Modeling likely challenge responses using an imperfect probabilistic lexicon model of Q's opponent is definitely more complex, but with a clear advantage against a lexicon-limited player... e.g. holding ACILLVY the expected value of CAVILLY for (say) 87 or zero (dep on whether it gets challenged) static value versus CAVIL for 25, or slightly more if it gets challenged, depends crucially on the probabilities you assign to whether your opponent will challenge.
I thought the usefulness of the modeling for making Q stronger might make the strategy appealing to Q's developers, and the possibility of using an imperfect model of the lexicon (used by Q for inference about fallible players' responses) as Q's own lexicon for making Q play at a lower level is just a side benefit. A big side benefit. Note that Q against Q might also produce phoney plays if Q doesn't know it's playing itself, and simulations might produce an optimal mixed strategy... To make an expanded lexicon with phoneys, you can start with some manual entry of common misspellings and then automatically generate using transposed vowels and noun+ED or verb+LY constructions and the like. The construction of plausible-looking phoneys is an independent exercise, of course, from the programming task of allowing an imperfect probabilistic lexicon model. However, a very large list of phoneys could be whittled down to a better list by letting Q play real opponents and learn which phoney it could sneak by real players. On 9/6/07, John Van Pelt <[EMAIL PROTECTED]> wrote: > > It would probably be more complex to include in the sims the probability > computation (per move) that opponent might challenge -- figure the > probability confidence that the given word carries a given probability > confidence in the opponent's lexicon? > > The real question is how to seed a starter lexicon with data like this? > > jvp > > >
