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Problems harder than NP-Complete

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Re: Problems harder than NP-Complete

#101

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.

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

#102

Earlier 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.

Yes. But you don't need to keep the whole tree in memory.

Re: Problems harder than NP-Complete

#103

Earlier 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.

Ahh sorry, I see what you're saying now. Yeah I guess it's in PSPACE if the length of each game is polynomial in n, and EXPTIME if games can go on for longer.

I guess chess (without the 50-move rule), checkers, and go (with a certain ruleset) can go on for longer.

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