tl;dr: I wrote a simple Tic Tac Toe AI as an exercise. You can get it on github
I am currently considering writing a basic chess AI as an exercise in AI development and to help me analyze my own games (and hopefully get a better chess-player just by thinking about how a machine would do it). As a small exercise and to get some familiarity with the algorithms involved, I started with Tic Tac Toe. Because of the limited number of games (only 255168) all positions can be bruteforced very fast, which makes it an excellent exercise, because even with a very simple Minimax-Algorithm perfect play is possible.
My AI uses exactly this algorithm (if coded a little crude). It comes with a little TUI and a small testsuite, you can try it like this:
$ git clone git://github.com/Merovius/tictactoe.git $ cd tictactoe $ make $ make test $ ./tictactoe
You will notice, that there already is no noticable delay (at least not on a relatively modern machine), even though the AI is unoptimized and bruteforces the whole tree of possible moves on every move.
Next I will first refactor the basic algorithm in use now, then I will probably implement better techniques, such as limited search-depth, αβ-Pruning or machine learning. I will then think about moving on to a little more complex games (for example Connect 4, Mill or Hex seem good choices). Then I will decide how big the effort would be for chess and if it's worth a try.