TicTacToe AI Making Incorrect Decisions
- by Chris Douglass
A little background: as a way to learn multinode trees in C++, I decided to generate all possible TicTacToe boards and store them in a tree such that the branch beginning at a node are all boards that can follow from that node, and the children of a node are boards that follow in one move. After that, I thought it would be fun to write an AI to play TicTacToe using that tree as a decision tree.
TTT is a solvable problem where a perfect player will never lose, so it seemed an easy AI to code for my first time trying an AI.
Now when I first implemented the AI, I went back and added two fields to each node upon generation: the # of times X will win & the # of times O will win in all children below that node. I figured the best solution was to simply have my AI on each move choose and go down the subtree where it wins the most times. Then I discovered that while it plays perfect most of the time, I found ways where I could beat it. It wasn't a problem with my code, simply a problem with the way I had the AI choose it's path.
Then I decided to have it choose the tree with either the maximum wins for the computer or the maximum losses for the human, whichever was more. This made it perform BETTER, but still not perfect. I could still beat it.
So I have two ideas and I'm hoping for input on which is better:
1) Instead of maximizing the wins or losses, instead I could assign values of 1 for a win, 0 for a draw, and -1 for a loss. Then choosing the tree with the highest value will be the best move because that next node can't be a move that results in a loss. It's an easy change in the board generation, but it retains the same search space and memory usage. Or...
2) During board generation, if there is a board such that either X or O will win in their next move, only the child that prevents that win will be generated. No other child nodes will be considered, and then generation will proceed as normal after that. It shrinks the size of the tree, but then I have to implement an algorithm to determine if there is a one move win and I think that can only be done in linear time (making board generation a lot slower I think?)
Which is better, or is there an even better solution?