(26-06-2025, 08:05 AM)Mauro wrote: You are not allowed to view links. Register or Login to view.

(26-06-2025, 01:47 AM)ReneZ wrote: You are not allowed to view links. Register or Login to view.I have often wondered about the initialisation method. After all, the self-citation explains (in a way) how to set up the 'next' word from a previous section, but I never saw anything about how to start. 

The seed sentence is in the 'metadata' at the top of Torsten's output files. For the one posted on GitHub:

Quote:#text.initial_line=pchal shal shorchdy okeor okain shedy pchedy qotchedy qotar ol lkar

Note: actually the last two words 'ol lkar' are then not used in generating the text, I don't know why the sentece is truncated, maybe a bug, but it's not important for the successive elaboration.

(26-06-2025, 01:47 AM)ReneZ wrote: You are not allowed to view links. Register or Login to view.Another thing I have been curious about is how the most frequent words come about.

There are probabilty parameters inside the software. Ie. this instruction (file You are not allowed to view links. Register or Login to view.):

Quote:{{"k"}  ,  { new  Substitution( new String[] {"t"}, 77), new Substitution(new String[] {"p"}, 94), new Substitution(new String[] {"f"}, 100)}},

I think it determines what can be substituted for 'k': I guess 77% of times with 't', (94-77)= 17% of times with 'p' and the remaining times with 'f'.


I think a human being would behave more of less the same way, just with greater fuzziness, and with the 'parameters' varying in time.