Consider the following problem statement:
Given an initial number, you and your friend take turns to subtract a perfect square from it. The first one to get to zero wins. For example:
Initial State: 37
Player1 subtracts 16. State: 21
Player2 subtracts 8. State: 13
Player1 subtracts 4. State: 9
Player2 subtracts 9. State: 0
Player2 wins!
Write a program that given an initial state, returns an optimal move, i.e. one that is guaranteed to lead to winning the game. If no possible move can lead you to a winning state, return -1.
This problem can be solved in pseudo-polynomial time using dynamic programming. The idea is just filling an array of length n (where n is the initial state) bottom up with the optimal moves, or -1 if no move leads to winning. This would take O(n * sqrt(n)) since for every number we need to consider subtracting each possible perfect square smaller than it (there are ~sqrt(n) of them). However, this is a pseudo-polynomial runtime complexity since the runtime actually scales exponentially with relation to the size of the input in binary (# of bits used to represent number).
Can anyone think of a polynomial algorithm for solving this problem? If not, could it be NP-Complete? Why?
