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sheep19

[Flocking] Avoid many "sub-flocks" in Cohesion

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Hi, I am developing a simulation of flocking for my thesis.

 

I am using Unity3D and C#.

 

For fast calculation of K-nearest neighbors I use the alglib library, which provides methods for it (uses a K-D tree). It also supports approximate knn for faster results, which is what I'm using since I don't need 100% accuracy.

 

 

In my tests I have 500 boids (birds) flying around. They are spawned near to each other so they form a swarm. However, after some seconds, this big swarm begins to break into smaller ones. I'm 99% certain that this is because for Cohesion's a-knn I use 30 for k, which means take into account the 30 "closest" (not really the 30 closest since I'm using aknn).

 

This has the effect that I described above - many small swarms of about 30 boids each, which is very logical since each boid considers a neighborhood of 30 closest boids for Cohesion).

 

----------------

 

When I change the k for Cohesion to bigger numbers (e.g 100) less swarms are formed. If I set k to 500 only one is formed. But this has a very big downside.

For k = 30, I get ~20 fps

For k = 500, I get ~3 fps

[a-knn epsilon is 50.0 for both)

 

Is there a solution to this? I'd like less swarms but better performance.

Is alglib slow? I couldn't find something else... I'm not doing anything special in my code, just the usual behaviors - Cohesion, Separation and Velocity Match. And one more, Cohesion to an anchor object so the flock will follow a path I want.

 

Thanks in advance.

 

2eas4sh.png

Edited by sheep19
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If you want global cohesion for the whole group, add a term that steers towards the center of mass of the whole flock. This should be very fast to compute, because it's the same point for all individuals.
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Alvaro's approach may well work, Another possibility might be (if you can easily access this info) steer each mini-flock towards the other mini-flocks, so I guess it would be a hierarchical flocking algorithm. I'm not sure whether either would look the same as one big flock, it can be hard to tell with emergent systems.

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It's pretty much mathematically provable that over time, your flocks will break into groups that are proportional to some degree with your k value. It's self-reinforcing. 

 

One method is to not use a hard-cap on k -- but rather use all neighbors within distance d. It's a subtle difference, but I think it would help.

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It's pretty much mathematically provable that over time, your flocks will break into groups that are proportional to some degree with your k value. It's self-reinforcing. 

 

One method is to not use a hard-cap on k -- but rather use all neighbors within distance d. It's a subtle difference, but I think it would help.

 

I see, thank you.

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