I *THINK* Eugene was asking for ideas that would be useful for over-the-board estimation strategy, not a code-based approach. (Steven's suggestion about O and G may help.)
Another question might be: are Quackle's superleaves known to be all that great -- or at any rate, how far from the mean do you have to be before you're beyond the margin of error for incomplete word knowledge, incomplete positional vision, and suboptimal strategy (assuming over-the-board human-v-human scenarios)? In other words -- it's probably worth it to "minimize" the error, but how close is it really worth the effort to get? -jvp On Fri, Jan 23, 2009 at 9:38 PM, Steven Gordon <[email protected]> wrote: > On Fri, Jan 23, 2009 at 7:29 PM, Graham Toal <[email protected]> wrote: > > On Fri, Jan 23, 2009 at 6:06 PM, Eugene Deon <[email protected]> wrote: > >> I've been trying to tune my leave estimation strategy by solving for the > >> exact values of my commonly considered estimation variables as to > minimize > >> the sum of squared errors between my strategy estimates and all the > leaves > >> in Quackle's "superleaves" file. > >> > >> So far my variables include only: > >> > >> -single letter values > >> > >> -double/triple/quad-letter penalties > >> > >> -vowel/consonant imbalance penalties > >> > >> -bonuses for number of tiles in CANISTER > >> > >> -a couple of letter pair values (QU, YY, IY, FF, ING) > > > > Why all the special cases? The value of a leave is how much it > > contributes to the next play. > > > > So... enumerate every possible play that can be made next with the > > unseen tiles and the leave. (This sounds like a lot of computation > > but it isn't) > > > > For each word, calculate the probability of drawing the tiles you need > > to make the play given the tiles you are holding (ie the leave). (I > > have the code that enumerates that probability function) > > > > Do this for other leaves, and compare. Special cases like letter pair > > values etc fall out in the wash; in fact, it works for larger leaves > > the same way (and faster, as the play choices are more limited) > > > > Graham > > Graham, > > This approach would effectively turn an N ply simulation into an N+1 > ply simulation, except that the last ply would be exhaustive instead > of random. I cannot believe that could be nearly as efficient as a > static rack evaluation at the leave nodes of a simulation. > > Steve > > ------------------------------------ > > Yahoo! Groups Links > > > >
