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Subject: Performance of MTD(f) versus eval granularity?

Author: Werner Mühlpfordt

Date: 09:47:43 11/01/01

Hi all,

I've got a question on how the performance of the MTD(f)
search algorithm will depend on the eval function's granularity.

At first glance, it seems that with increasing number of
decimals delivered by the evaluator, the search time will go
up because the binary search will need more cycles to reach
convergence. On the other hand, a search of a given depth
reaches only a limited amount of positions with an eval near
the best one. Thus, any more accuracy would be for free when
the "tick" size is below the difference to the position that
is closest to the best one, wouldn't it?
And if the number of decimals chosen is sound, then the difference
between this "next-to-best" position to the real best one would
really matter, and the time would be well spent.

Does this allow to conclude that the factors of choice for eval granularity
are no way different for MTD(f) than for other algorithms?

Thanks in advance;

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