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🔥Min Cost Climbing Stairs: Dual Step OptimizationEasy
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EasyDynamic Programming•Acceptance: 65.8%
Min Cost Climbing Stairs: Dual Step Optimization
Targeted in FAANG & Tech OA:AmazonMicrosoft
Real-World Engineering Context
Underpins energy minimization routes in robotic leg kinematics and network hop battery consumption budgeting.
You are given an integer array `cost` where `cost[i]` is the cost of `i`th step on a staircase. Once you pay the cost, you can either climb one or two steps.
You can either start from the step with index `0`, or the step with index `1`.
Return the minimum cost to reach the top of the floor (past index `n - 1`).
Sample Test Cases
Input: [[10,15,20]]
Expected: 15
Input: [[1,100,1,1,1,100,1,1,100,1]]
Expected: 6
Input: [[0,0]]
Expected: 0
Constraints
- 2 <= cost.length <= 1000
- 0 <= cost[i] <= 999
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