Abstract: We introduce Group Motion Graphs, a data-driven animation technique for groups of discrete agents, such as flocks, herds, or small crowds. Group Motion Graphs are conceptually similar to motion graphs constructed from motion-capture data, but have some important differences: we assume simulated motion; transition nodes are found by clustering group configurations from the input simulations; and clips to join transitions are explicitly constructed via constrained simulation. Graphs built this way offer known bounds on the trajectories that they generate, making it easier to search for particular output motions. The resulting animations show realistic motion at significantly reduced computational cost compared to simulation, and improved control.