Apart from the lame April fools date obfuscation in the piece, the actual numbers already made the story incredible without reading further!Don wrote: In the book One Jump Ahead, Jonathan Schaeffer at some point thought that it might be good enough to say that if you were N checkers ahead you could write the position off as a win - and much to his surprise this was not a valid assumption even for a fairly large number of checkers, and in checkers a single pawn (or checker) ahead is a huge advantage. It's been my experience that no simplistic rule can be reliably used to stop a search without introducing scalability issues - because you will ALWAYS be able to find a position where it is badly wrong! In this study Vas it treating 5.12 as a forward pruning rule to represent a complete search to the end of the game.
First, the solution space of checkers was 10^22 (the search space was 10^40), which was reduced to 10^14 by a bidirectional search. The back-end search built 10^14 database positions, and the front-end search built 10^14 opening positions. Schaeffer (http://ilk.uvt.nl/icga/journal/pdf/toc30-4.pdf) estimates it would take 200 core years to re-create this solution. Second, Schaeffer also estimates that the solution space for chess is about the square of that of checkers.
How does Vas's claim stack up against this? Hm, about 10 times the computing power but about the square of the search space (10^80 vs 10^40). Being liberal, let's suppose the actual solution space is the square root of that (10^40). However, the efficient bidirectional search (giving almost another square root reduction), was dependent on 10-piece databases which were already reachable from shallow root searches. Without the equivalent chess databases, the 10^40 solution space will not be reduced by another square root. And covering 26 orders of magnitude with 10 times more computing power...
BTW, the way checkers was solved by Schaeffer et al. was by iterating over the threshold value. So a real proof would take the 5.12 as the first step in such an iteration, and stepwise increase it all the way to a mate score.
