Placement Into a Flock
This page complements our AAMAS 2015 paper.
Contents
Flock Behavior with No Influencing Agents
The following video shows the behavior of the flock when not being influenced by any influencing agents. In this case, each agent orients itself towards the average heading of its neighbors.
This video depicts 4 separate trials, where each trial is concluded when the flock has converged to travelling at a particular heading.
Drop Case
In the Drop case, we are able to initially drop each influencing agent into the flock at whatever location we desire.
In our AAMAS paper, we consider four different methods in which to determine these initial positions at which to drop the influencing agents. Below we present videos of each of these methods. We show videos in which the number of agents (n) is 10, since this is one value of n that was used to obtain the data presented in Figure 5 in our paper.
As we present videos below, note that we use the same notation as in the paper. Specifically, the number of agents is represented by n, the number of influencing agents is represented by k, and the number of flocking agents is represented by m, such that k+m=n. For the videos shown below, we always use a random seed of 1 for calculating the initial flocking agent positions.
On the bottom right of the videos, you will notice that some numbers are printed out part way though each trial. These numbers are (from left to right): the number of time steps for the flock to converge, a number irrelevant to these trials (always 0.0), the number of flocking agents 'lost', the x-axis average distance from each not 'lost' flocking agent to the center of the flocking agents that are not 'lost', and the y-axis average distance from each not 'lost' flocking agent to the center of the flocking agents that are not 'lost'.
n=10, k=1, m=9 -> 10% of flock is composed of influencing agents
| Random Placement | Grid Placement | |
| Border Approach | Graph Approach | |
n=10, k=2, m=8 -> 20% of flock is composed of influencing agents
| Random Placement | Grid Placement | |
| Border Approach | Graph Approach | |
n=10, k=3, m=7 -> 30% of flock is composed of influencing agents
| Random Placement | Grid Placement | |
| Border Approach | Graph Approach | |
n=10, k=4, m=6 -> 40% of flock is composed of influencing agents
| Random Placement | Grid Placement | |
| Border Approach | Graph Approach | |
n=10, k=5, m=5 -> 50% of flock is composed of influencing agents
| Random Placement | Grid Placement | |
| Border Approach | Graph Approach | |
Drop + Reposition Case
In the Drop + Reposition case, each influencing agent begins at whatever location we desire and then it attempts to reposition back to it's initial position if it stays too far away.
In our AAMAS paper, we consider two different ways in which to determine the positions at which the influencing agents are initially placed in this case. Below we show videos in which the number of agents (n) is 50 and the number of influencing agents (k) is 5. For each video, we use a random seed of 0 for calculating the initial flocking agent positions.
| Grid Desired Positions, Speed 0.4 | Border Desired Positions, Speed 0.4 | |
| Grid Desired Positions, Speed 1.0 | Border Desired Positions, Speed 1.0 | |
Dispatch Case
In the Dispatch case, each influencing agent begins at one of more stations outside the flock and is directed to travel to a particular location in the flock. In this section we show videos in which the influencing agents begin at one station located at a corner of the flock.
In our AAMAS paper, we consider three different methods in which to determine the positions to which the influencing agents are directed to travel in this case. Below we present videos of each of these methods. We show videos in which the number of agents (n) is 50 and the number of influencing agents (k) is 5. For each video, we use a random seed of 0 for calculating the initial flocking agent positions.
| Random Desired Positions, Speed 0.4 | Grid Desired Positions, Speed 0.4 | |
| Border Approach Desired Positions, Speed 0.4 |
| Random Desired Positions, Speed 1.0 | Grid Desired Positions, Speed 1.0 | |
| Border Approach Desired Positions, Speed 1.0 |
Dispatch Case (Multiple Initialization Points)
In the Dispatch case, each influencing agent begins at one of more stations outside the flock and is directed to travel to a particular location in the flock. In this section we show videos in which the influencing agents begin at two stations located at opposite corners of the flock. Each influencing agent begins at the station closest to its desired position.
Below we show videos in which the number of agents (n) is 50 and the number of influencing agents (k) is 5. For each video, we use a random seed of 0 for calculating the initial flocking agent positions.
| Grid Desired Positions, Speed 0.4 | Border Desired Positions, Speed 0.4 | |
| Grid Desired Positions, Speed 1.0 | Border Desired Positions, Speed 1.0 | |