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Subject: Re: Distance-to-mate vs Best-move tables

Author: Ratko V Tomic

Date: 08:01:40 10/23/01

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>I don't see how.  I will never probe them most likely.
> Because once I get a TB "hit" I don't search down that
> branch any further, period.

Well, not in that evaluation. But in the hundreds of millions
of evaluations with a limited number of pieces (which may
have few hundred millions distinct arrangements all together)
the odds of hitting the "wasted" piece arrangement later are
certainly much greater than the odds of hash table hits in
the middle game. Your cutoff argument would equally imply
that the middle-game hash tables are useless. The point is
that you can arrive to the same position may different ways,
especially for the kind of material on the board the
tablebases cover.

Note also that fetching a chunk of table from the disk, to
perform what seems to program "one lookup," via file read
or the "transparent" memory paging by the OS, will take more
time than few hundreds simple RAM/CPU based calculations to
deduce the same value. That's why compressed disks work
often faster than uncompressed -- a single extra wait of
few milliseconds for a disk spin to fetch a page pays for
millions of computation steps of the decoder, which in turn
covers much greater quantity of data than the page being
fetched.

>>Considering also that using the best-move you may be able to
>>fit couple times more table information on any given disk
>>or RAM size you have available,
>
> All the TBs so far use 8 bit values.  So there is no savings
> on the "best move" approach until we get to the 6 piece files
> with mates > 127...

Well, no saving if you encode the best move in a byte. With the
right pattern preprocessor/dictionary extractor and move generator
the best move ought to fit on average in 1 bit or less. The best
move table can easily take advantage of any endgame rules or
knowledge, human or computer extracted patterns, to make the
move generator produce the best-move in many fewer tries than
a random move generator would do (which is the most of a
pattern that Huffman or similar memoryless stream compression
could squeeze out).

With distance-to-mate tables the only compression available is
of that 'memoryless stream' type, since the values in these tables
are result of multi-step iterations of highly nonlinear functions,
so for all practical purposes any simple connection to the
patterns in the initial positions is lost by the time you reach
the terminal node and get the distance value. The only regularity
left which is readily extractable are the bulk frequencies of
different distance values. The rest of pattern is oblitareted.

The best-move tables are more similar to gradient methods of
optimization which are sensitive to the local patterns. The move
generator used in the best-move table decoder can easily and
beneficially (for compression ratio) absorb any amount of
knowledge/regularity in data one can come up with.



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