Initially we wanted to use these techniques to train a robot soccer team, however we soon learned that thse techniques were simply the wrong tool for the job. Other than Tesauro's work on Backgammon we found few worthwhile applications of reinforcement learning. There wasn't anything similar to our soccer problem domain.
Motivation Consider the game of Tetris.
The player is continually given pieces of varying shape that must be positioned and rotated, then dropped on the pieces below. Since these pieces begin to pile up, the player must try to stack them efficiently. Furthermore, if the player manages to complete a row, then that row dissapears thus freeing up more space. The objective is to keep the height as low as possible. People who play many hours of this addicting game, will likely develop strategies for playing.