It is fascinating to compare & contrast chess, Go, and backgammon, and how quite different approaches are needed to program in each. For chess, 'pure calculation' is most effective, while the author suggests MC is good for Go & others. In backgammon, TD-gammon used a rather naive neural net approach and trained itself, optimizing its own play over time! It is also interesting how computers' success in these areas feeds back into how humans play the game (at least in backgammon and chess opening strategy).