One aspect of a simulated annealing cooling schedule is the temperature. i. Explain the effect of having the starting temperature too high or too low. ii. Describe how you can decide on a suitable starting temperature. iii. Discuss how you can decide on a final temperature.
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- The size of a colony of blue bacteria growing in a petri dish is modeled by the equation where t is time in days. The size of a colony of green bacteria is modeled by the equation where t is again time in days. Both colony sizes are measured in square centimeters. Part A: Graph the growth of both colonies on the same plot over the course of 6 days in one hour increments. One way to get one hour increments is to use a step size of 1/24. Another way is to use linspace and specify that it should create 6days x 24hours evenly spaced values. In either case, make sure you start at 0 days, not 1 day. Make the color of the curve match the color of the bacteria it represents. Give your graph a title and axis labels. Part B: How large is the green bacteria colony when the blue colony reaches its maximum size. You must answer this question using Matlab calculations, not manually entering the answer. To check your work, the blue colony’s maximum size is 270.56 and when it reaches that…4. Consider a random walk on the infinite line. At each step, the position of the particle is one of the integer points. At the next step, it moves to one of the two neighboring points equiprobably. Show that the expected distance of the particle from the origin after n steps is O(n/2).You are explaining the problem of searching for a move in chess to your friend. Your friend notices that the algorithm needs to find the maximum of some function (i.e., the move that is best for you) and suggests that one should simply differentiate the function, set the result to zero, and solve. Explain why this will not work.
- a) Explain on Simulated Annealing algorithm behaves at very high temperatures, and how it behaves at very low temperatures. (b) Imagine the implementation of Simulated Annealing algorithm in real life. Let's say, you have a caretaker at your home. Your home has a garden and it has a fountain with a network of pipes that contains 150 faucets. You informed your caretaker that you are going for short holiday to Langkawi for 3 days and when you return you would like the fountain to spray as high as possible. Your caretaker knows that it is impossible to check all faucets within 3 days to obtain an optimal setting. You can use Simulated Annealing algorithm to maximize the height of the fountain, also can assume whether a faucet can be ON or OFF and measuring the water height. Adding to that, you can make any other assumptions required for this scenario, explain clearly using Simulated Annealing algorithm.Casinos have devised different automated mechanical methods for shuffling the cards.One such method divides the deck into to seven piles by placing each card randomlyeither on the top or at the bottom of one pile (i.e. each card has 14 possible placesto choose from). After that, the piles are put together to form the shuffled deck.Is this a good method? Can a gambler utilize this information to his advantage?Correct answer will be upvoted else Multiple Downvoted. Don't submit random answer. Computer science. You have n particular focuses (x1,y1),… ,(xn,yn) on the plane and a non-negative integer boundary k. Each point is a tiny steel ball and k is the draw in force of a ball when it's charged. The draw in power is something very similar for all balls. In one activity, you can choose a ball I to charge it. When charged, all balls with Manhattan distance all things considered k from ball I move to the situation of ball I. Many balls may have a similar facilitate after an activity. All the more officially, for all balls j with the end goal that |xi−xj|+|yi−yj|≤k, we dole out xj:=xi and yj:=yi. An illustration of an activity. Subsequent to charging the ball in the middle, two different balls move to its position. On the right side, the red dab in the middle is the normal situation of those balls. Your errand is to observe the base number of activities to move all balls to a similar…
- Q1/ The ideal gas equation of state is given by: PV = nRT Where: P is the pressure (atm), V is the volume (L), T is the temperature (K), R=0.08206 (L atm)/(mol K) is the gas constant, and n is the number of moles. Real gases, especially at high pressures, deviate from this behavior. Their responses can be modeled with the van der Waals equation: P-- nRT n² a + = 0 V-nb V2 Where a and b are material constants. For CO₂ a 3.5924 L'atm/mol², and b=0.04267 L/mol. Calculate P from both equations for CO₂ gas with 40 values of V between 0.01 and 1.5 and display the results in: 1- Three-column table where the values of Vand both P are displayed in the first, second, and third columns, respectively. 2-Plot V versus both P in two different plots in the same figure with a solid line, black color, with circle marker. Add a title, labels, and the grid to the plot. Make all texts bold with font size of 13. Take T-298K and n-3 moles.Correct answer will be upvoted else Multiple Downvoted. Computer science. You should stop precisely one of these boards, at any subsequent you wish. Then, at that point, the boards adjoining it get stopped one second after the fact, the boards nearby those get stopped 2 seconds after the fact, etc. At the end of the day, in the event that you stop board x, board y (for all substantial y) would be stopped precisely |x−y| seconds after the fact. For instance, assume there are 4 boards, and the 3-rd board is stopped when the digit 9 is on it. The board 1 stops 2 seconds after the fact, so it has the digit 1; the board 2 stops 1 second after the fact, so it has the digit 0; the board 4 stops 1 second after the fact, so it has the digit 0. The subsequent 4-digit number is 1090. Note that this model isn't ideal for n=4. When all boards have been stopped, you compose the digits showed on them from left to right, to frame a n digit number (it can comprise of driving…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.…
- Computer science. Correct answer will be upvoted else downvoted. Think about a n by n chessboard. Its columns are numbered from 1 to n from the top to the base. Its sections are numbered from 1 to n from the passed on to one side. A cell on a convergence of x-th line and y-th section is indicated (x,y). The fundamental corner to corner of the chessboard is cells (x,x) for all 1≤x≤n. A stage of {1,2,3,… ,n} is composed on the fundamental slanting of the chessboard. There is actually one number composed on every one of the cells. The issue is to segment the cells under and on the principle askew (there are by and large 1+2+… +n such cells) into n associated areas fulfilling the accompanying imperatives: Each district ought to be associated. That implies that we can move from any cell of a locale to some other cell of a similar area visiting just cells of a similar district and moving from a cell to a neighboring cell. The x-th area ought to contain cell on the fundamental…业 In the 8 queens problem, you are to place 8 queens on the chessboard in such a way that no two queens attack each other. That is, there are no two queens on the same row, column, or diagonal. The picture above shows a near solution--the top left and bottom right queens attack each other. We want to solve this problem using the techniques of symbolic Al. First, we need states. What would the best choice be for states? Each queen and its position x Michigan, Illinois, Indiana, etc. How many queens we have placed so far A board with the positions of all the queens that have been placed so far 00 What would the start state be? A single queen's position Crouched, with fingers on the starting line Placing the first queen x An empty board What would the goal state be? CA board with 8 queens placed Ball in the back of the net The positions of all 8 queens A board with 8 queens placed, none attacking each otherv What would the best choice for "edges" or "moves" be? Tiktok Moving a queen from…You are a computer research scientist at Tesla, and your task is to create a computer vision application for self-driving cars to detect object and avoid collision. You know that Graham's scan is a method of computing the convex hull of a finite set of points in the plane. You decide to apply this algorithm to achieve the goal of your task. a) Suppose Graham's scan executes n points, where n >= 3. Prove that, at the end of the program, the stack S consists of, from bottom to top, exactly the vertices of convex hull in counter-clockwise order.