Well well, I've been rather lazy with slot grammars in the last few months. I did something but, TL;DR; I did not find anything particularly useful or interesting, and I feel I need some fresh idea or approach before pursuing this again.
So (brief resume) I developed a 'figure of merit' (Nbits) for grammars and used it to find slot grammars which scored quite high on this metric (which I called looping slot grammars). What I wanted next to do was to explore the space of looping slot grammars to see if I could find better ones. I used a MonteCarlo method to generate grammars, examined several tens of millions of them, tweaking the grammars by hand to try to get the best results. I actually found thousands of grammars which score better than my previous record, but this is more a bane than a boon because they all score very similarly and there is no obvious way to select one. But just for reference, this is the best one I found (whole VMS, Rf1a-n transcription, words with rare characters removed):
SLOT 1: ch sh y
SLOT 2: eee ee e q a
SLOT 3: o
SLOT 4: iii ii i d
SLOT 5: y p f k l r s t cth ckh cph cfh n m
Looping it 5 times it can be used to encode the whole VMS (with 99.8% coverage) using 480985 bits (the previous record holder, LOOP-Lay-oa, needed 484688). Just for reference again, the second-best grammar I found uses only 30 more bits .
I also followed oshfdk's suggestion above and worked with the different sections of the manuscript, finding the same disappointing behaviour. Moreover, all the 'best' grammars for one section perform poorly on the other sections and on the manuscript as a whole, and they have structures different from the 'best overall' shown above (ie. [n m] may not cluster with the other characters, [y] may not be duplicated, etc.).
However, I would like to notice that the 'looping slot grammar' approach tries to divide the Voynich word types in 'chunks' (ie. the 'best' grammar above finds aiin ar ol al qok etc. as chunks) which are then used to 'compose' words, and as such it has many analogies with, say, the Naibbe cipher or core-mantle-crust or the 'syllables' recently discussed elsewhere here by dashofsk (if I'm not mistaken!).
I would like I could write a software which tries to divide the Voynich words in chunks, trying to maximize the Nbits metric, but in an unsupervised way (without the need for an underlying slot grammar). I know there are unsupervised clustering algorithms around which could maybe be adapted to the task, but I don't know them well (read: at all) and in any case it looks like a major project which I'm surely not in the mood to tackle at the moment
And ofc there's no guarantee of success, but this is a given anyway with the VMS.
So (brief resume) I developed a 'figure of merit' (Nbits) for grammars and used it to find slot grammars which scored quite high on this metric (which I called looping slot grammars). What I wanted next to do was to explore the space of looping slot grammars to see if I could find better ones. I used a MonteCarlo method to generate grammars, examined several tens of millions of them, tweaking the grammars by hand to try to get the best results. I actually found thousands of grammars which score better than my previous record, but this is more a bane than a boon because they all score very similarly and there is no obvious way to select one. But just for reference, this is the best one I found (whole VMS, Rf1a-n transcription, words with rare characters removed):
SLOT 1: ch sh y
SLOT 2: eee ee e q a
SLOT 3: o
SLOT 4: iii ii i d
SLOT 5: y p f k l r s t cth ckh cph cfh n m
Looping it 5 times it can be used to encode the whole VMS (with 99.8% coverage) using 480985 bits (the previous record holder, LOOP-Lay-oa, needed 484688). Just for reference again, the second-best grammar I found uses only 30 more bits .
I also followed oshfdk's suggestion above and worked with the different sections of the manuscript, finding the same disappointing behaviour. Moreover, all the 'best' grammars for one section perform poorly on the other sections and on the manuscript as a whole, and they have structures different from the 'best overall' shown above (ie. [n m] may not cluster with the other characters, [y] may not be duplicated, etc.).
However, I would like to notice that the 'looping slot grammar' approach tries to divide the Voynich word types in 'chunks' (ie. the 'best' grammar above finds aiin ar ol al qok etc. as chunks) which are then used to 'compose' words, and as such it has many analogies with, say, the Naibbe cipher or core-mantle-crust or the 'syllables' recently discussed elsewhere here by dashofsk (if I'm not mistaken!).
I would like I could write a software which tries to divide the Voynich words in chunks, trying to maximize the Nbits metric, but in an unsupervised way (without the need for an underlying slot grammar). I know there are unsupervised clustering algorithms around which could maybe be adapted to the task, but I don't know them well (read: at all) and in any case it looks like a major project which I'm surely not in the mood to tackle at the moment
And ofc there's no guarantee of success, but this is a given anyway with the VMS.