Tesauro (1995) describes TD-Gammon as a neural network that trains itself as a backgammon evaluation function by self-play, developed to explore ideas in reinforcement learning, whose basic paradigm he sets out.

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.