f(n) = g(n) + h(n). Discuss which thing should be optimal, underestimated, overestimated, admissible or non-admissible. What will happen if you make it monotonic? Give the example case to preserve its admissibility?
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Q 2: f(n) = g(n) + h(n). Discuss which thing should be optimal, underestimated, overestimated, admissible or non-admissible. What will happen if you make it monotonic? Give the example case to preserve its admissibility?
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- In an optimal A* search, a- describe the problem of a heuristic function that overestimates the cost. How does it effect the solution? Give an example. b-is a heuristic method that underestimates the cost admissible? How does it effect the solution? Give an exampleQUESTION 9 What is one advantage of AABB over Bounding Spheres? Computing the optimal AABB for a set of points is easy to program and can be run in linear time. Computing the optimal bounding sphere is a much more difficult problem. The volume of AABB can be an integer, while the volume of a Bounding Sphere is always irrational. An AABB can surround a Bounding Sphere, while a Bounding Sphere cannot surround an AABB. To draw a Bounding Ball you need calculus knowledge.The monotone restriction (MR) on the heuristic function is defined as h (nj ) 2 h (ni ) - c (ni , nj ). Please prove the following: 1. If h(n)Isn't the actual optimal S->B->G. If yes, then how are the assumed heuristics valid?This question is about the problem “Making Change". In the Republik Question 3 Unsaved k, the only denominations available are 1, 4, 7 and 12 cents. Does Mak- ingChange produce an optimal solution for all possible inputs? No. For instance it does not return an optimal solution when the input is 26. No. For instance it does not return an optimal solution when the input is 24. No. For instance it does not return an optimal solution when the input is 20. No. For instance it does not return an optimal solution when the input is 23. Yes No. For instance it does not return an optimal solution when the input is 25.8. A school is creating class schedules for its students. The students submit their requested courses and then a program will be designed to find the optimal schedule for all students. The school has determined that finding the absolute best schedule cannot be solved in a reasonablo time. Instead they have decided to use a simpler algorithm that produces a good but non-optimal schedule in a more reasonable amount of time. Which principle does this decision best demonstrate? O A Unreasonable algorithms may sometimes also be undecidable O B. Heuristics can be used to solve some problems for which no reasonable algorithm exsts O C. efficiency Two algorithms that solve the same problem must also have the same O B. Approximate solutions are often identical to optimal solutionsConsider navigating the maze shown below (same maze used in the homework). (N M 4 2 K 2 2 2 E B G 2 2 F H 2 The maze is represented as a graph with edge costs as shown on the edges. The edge cost is 1 for all edges where the cost is not shown. Let B be the initial state and G is the goal state. The heuristic cost of every node to reach G is : h(n) Th A 5.1 B 4.1 C 3.9 D 14 E 2.2 IF 3.8 G 0 IH 3.7 IJ 7 IK 16 L 14 IM 0.5 IN 1.5 IP 1.8 S 4.5 Show the steps of an A* search starting from B to goal G: . Show the frontier and explored set in every iteration (i.e., complete the above table) List the vertices in the order they are expanded.Finish the computation of the following main table of constructing an optimal BST and write down the process in detail. Thank youCalculate the optimal value of the decision parameter p in the Bresenham's circle drawing algorithm. The stepwise procedure for implementing Bresenham's algorithm for circle drawing is delineated.8. A school is creating class schedules for its students. The students submit their requested courses and then a program will be designed to find the optimal schedule for all students. The school has determined that finding the absolute best schedule cannot be solved in a reasonable time. Instead they have decided to use a simpler algorithm that produces a good but non-optimal schedule in a more reasonable amount of time. Which principle does this decision best demonstrate? A. Unreasonable algorithms may sometimes also be undecidable B. Heuristics can be used to solve some problems for which no reasonable algorithm exists C. Two algorithms that solve the same problem must also have the same efficiency D. Approximate solutions are often identical to optimal solutions 0000Practice Test Questions: Prove each of the following statements, or give a counterexample: Best-first search is optimal in the case where we have a perfect heuristic (i.e., h(n) = h∗(n), the true cost to the closest goal state). Suppose there is a unique optimal solution. Then, A* search with a perfect heuristic will never expand nodes that are not in the path of the optimal solution. A* search with a heuristic which is admissible but not consistent is complete.Use the bottom-up dynamic programming to determine an optimal set of coins. The greedy algorithm approach for this has an issue such as if we have the set of coins {1, 5, 6, 9} and we wanted to get the value 11. The greedy algorithm would give us {9,1,1} however the most optimal solution would be {5, 6} Write a bottom up approach that would show the set of coins {5,6} when we give the set of coins {1, 5, 6, 9} and a value of 11. P.S.: - I do not need the minimum number of coins, but want the set of coins to be shown. C++ or Python code is appreciatedSEE MORE QUESTIONS