We are interested in the automation of planning and learning in dynamic physical environments. Recently we have begun to consider the game of pinball as a robotics testbed. Our intention is to build an autonomous learning agent that controls the game and improves its performance over time. We believe that pinball will give us a structured environment in which to investigate issues of planning and learning, while providing the real-world constraints of uncertainty and real-time control. Our work to date has led to a simple, physically realistic pinball simulation, which we are now using to test learning agents. In the future we will have a physical game interfaced to our computer system.