Allow us to characterize the terrorizing worth of a succession as the amount of the number of slopes and the number of valleys in the arrangement. You can change precisely one integer in the succession to any number that you need, or let the grouping stay unaltered. What is the base terrorizing esteem that you can accomplish

Allow us to characterize the terrorizing worth of a succession as the amount of the number of slopes and the number of valleys in the arrangement. You can change precisely one integer in the succession to any number that you need, or let the grouping stay unaltered. What is the base terrorizing esteem that you can accomplish

Operations Research : Applications and Algorithms

4th Edition

ISBN:9780534380588

Author:Wayne L. Winston

Publisher:Wayne L. Winston

Chapter13: Decision Making Under Uncertainty

Section13.4: Decision Trees

Problem 9P

See similar textbooks

Similar questions

In this question, you are asked to trace the Naïve Bayes algorithm for classification on some toy sentences, and then to consider some variants. The following five sentences are the training data: (the number in parentheses indicates the category that each sentence belongs to) The dog barked. (1)The mouse ran up the clock. (2)The dog ran away. (1)The collie dog barked. (1)A mouse ate the cheese. (2) The following three sentences are the test data: t1 = A dog barked loudly.t2 = The dachshund ran up the hill.t3 = The rodent nibbled the cheese. To which category does the algorithm assign each of the test sentences? Use Laplace smoothing (Add 1 smoothing). Please show your calculations and upload your solution copy .
Simulated annealing is an extension of hill climbing, which uses randomness to avoid getting stuck in local maxima and plateaux. a) As defined in your textbook, simulated annealing returns the current state when the end of the annealing schedule is reached and if the annealing schedule is slow enough. Given that we know the value (measure of goodness) of each state we visit, is there anything smarter we could do? (b) Simulated annealing requires a very small amount of memory, just enough to store two states: the current state and the proposed next state. Suppose we had enough memory to hold two million states. Propose a modification to simulated annealing that makes productive use of the additional memory. In particular, suggest something that will likely perform better than just running simulated annealing a million times consecutively with random restarts. [Note: There are multiple correct answers here.] (c) Gradient ascent search is prone to local optima just like hill climbing.…
Implement an algorithmic solution, indicating which states are valid and which are not, and model the space of the following problem: An interest group from a small town decided to sue a company for commercial abuse. For this, the people have organized themselves and decided to send 3 representatives, who will have to travel in a Van to the city where the lawsuit will be filed. The company to be sued, upon learning of these actions, has decided to send 3 lawyers to persuade the representatives, who will also travel in the same Van for that purpose. The community must file the class action suit under these conditions: - The three applicants must reach the destination city; - Only two people can travel per trip in the Van (small town - city, city - small town); - There can never be more lawyers than plaintiffs in any one place (either in the small town or city) because the lawyers can persuade the plaintiffs and as a consequence, the lawsuit would not be made; - The Van cannot be…
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!
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 solution!
Correct answer will be upvoted else downvoted. Computer science. Presently Nezzar has a beatmap of n particular focuses A1,A2,… ,An. Nezzar might want to reorder these n focuses so the subsequent beatmap is great. Officially, you are needed to find a change p1,p2,… ,pn of integers from 1 to n, to such an extent that beatmap Ap1,Ap2,… ,Apn is great. In case it is unthinkable, you ought to decide it. Input The primary line contains a solitary integer n (3≤n≤5000). Then, at that point, n lines follow, I-th of them contains two integers xi, yi (−109≤xi,yi≤109) — directions of point Ai. It is ensured that all focuses are unmistakable. Output In case there is no arrangement, print −1. In any case, print n integers, addressing a legitimate change p. In case there are numerous potential replies, you can print any.
Correct answer will be upvoted else Multiple Downvoted. Computer science. You are given an integer n (n>1). Your assignment is to find a succession of integers a1,a2,… ,ak with the end goal that: every simulated intelligence is completely more prominent than 1; a1⋅a2⋅… ⋅ak=n (I. e. the result of this grouping is n); ai+1 is separable by simulated intelligence for every I from 1 to k−1; k is the most extreme conceivable (I. e. the length of this grouping is the greatest conceivable). In case there are a few such groupings, any of them is adequate. It tends to be demonstrated that somewhere around one substantial grouping consistently exists for any integer n>1. You need to answer t autonomous experiments. Input The primary line of the input contains one integer t (1≤t≤5000) — the number of experiments. Then, at that point, t experiments follow. The main line of the experiment contains one integer n (2≤n≤1010). It is ensured that the amount of n…
Draw the TST that results when the keys "now is the time for all good people to come to the aid of" are inserted in that order into an initially empty TST
Simulated annealing is an extension of hill climbing, which uses randomness to avoid getting stuck in local maxima and plateaux. a) For what types of problems will hill climbing work better than simulated annealing? In other words, when is the random part of simulated annealing not necessary? b) For what types of problems will randomly guessing the state work just as well as simulated annealing? In other words, when is the hill-climbing part of simulated annealing not necessary? c) Reasoning from your answers to parts (a) and (b) above, for what types of problems is simulated annealing a useful technique? In other terms, what assumptions about the shape of the value function are implicit in the design of simulated annealing? d) As defined in your textbook, simulated annealing returns the current state when the end of the annealing schedule is reached and if the annealing schedule is slow enough. Given that we know the value (measure of goodness) of each state we visit,…
In the context of evolutionary computing the goal function is known as the fitnessfunction and the problem is to maximize it. The typical formulation has to be changedin a simple way.min f (x) = − max[− f (x)] (4.9)Another requirement is that the goal function is positive.Phenotype evolution treats x as a phenotype and the goal function as the fitnessfunction. The typical framework for the method is as follows:
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."
6) (a) Useatruthtabletoshowthat∼(p→q)≡p∧∼q (b) Use the equivalence from part (a) to quickly figure out, without using a truth table, that p → q ≡ ∼ (p ∧ ∼ q) (c) Why does the equivalence from part (b) provide us with further evidence that we made the right choices in the last two lines of the truth table for conditional statements? (At least, it does for me!)