Hi, everyone. This is my first post to the list. Beginning chess programmers have something called "perft" at their disposal, which is just a count node of a search tree of fixed depth, with no prunning whatsoever and no extensions. It's easy to detect errors in your move generation or do/undo functions by comparing these results with the results of other programs.
The average length of a simulation could play a similar role in MC-based go programming. We would have to agree on a simple setting that people could try to reproduce. For example: 1 - Completely random moves. 2 - Multi-stone suicides allowed 3 - Don't play in things that look like eyes (all four neighbors are the same color or outside, and the enemy has occupied at most one of the four corners if in the middle of the board or no corners at all if on the border). 4 - The game is played until neither player has a valid move. If people typically disallow multi-stone suicides (although this seems expensive to me), change rule 2 to its opposite. We could also change 4 to stop when any one player doesn't have a valid move. Any set of rules which is specific enough to allow reproducibility is good enough, and maybe we can agree on one in this thread. Álvaro. On 3/19/07, Eduardo Sabbatella <[EMAIL PROTECTED]> wrote:
My thoughts about average moves is directly related to the move selection algoritm you use. Using totally random move generator, I'm sure everybody should get the same average of moves. But using diferent heuristics in order to get not 'so' random moves (i.e. ataries getting double possibility, patterns, etc).. Average moves should be different using different approachs, what do you think? My 2 cents, Eduardo
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