Earlier quoted context omitted.
Consider a game like go, where board size is n. This means the game tree's branching factor is O(n). Let's say the game tree's depth is O(n) too. Then what is the size of the tree?
Under these conditions if you are doing a DFS over positions then you need to store O(n^2) positions in memory, considering that a position takes O(n) memory, you are using O(n^3) memory in total.
Problems harder than NP-Complete
101–103 of 103 posts
Re: Problems harder than NP-Complete
#102Earlier quoted context omitted.
Under these conditions if you are doing a DFS over positions then you need to store O(n^2) positions in memory, considering that a position takes O(n) memory, you are using O(n^3) memory in total.
If a tree's branching factor (i.e. the number of possible actions per turn) is N, and the depth of the tree (i.e. the length of the game) is N, the size of the tree is N^N, not N^2.
Re: Problems harder than NP-Complete
#103Earlier quoted context omitted.
If a tree's branching factor (i.e. the number of possible actions per turn) is N, and the depth of the tree (i.e. the length of the game) is N, the size of the tree is N^N, not N^2.
Yes. But you don't need to keep the whole tree in memory.
I guess chess (without the 50-move rule), checkers, and go (with a certain ruleset) can go on for longer.