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; Werner
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