lpetrich
Contributor
Instead of practicing, this AI mastered chess by reading about it - MIT Technology Review noting
[1907.08321] SentiMATE: Learning to play Chess through Natural Language Processing
Chess has a big literature about it, and part of that literature is commentaries on games. The researchers used 2700 games with commentaries, and trained a natural-language-processing (NLP) model on them. A side that makes good moves tends to win, and a side that makes bad moves tends to lose. That offers a way of recognizing "good" and "bad", and one can then use this to get assessments of individual moves. That was then used to train a chess engine, SentiMATE. It is not as good as some others, but it is fairly good.
[1907.08321] SentiMATE: Learning to play Chess through Natural Language Processing
Chess has a big literature about it, and part of that literature is commentaries on games. The researchers used 2700 games with commentaries, and trained a natural-language-processing (NLP) model on them. A side that makes good moves tends to win, and a side that makes bad moves tends to lose. That offers a way of recognizing "good" and "bad", and one can then use this to get assessments of individual moves. That was then used to train a chess engine, SentiMATE. It is not as good as some others, but it is fairly good.
The researchers say the learning techniques used by SentiMATE could have many other practical applications beyond chess. For instance, they might help machines analyze sports, predict financial activity, and make better recommendations. “There is an abundance of books, blogs and papers all waiting to be learnt from,” the team points out.