Scrabble game using machine learning I've been thinking if machine learning can be used to play the game Scrabble. My knowledge is limited in the ML field, thus I've seeking some pointers :) 

I want to know how could I possibly build a model that picks a move from all the given valid moves of the current game state, and then plays the move and wait for the delayed reward. The actions here aren't static actions, they are basically selecting move to maximize the final score.

Is there any way to encode the valid moves and then use a model to pick those moves?

I've also considered the genetic approach, but I think if I can represent my move with a set of features (score, consonantVowels ration, rack leave score, #blank tiles after the move, ...etc), training a neural network like this could take a long time.

Another training related question, is it feasible to run the training on a GPU given that I will be waiting for a response (the new game state) from the opponent (e.g. Quackle) after every action?

Thank you :)
Scrabble was solved using reinforcement learning achieving super-human performance. If you are interested, you can start reading about it here: https://en.wikipedia.org/wiki/Maven_(Scrabble)#cite_note-1 

You can also read about it here: http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/games.pdf (there're several slides about Maven)