to move the disks to the end of the row using a constrained set of actions. At each step, a disk can only be moved to an adjacent empty cell, or to an empty cell two spaces away, provided another disk is located on the intervenin
Can you help me with this code because I am struggling a little bit on how to do this, I only need help with section 2.3 but you section 2.2 to understand 2.3. I have add the questions for both sections but I only need help with section 2.3. Again I only need help with section 2.3
question for 2.3:
Recall the Linear Disk Movement section. The starting configuration of this puzzle is a row of L cells, with disks located on cells 0 through n - 1. The goal is to move the disks to the end of the row using a constrained set of actions. At each step, a disk can only be moved to an adjacent empty cell, or to an empty cell two spaces away, provided another disk is located on the intervening square.
In a variant of the problem, the disks were distinct rather than identical, and the goal state was amended to stipulate that the final order of the disks should be the reverse of their initial order.
Implement an improved version of the solve_distinct_disks(length, n) function from Homework 2 that uses an A* search rather than an uninformed breadth-first search to find an optimal solution. As before, the exact solution produced is not important so long as it is of minimal length. You should devise a heuristic which is admissible but informative enough to yield significant improvements in performance.
section 2.2 linear disk movement.
you will investigate the movement of disks on a linear grid. The starting configuration of this puzzle is a row of L cells, with disks located on cells 0 through n - 1. The goal is to move the disks to the end of the row using a constrained set of actions. At each step, a disk can only be moved to an adjacent empty cell, or to an empty cell two spaces away, provided another disk is located on the intervening cell. Given these restrictions, it can be seen that in many cases, no movements will be possible for the majority of the disks. For example, from the starting position, the only two options are to move the last disk from cell n - 1 to cell n, or to move the second to-last disk from cell n - 2 to cell n.
task:
Write a function solve_identical_disks(length, n) that returns an optimal solution to the above problem as a list of moves, where length is the number of cells in the row and n is the number of disks. Each move in the solution should be a two-element tuple of the form (from, to) indicating a disk movement from the first cell to the second. As suggested by its name, this function should treat all disks as being identical. Your solver for this problem should be implemented using a breadth-first graph search. The exact solution produced is not important, as long as it is of minimal length. Unlike in the previous two sections, no requirement is made with regards to the manner in which puzzle configurations are represented. Before you begin, think carefully about which data structures might be best suited for the problem, as this choice may affect the efficiency of your search.
>>> solve_identical_disks(4, 2)
[(0, 2), (1, 3)]
>>> solve_identical_disks(5, 2)
[(0, 2), (1, 3), (2, 4)]
>>> solve_identical_disks(4, 3)
[(1, 3), (0, 1)]
>>> solve_identical_disks(5, 3)
[(1, 3), (0, 1), (2, 4), (1, 2)].
Write a function solve_distinct_disks(length, n) that returns an optimal solution to the same problem with a small modification: in addition to moving the disks to the end of the row, their final order must be the reverse of their initial order. More concretely, if we abbreviate length as L, then a desired solution moves the first disk from cell 0 to cell L - 1, the second disk from cell 1 to cell L - 2, . . . , and the last disk from cell n - 1 to cell L - n. Your solver for this problem should again be implemented using a breadth-first graph search. As before, the exact solution produced is not important, as long as it is of minimal length.
>>> solve_distinct_disks(4, 2)
[(0, 2), (2, 3), (1, 2)]
>>> solve_distinct_disks(5, 2)
[(0, 2), (1, 3), (2, 4)]
>>> solve_distinct_disks(4, 3)
[(1, 3), (0, 1), (2, 0), (3, 2), (1, 3), (0, 1)]
>>> solve_distinct_disks(5, 3)
[(1, 3), (2, 1), (0, 2), (2, 4), (1, 2)]
here is part 2 of my work for linear disk movement:
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