Justify your answer.
Consider GCET’s central library where the librarian Mario is required to sort thebooks before closing each day. The library has long shelves, and the books arenumbered through 1 to N, the librarian wishes to arrange the books so that they appearin the sequence 1,2, …, N.He intends to do this by a sequence of moves. In each move Mario can pick up anybook and insert it at a different place. Let he has 5 books and they are initially arrangedin the order: 1 4 5 3 2Mario will rearrange this in ascending order by first moving book 2 to the beginningof the shelf to get : 1 2 4 5 3Then moving book 3 to position 3, he gets 1 2 3 4 5You are required to write a program for Mario that determines the minimum numberof moves that are necessary to sort the bookshelf. C programming, please solve with full answer and solve with Flowchart and Discription
Consider GCET’s central library where the librarian Mario is required to sort thebooks before closing each day. The library has long shelves, and the books arenumbered through 1 to N, the librarian wishes to arrange the books so that they appearin the sequence 1,2, …, N.He intends to do this by a sequence of moves. In each move Mario can pick up anybook and insert it at a different place. Let he has 5 books and they are initially arrangedin the order: 1 4 5 3 2Mario will rearrange this in ascending order by first moving book 2 to the beginningof the shelf to get : 1 2 4 5 3Then moving book 3 to position 3, he gets 1 2 3 4 5You are required to write a program for Mario that determines the minimum numberof moves that are necessary to sort the bookshelf. please solve with Flowchart and description
Suppose a candidate solution p, where p is a phenotype consisting of 4 vertices. Suppose that minimum fitness occurs when no pair of vertices in p are connected, and maximum fitness occurs when all pairs of vertices in p are connected. Write a pseudocode on how to calculate the fitness F of p.
Suppose you have been given a map of 6 cities connected with each other via different paths. Your job is to visit every city just once covering the minimum distance possible. Solve this problem using Genetic Algorithm. You can start at any point and end at any point. Just make sure that all the cities have been covered. 1. Encode the problem and create an initial population of 3 different chromosomes 2. Choose any one parent from your above solution and identify the following:i. Gene ii. Chromosome 3. Think of an appropriate fitness function to this problem and give proper justification. 4. Use the fitness function to calculate the fitness level of all the chromosomes in your population. Select the fittest 2 chromosomes based on the fitness function. 5. Perform crossover that you have been taught in the class on the selected parents. Now based on the offspring, for this problem do you think that is the best way to perform crossover? If not, explain why. 6. Perform mutation that you…
Observe the following two Sequential Search and Binary Search algorithms in the image. Perform a comparative analysis of the Sequential Search and Binary Search algorithms in terms of the number of basic operations executed by the two algorithms. A. Calculate and analyze the time complexity T(n) and the efficiency class of the two search algorithms in the worst case. B. Write an example case by writing down the elements for different data sizes, for example n=4, 8, ... Please specify the elements of table A and the data you are looking for, x. Write an illustration of the comparison process for every n to confirm the complexity of the algorithm in point a). C. Describe your opinion regarding the comparative analysis of the efficiency of the two algorithms! Please solve subparts A,B,C in 60 minutes ASAP can u get thank u