![]() ![]() So the actual data that I train on is like this X = [0,2,2,Ġ means empty, 1 means an X is there, 2 means a Y is there. So I have a function that converts a winning sequence into a series of board positions, and a label saying which move is next. ![]() In other words, given a board with none or some X's and O's, assuming it's player X's turn, predict a good move (1-9) based on past observations a boards, and knowledge of the next move that was chosen Now, I'm not doing machine learning on the winning sequences, because I want the program to get a "current board position" not a sequence. So in the first sequence, that means that player X chose 4, O chose 2, X chose 5, O chose 3, X chose 6 A sequence represents series of choices, 1 to 9, on the game board. I have a function getWinSequences('X', 1000000) that returns of list of sequences that win for X. Is it reasonable to expect to learn to predict a good move from 1 million samples of games that player X won? My idea was to create a simple tic tac toe game, and have it just play millions of random games, and use the data to learn to predict the next move based on sequences that won in the past. ![]() I decided to practice by making up some problems and solving them. ![]() My only experience with Machine Learning is Andrew Ng's Coursera course, but I did work through that just fine and passed with 100%. ![]()
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