Videos
No Obstacles: http://youtu.be/XGXbTiyh0Qw
Obstacles: http://youtu.be/De9qLQHNbWI
Outcome
The location that we chose for our assignment is our classroom, HL106A. In this room, we moved the tables and chairs around twice so there would be a change in the space and in the interaction with the space. The first time around, we chose a large space with no obstacles (besides the perimeter of the room). The second space involved haphazardly moving tables and chairs in order to ensure that there would be more collisions. Despite the fact that we were in the same room for both trials, there is a significant difference in the amount of obstacles. Because of this, we considered the two trials to have been done in different spaces.
Our algorithm was left more open to personal choice and randomness, including differing speeds when walking and how many times we spin around when we reach an obstacle or edge of the boundary space. This creates a generative and emergent outcome because each time due to dizziness and personal preference which can change from spin-to-spin, the direction someone walks after hitting an obstacle or after colliding with another person changes and creates a completely new movement that will vary with new performers and new environments. The outcome is changing as it is being created, leading to a generative and emergent outcome from a set of instructions. As the environment changes, with more obstacles, the outcome changed because the performers were stuck in smaller spaces, leading to more spinning and less collisions with other performers.
Our outcome supports the decisions made in our pseudocode because we all followed the directions that were presented to us. Our outcome was random due to the decision to make everyone spin randomly when they hit a wall. When we hit the walls, we closed our eyes to make our next path indeterministic. Since our paths were indeterministic, our collisions were unpredicted, but all of our dosey-does were of the same length (4 hops).
Pseudo-code:
timer.start
while timer < 150
walkStraight
if collision
if object == wall
spin(randomtime)
if object == person
doSiDo(4, object)