7 Additional Experimental Results and Further Analysis

The descriptions of each model setup are provided in Section 8.2 . The reason is that different types of agents have distinct behavior patterns or feasibility constraints. Compared to single-stage training, the 4.0s NBA dataset to demonstrate the effect of different numbers of edge types and re-encoding gaps. More specifically, in the first case of Figure 7, for the player of the green team in the middle, the historical steps move forward quickly, while our model can successfully predict that the player will suddenly stop, since he is surrounded by many opponents and he is not carrying the ball. Such case is a very common situation in basketball games.