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Neat Algorithms - Flocking

harry.me

21–26 of 26 posts

Re: Neat Algorithms - Flocking

#21
post #17

Bat swarms and game AI aside, what are the real world applications of something like this? It strikes me as significantly less useful than say a neural net.

Au contraire, these [swarms can be very useful](http://en.wikipedia.org/wiki/Swarm_intelligence). No one machine learning algorithm is best for all tasks. With current state-of-the-art technology, a human must choose the most appropriate algorithm by using what you could consider a priori knowledge about the task.

Re: Neat Algorithms - Flocking

#23
post #9

Woah! Super cool idea. So many ways you can take this to a new level. Also, if anyone is looking to contribute to some open source, this would be a great opportunity as there is lots of epic optimization problems in this algorithm to work on. For example, whats the fastest data structure/algorithm to make searching for neighbours?

I'd guess some type of BSP tree. I agree, it looks fun to work on, see how massive of a simulation you could run in real time.

Re: Neat Algorithms - Flocking

#24

Here's a CoffeeScript port of this algorithm I did awhile ago. https://gist.github.com/3733089 and a demo: http://wsb.im/flocking/index.html Definitely fun stuff to play around with.

Yours is a lot more fun to play with. Good job!

Re: Neat Algorithms - Flocking

#25

The original paper[0], published in '86, in addition to being a huge step forward over contemporary graphics techniques, is extremely comprehensible and an excellent read. It also goes into some detail about collision avoidance, which is hard to see in the browser demo (boids will avoid the mouse but not in a very large area), and goal seeking, which isn't in it. It ends with a fairly eyebrow-raising testament to the…

If anyone's interested, I have started implementing Reynold's demos on an HTML 5 canvas:

http://www.etiennek.com/demos/html5steering/

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