Shepherding Random Numbers
119 points by andra_nl 8 years ago | 15 comments- JadeNB 8 years agoAs a mathematician but not a statistician or probabilist (so very much not an expert here), this:
> When we look at this it can sometimes seem as if there is a pattern emerging from the behaviour. However, if you feel like you can see such a pattern it is entirely coincidental, since the nodes are completely unaware of each other.
bothered me. It seems to me that the fact that patterns can emerge from non-coördinated behaviour is one of the interesting facts about mathematics. See, for a dodgy example—because there is some coördination—firefly flash-locking; and, for a genuine example that I literally just happened to be reading about this morning, the fascinating Nobel-Prize work discussed at https://johncarlosbaez.wordpress.com/2016/10/07/kosterlitz-t... . (I encourage you to go read the latter if you haven't already; as you will expect if you have read Baez's work, it's exposition at a level just about anyone, including non-mathematicians, can probably understand of scientific Nobel-Prize work, and those don't come along very often.) I guess, though, that to make any rigorous statement that this can occur, and isn't just an illusion, one has to make a rigorous definition of 'pattern', and the implicit definition of something like "externally imposed structure" has just as much claim to being 'correct' as anything I could cook up.
- open_nsfw 8 years agoI'm pretty sure each point was rendered independently - i.e. the nodes have no interactions. So unlike flocking, they are are entirely coincidental.
- strainer 8 years agoI enjoyed the link thanks. The patterns concerned there develop out of unstable states (random or patterned) by ~preferences of the interconnecting medium. I notice two dimensional mediums were only examined and 3d may provide scope for more complex phenomenon. The apparent patterning which Hoff mentions is entirely coincidental and uncoordinated by any medium/connection between random variates. Collections of random variates are able to present seemingly unlikely relationships or artefacts which can amount to meaningful or stable forms in other contexts - as monkeys at a keyboard chancing on a few pearls of wisdom.
I have spent a while scrutinising the appearance of patterns in test plots for my random number library: http://strainer.github.io/Fdrandom.js/ and learned that they can be expected to occur to some degree. There surely must be some theoretical and philosophical investigations of chaos capacity to chance on order.
- open_nsfw 8 years ago
- rawnlq 8 years agoThere are a lot of very cool math properties hidden in each of these examples so I want to start a discussion on modeling some of them:
For the "memory" example, each particle is moving Uniform(-k, k) at each timestep (where k is some just some fixed distance). So the the distribution of the position of a particle at timestep t is the sum of t identically independent distributions, which will converge to a normal distribution, specifically with Uniform(a, b) having variance (b - a)^2 / 12, you converge to:
N(0, t * k^2 / 3)
So it turns out these particles end up behaving kind of like brownian motion! (Note I didn't take into account hitting walls. I am not sure how to model that?)
For the "velocity" example, empirically you can see that if you just let it run forever the points will just end up bunching at the walls. This makes sense since if there's a positive velocity in either direction it's hard to flip your velocity back into the other direction to get off the wall. By symmetry you expect half to be bunched on one wall and half on the other.
A fun question to ask then is if the velocities will accumulate so much in one direction such that it will always stay stuck on one wall after you run it a long enough time. I believe the answer is no! It will always switch directions again due to the fact that the probability that a random walk on a line returning to the origin has probability 1 as you run it forever (google recurrent random walk in 1 or 2 dimensions). This means the velocity (which is doing the random walk) will have to cross 0 and flip signs at some point. So although you will mostly find these particles hugging the walls, they will keep switching sides forever!
I think there are a lot of other really cool properties in these fancy visualizations waiting to be discovered.
- bajsejohannes 8 years agoRecommend following the link at the bottom: http://inconvergent.net/generative/
Very nice work. My favorite is this: http://inconvergent.net/generative/trees/
- visarga 8 years ago<offtopic>It's interesting how random numbers are essential in AI. Dropout and adding random Gaussian noise are standard practices. Random numbers are also essential in exploration strategies in Reinforcement Learning (epsilon greedy).
In the human brain, signals are stochastic, so they embed a large portion of randomness with each bit of information. Amazingly, adding noise to signals helps learning. Intelligence is at the edge of order and chaos - the lesson being that chaos is an essential part of it.
- DanBC 8 years agoThese are beautiful.
If you're interested in these you might also be interested in the book "Computers, Pattern, Chaos, and Beauty":
http://www.worldcat.org/title/computers-pattern-chaos-and-be...
- noelwelsh 8 years agoLooks very interesting!
Another suggestion: I'm currently working through "Creating Symmetry" (http://press.princeton.edu/titles/10435.html) which is a very readable maths text and one that involves some gorgeous images.
The author calls is a postmodern maths book, and says "Postmodern books are situated in time and place, taking into account the identities of both reader and author. Here I am, writing to reach you; please join me." The world needs more postmodern maths books.
- zimpenfish 8 years agoAh, that book very much aligns with my current interests. Thank you kindly!
- zimpenfish 8 years ago
- noelwelsh 8 years ago
- dorianm 8 years agoThat's amazing!
He also has a very interesting Twitter account where he posts his experiments: https://twitter.com/inconvergent
- joshu 8 years agoI love his stuff. I've ported some of his code on GitHub to emit gcode and run it on my various drawing machines. Fun stuff.
- mturmon 8 years agoGiven how close to random walks (e.g., with absorption/reflection) some of these concoctions are, the probabilist in me wants a higher-level explanation, in a few cases, to be part of the post. Either way, it's fun to look at.
- marmaduke 8 years agoYay stochastic differential equations..
- rawnlq 8 years agoI think he has to sample his position deltas from a gaussian with mean 0 and variance equal to the time since last update for it to be a valid brownian motion.
See https://en.wikipedia.org/wiki/Brownian_motion#Mathematics
- rawnlq 8 years ago
- jijojv 8 years agovery nice animations