Outcome
What we basically did was run this algorithm 4 different times, choosing different actions for each person via a random number generator in each time. With this algorithm, we had an intended outcome in that the entire group would be participating in various basketball actions and moving around the court. However, there are still many aspects of the final outcome that cannot be predicted. Even though we had full knowledge of the workings of the algorithm, there were still several movements in the video that were not planned for in the algorithm. This reflects generative emergence in that even though we knew everything about the system in which we were working, new and unexpected events still arise. An example is how in some of the videos, there were instances when 3 people would start moving together as a group, or when all 4 members would be clustered in the same spot. Additionally, there was a case when a member had two specific actions (3 and 5) for when they did not have the ball, they would move in the same path back and forth, without any divergence from that point (at least till they got the ball again). We certainly did not expect that to occur from the pseudo-code. In a way, this is similar to the bugs that crop up in games (called easter eggs). These are usually some events or glitches that the game programmers did not intend to produce, but were a happy accident. Likewise, when creating movement forms, or any art forms that are meant to be emergent, having such surprises actually makes the final outcome much more thought-provoking.