Look at the following algorithm (written in pseudo-code). What is the output of this algorithm if it is implemented in Python and executed?   accumulatedValue = 1 for i in range 1 to 5:      update accumulatedValue to be accumulatedValue + 1 print accumulatedValue

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1. Design an algorithm to find the weighted sum of four test scores (https://en.wikipedia.org/wiki/Weight_function). Assume that the weights have been accurately calculated in advance such that their sum equals one.  Your algorithm must-read in the four test scores and four corresponding weights in the following order: score1 weight1 score2 weight2 score3 weight3 score4 weight4 Write your algorithm such that it can be run with any set of data values. However, you can test your algorithm on the following sample data to verify that the result is 70: 90 0.10 80 0.20 70 0.30 60 0.40   2. Write an algorithm that prompts the user for the radius, in inches, and price of a pizza, and then reads in those values.  Finally, have the algorithm compute and output the pizza’s cost per square inch.   3. Sports exercise advisor algorithm. In this algorithm you will start out with a temperature value in Celsius, so you do not need to ask the user for it. First, convert the temperature to Fahrenheit.…

t for several problems you will modify some provided Python code to implement algorithms to solve the same instance of the knapsack problem. After implementing all of the code and solving the problem, you must provide a single table of all results similar to the following: Table 1: Example of results summary (numbers are not realistic) Algorithm Iterations Items Selected Weight Objective Local Search (Best Improvement) 3102 49 97 117 Local Search with Random Restarts (k = 100) Local Search with Random walk (p = 0.25) 9510 121 21 147 2102 87 32 184 etc. Knapsack Problem Definition Given n different items, where each item i has an assigned value (v.) and weight (w), select a combination of the items to maximize the total value without exceeding the weight limitations, W, of the knapsack. IMPORTANT!: When generating random problem instance set you must use the code provided and values: n = 150; max weight of 2500; and, use a seed value (for the random number generator) of 51132023.