### Problem-solving ideas
Dynamic Programming with Rolling Array Optimization
How to judge it is dynamic programming?
Analyze the topic and discover the no aftereffects and optimal sub-problems (optimal sub-structures)
No aftereffect: The solution of the current problem is only related to the solution of the previous problem and has nothing to do with the solution of the subsequent problem.
Optimal subproblem: The optimal solution of the current problem depends on the optimal solution of the subproblem, and there is a recursive relationship between the two.
class Solution {
public:
int uniquePathsWithObstacles(vector<vector<int>>& obstacleGrid) {
if(obstacleGrid.size() == 0 || obstacleGrid[0].size()==0) return 0;
int m = obstacleGrid.size();
int n= obstacleGrid[0].size();
vector<int> dp(n, 0);
if(obstacleGrid[0][0] == 0) dp[0] = 1;
for(int i=0;i<m;i++){
for(int j=0;j<n;j++){
if(obstacleGrid[i][j]==1){
dp[j]=0;
continue;
}
if(j>=1) dp[j] = dp[j] + dp[j-1];//cur = up + left
}
}
return dp[n-1];
}
};