If two search heuristics h1(s) and h2(s) have the same average value, the heuristic h3(s) = max(h1(s), h2(s)) could give better A* efficiency than h1 or h2. Select one: True False
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If two search heuristics h1(s) and h2(s) have the same average value, the heuristic h3(s) = max(h1(s), h2(s)) could give better A* efficiency
than h1 or h2.
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- Sum of Squared Errors: Remember from your statistics courses that if two random variables X and Y are related by a relation YaX+b and you had a set of observations {(1, 1), (2, 2)..... (z.)). then for every estimated values of a and b, the Sum of Squared Errors (SSE) was defined as in the following formula. SSE(-ar-b)². 1-1 The less SSE, the better a and b are estimated. Consider the following fixed list. In this list each sub-list of length two is standing for one pair (z.). Write a function that recieves two numbers a and b and returns the associated SSE. L- [[1, 2], [1.1, 2], [2, 7.1), (2.5, 7.21, (3, 11]]This assignment uses several heuristic search techniques to find possibly optimal truth assignments for variables in the given Boolean formulas (see the bottom of the assignment). The formulas are in conjunctive normal form (ANDs of ORs). The fitness of an assignment is the number of clauses (ORs) that the assignment satisfies. If there are c clauses, then the highest fitness is bounded by c. However, if the formula is not satisfiable, then you cannot simultaneously make all c clauses true. You will use three of the following seven techniques: DPLL Resolution Genetic algorithms Local search Simulated annealing GSAT WalkSAT You must choose at least one complete algorithm to implement - DPLL or Resolution.You are given the midsem and endsem marks for the N Students in the course. A student P is said to dominate a student Q, if the midsem and endsem marks of P are both greater than the respective midsem and endsem marks of Q. Design an efficient algorithm for finding all the students that are not dominated by any other student in the class.
- Write an expression for the decomposition of selection bias in each of the following cases. Which is the "worst"? (a) (b) (c) Sx = 0 X = [0, 1], Six = [0, 0.75], Sox= [0.25, 1], f(x) = 1 X = 2¹Correct answer will be upvoted else downvoted. Computer science. You are given three positive (more prominent than nothing) integers c, d and x. You need to track down the number of sets of positive integers (a,b) with the end goal that balance c⋅lcm(a,b)−d⋅gcd(a,b)=x holds. Where lcm(a,b) is the most un-normal various of an and b and gcd(a,b) is the best normal divisor of an and b. Input The primary line contains one integer t (1≤t≤104) — the number of experiments. Each experiment comprises of one line containing three integer c, d and x (1≤c,d,x≤107). Output For each experiment, print one integer — the number of sets (a,b) to such an extent that the above uniformity holds.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…
- Remaining Time: 2 hours, 27 minutes, 02 seconds. Duestion Completion Status: Y=A'. B' + (AOB) b. Using Karnaugh map, simplify the following Boolean function F (show your grouping): [2 Marks] A B C F 1 1 1 1 1 1 1 1 1 0. 1 1 1 1 1 1 Click Save and Submit to save and submit. Click Save All Answers to save all answers. Save All A O Type here to search DLL FS F9 F10 F11 9 3 r 7 Y 8 W E R = G i JJ 立Correct answer will be upvoted else Multiple Downvoted. Don't submit random answer. Computer science. You have a knapsack with the limit of W. There are likewise n things, the I-th one has weight wi. You need to place a portion of these things into the knapsack so that their all out weight C is half of its size, however (clearly) doesn't surpass it. Officially, C ought to fulfill: ⌈W2⌉≤C≤W. Output the rundown of things you will place into the knapsack or establish that satisfying the conditions is unimaginable. In case there are a few potential arrangements of things fulfilling the conditions, you can output any. Note that you don't need to expand the amount of loads of things in the knapsack. Input Each test contains various experiments. The principal line contains the number of experiments t (1≤t≤104). Depiction of the experiments follows. The main line of each experiment contains integers n and W (1≤n≤200000, 1≤W≤1018). The second line of each experiment…Particle filters are a good way of keeping track of a set of hypotheses when performing SLAM. With regards to the FastSLAM algorithm discussed in the video, select all the true statements in the following set. Select one or more: ✔a. Each particle must keep a hypothesis of the noise in the motion model * ✓b. Each particle must keep a hypothesis of the robot's observations* ✓c. Each particle must keep a hypothesis of the position of the robot d. Particles do not keep a hypothesis of the variance in landmark positions e. Particles do not keep a hypothesis of the robot's sensor model ✔f. Each particle must keep a hypothesis of the positions of landmarks g. Particles do not keep a hypothesis of the variance in the robot's positon ✔h. Each particle must keep a hypothesis of the path followed by the robot* Your answer is incorrect. The correct answers are: Each particle must keep a hypothesis of the position of the robot, Each particle must keep a hypothesis of the positions of landmarks,…
- For (∃ x)(P(x,b)) Would an example of this being true if the domain was all the Avengers and x was green skin, then "b" being the Hulk would make this true. Am example of this being false would be: If the domain was all integers and x was positive, even integers and "b" was integers greater than zero.As an investor, I always check the stock market in order to find good companies to invest in. Recently, I found that the best companies to invest in, are the ones that have largest sum formed by a strictly increasing set of numbers (a set where the next element is always greater than the current element). But before I invest, I need to know the position of the first element of the consecutive increasing numbers. Help me so we can start investing already! Note: If it is already the last element of the row in the array, the next element is the first element of the next row, if there exists a next row. Input 1. Number of rows Description This is the number of rows of the multidimensional array. 2. Number of columns Description This is the number of columns of the multidimensional array. 3. Elements of the multidimensional array Output The first line will contain a message prompt to input the number of rows. The second line will contain a message prompt to input the…Q5/ Consider the following search space in which the goal is to find the p from S to G, next(S,A,5), next(S,B,2),next(A,G,5), next (B,D,1), next(B,C,2), next (C,G,2), next(D,G,5), where next(X,Y,Z) means that Y is a child of X and the cost of going from X to Y is Z. ho(S)=0, ho(A)=0, ho(B)=0, ho(C)=0, ho(D)=0, ho(G)=0, h₁(S)-5, h₁(A)=3, h₁(B)=4, h₁(C)=2, h₁ (D)=5, h₁(G)=0, h₂(S)-6, h₂(A)=5, h₂(B)=2, h₂(C)=5, h₂(D)=3, h₂(G)=0, - Which of the above heuristic functions ho,h1 and h2 are admissible? - Give the solution of the longest path found by the A algorithm using the admissible heuristic function. Note: showe the solution using paper please