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This paper describes the properties of a set of simple neural network oscillators suited to two robotic tasks. One robotic task is "wall-bouncing", in which the robot repeats the process of hitting balls that rebound from the wall. Another robotic task is "passing a ball", in which two robots repeat the process of passing balls to each other. The motions of the robot (paddle) are controlled by a set of neural oscillators consisting of four weakly coupled Bonhoffer-van der Pol (BVP) oscillators. We demonstrate that rhythmic movement of the paddle emerges as a stable limit cycle generated by the global entertainment between the paddle, the neural system, and the environment, including balls.