Given an array of non-negative integers, you are initially positioned at the first index of the array.
Each element in the array represents your maximum jump length at that position.
Your goal is to reach the last index in the minimum number of jumps.
For example:
Given array A =
Given array A =
[2,3,1,1,4]
The minimum number of jumps to reach the last index is
2
. (Jump 1
step from index 0 to 1, then 3
steps to the last index.)
Note:
You can assume that you can always reach the last index.
You can assume that you can always reach the last index.
I am always confuse whether to use DP when get a question like this. I ask myself what the subproblem is and how the solution structures of subproblems overlapping each other. For this question, the definition of the subproblems is steps[i] = min{1+steps[j]}, if nums[j] can reach i, j
A neater solution I like is given in Leetcode forum:https://leetcode.com/discuss/45992/10-lines-c-16ms-python-bfs-solutions-with-explanations
The explanation given by author is in below:
This problem has a nice BFS structure. Let's illustrate it using the example
nums = [2, 3, 1, 1, 4]
in the problem statement. We are initially at position 0
. Then we can move at most nums[0]
steps from it. So, after one move, we may reach nums[1] = 3
or nums[2] = 1
. So these nodes are reachable in 1
move. From these nodes, we can further move to nums[3] = 1
and nums[4] = 4
. Now you can see that the target nums[4] = 4
is reachable in 2
moves.
Putting these into codes, we keep two pointers
start
and end
that record the current range of the starting nodes. Each time after we make a move, update start
to be end + 1
and end
to be the farthest index that can be reached in 1
move from the current [start, end]
.
To get an accepted solution, it is important to handle all the edge cases. And the following codes handle all of them in a unified way without using the unclean
if
statements :-)
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