Absolutely agreeable. But a dedicated GUI can handle it easier without even modifying SF. I would suffice to give the Romi learning algorythm to the GUI for having SF playing with a learning book (and saving pgn games as well). Then, Romi can just import the games into her learning file.Ovyron wrote:Rodolfo, for elo points I think RomiChess's method is the best, as it eventually can learn how to beat anyone from a given position, doing it from starting position would just take a while...
The problem is Romi reaching won positions and losing them, then avoiding them because it lost...
For this conundrum I propose the following solutions:
1. Implement Romi Learning into Stockfish! It could potentially be 200 elo stronger than any opponent after a few thousand training games. The main elo would come from being ahead of the clock as Stockfish would learn what the opponent plays and just move instantly, deeper and deeper, what won in the past. This is also Michael's dream, given Romi is open source, the only reason this hasn't happened is lack of interest.
2. Have an adapter that uses Romi as book, then switches to Stockfish to play the game, then sends the pgn to Romi with game result so it learns. The adapter could be simple, and could be used to make any engine a book for another engine: just play engine A's moves if they're played in less than a second (book assumed), otherwise (A took longer than 1 second) fire up engine B (assumes out of book) for the rest of the game.
(I say "her" because Romi is a woman!)