3 ms·

Similar to "flocking" behaviour in birds that only requires notice to be taken of immediate neighbours in the flock.

TeMPOraL 5y ago
Yes, something like that - and I'm wondering if there's a way to imprint a pattern on such flock of birds, so that they then flock into appropriate shape from whatever starting configuration they were in, and maintain the shape over time, even in the face of strong winds or some of the flock members dying. Here's one idea I'm thinking about: flocking-like equations in "boids" simulations are local, a pure function of (the observed state of) the neighbors. In a typical implementation, they just compute velocity/acceleration vectors out of position/velocity/acceleration/class of the neighbors[0]. And the result are pretty, fluid, and uniform in steady-state flocks. But what if we added more observable state and equations to this? Imagine each boid having a "color", a value that is a function of not just the color of the neighbors, but also of their position/velocity/acceleration/class. And then, the equations computing velocity/acceleration take this color into account too, e.g. by offsetting the result by some function of the neighbors' colors. Could we then design the f([colors]) -> v/a offset and f([everything]) -> color functions so that they end up forcing the flock into an arbitrary uniform shape? I believe we could, but I'm not sure how to define these functions for any particular shape. (Or, in short: I'm looking for a method to turn an arbitrary picture into an error term for boids rules that makes the flock assume the shape of the picture, instead of an uniform blob.) I'm sure there must be some pre-existing theoretical work behind finding such functions - this problem feels like a cousin of the "find a formula that draws a target picture on X/Y plot". I just don't know the right keywords to look this up. But this is kind of the idea on the back of my head - encoding desired group behavior in a function that is common to every member of the group and is entirely local (only a function of the immediate observed environment), but that forces the system to settle in a desired configuration. -- [0] - "class" being e.g. member of same species, a predator, or a prey.
- Wildgoose 5y ago
  Yes. Imagine that the "boids" change colour as well as alter their X, Y, Z position. That supplies additional "guiding" information to provide purpose and also alter behaviour, in much the same way that hormones act on a growing foetus. And this reminds me of those audience experiments with people holding up blue and red cards and using this "vote" to successfully steer a vehicle.
  - TeMPOraL 5y ago
    Yup. Also nothing says the boids have to execute a single behavior all the time. In a parallel comment, I described an idea where boids first start doing nothing except publishing a "depth" value that's a function of their neighbors "depth" value, waiting for the system to settle (as detected by neighboring values not changing by more than some fixed epsilon over some fixed Δt). They could then record their individual values and continue to a second algorithm (e.g. traditional "boids"), that uses this (now fixed) "depth" value as a parameter. This is, in general, a pattern for individual unit to discover their role in the group, without ever knowing the whole group. I just realized this sounds like things the field of "distributed consensus" deals with - I'll add that to my research list. I remember the voting games and "Twitch plays X" events. It's kind of a different situation (external controllers voting on control input to a single actor), but there might be some parallels.
- hnlmorg 5y ago
  It might be worth first reading up on the research being drone performances. The current model is basically what I'd already described (https://eandt.theiet.org/content/articles/2021/04/there-s-no-business-like-drone-business/ https://eandt.theiet.org/content/articles/2021/04/there-s-no...) but research is happening to use "AI" to navigate swarms (eg https://www.youtube.com/watch?v=7KIa9FlmbRc https://www.youtube.com/watch?v=7KIa9FlmbRc) The real problem with such research is it might work on a quadcopter with room for a chipset capable of relatively powerful real time compution (be that an off the shelf CPU or something more bespoke), but that doesn't scale down to the grain of sand level. At that point you'll want to offload as much computation overhead as you can. Which, again, brings me back to my original post. Maybe one day in the distant future (if we haven't annihilated each other first) we'll have the technology to built smart grains of sand. But it's seems pointless theorising about something that might just as easily be deprecated by some other fantasy device by our current technological capabilities. Anyhow, if you're after a paper on the actual calculations you'd run to convert a database of nearest neighbour coordinates into a matrix that can be used to instruct those robots, then I don't have anything directly to hand on that. When I've looked this stuff up in the past I've found most of the time it was proprietary. Maybe there is a paper I've missed. However I have seen papers doing similar work (in the sense that there is transferable logic) in a two dimensional fields, eg matrix reordering.
  - TeMPOraL 5y ago
    Thanks! I haven't thought about drone performances. In retrospect, it's a good starting point. I've seen plenty of videos of drone swarms being synced up to produce shapes and animations. > Maybe one day in the distant future (if we haven't annihilated each other first) we'll have the technology to built smart grains of sand. But it's seems pointless theorising about something that might just as easily be deprecated by some other fantasy device by our current technological capabilities. Maybe. But I feel this isn't pointless - I find myself constantly returning to this topic whenever I follow seemingly unrelated avenues of idle curiosity (e.g. "how to build self-maintaining systems", "how to do in-orbit construction" , "how to get rid of household cleaning chores", "how to build a food replicator", "ooh isn't biotech kind of fun", etc.). I think we'll eventually start building "smart matter" at some scale. Might be nanometer. Might be millimeter. Might be meter. Each of those scales has its own physics regime, but I think the concepts behind self-organization will be common. And we're already working on those ideas when studying biology at molecular and cellular level. > When I've looked this stuff up in the past I've found most of the time it was proprietary. Do you remember any names? Might be that some of the research is released. Or maybe my employer has access. > However I have seen papers doing similar work (in the sense that there is transferable logic) in a two dimensional fields, eg matrix reordering. Thanks, I'll look it up.
- TheOtherHobbes 5y ago
  I don't think that would work. Bloxels would need to know their location in the grid. And any kind of closed object would cause problems because bloxels would only adhere to the surface, not build up bulk inside. Maybe better would be a kind of 3D printing model, where the shape is 2D and changes over time, which leads to accretion of a 3D shape. Even so - without feedback and monitoring you'll get errors and holes. And you'll still have the problem that unless you're using some novel form of programmable electrostatic bonding, adhesion between bloxels will be weak. So you won't be able to do much with your finished shape except look at it. Probably not even pick it up, in fact.
  - TeMPOraL 5y ago
    > Bloxels would need to know their location in the grid. That's the thing I'm trying to work around. If bloxels are like boids in the flocking simulations, they don't care about their location - they move and change state based on the movement and state of their neighbors. In the flocking simulations, boids automatically form stable shapes and recover from disruptions, and none of them have assigned positions or even any kind of unique identifier. It's the repulsion and attraction functions - identical in every boid - that determine the steady state shape of the flock. That said, I think there's a way for bloxels to tell where they are in their "flock". Imagine each bloxel continuously publishing a "depth" value that's computed as e.g. length of the vector \Sigma_{n}^{Neighbors}: Depth(n) x DirectionTo(n). The values would initially fluctuate, but I feel it's possible to set this up so that over short time the system will settle, with every boid's "depth" value being a correct indication of how far it is from the centre of the group. So e.g. upon activation, a pile of bloxels could wait for "depth" values to stabilize, and then each bloxel would remember its value as its designated position, and execute some different algorithm with that bit of state fixed. Note to self: there's a bunch of free "agent-based simulation" programs I saw on the Internet the other day; such "depth" calculation should be a simple thing to simulate and verify. Related keyword: phase-locked loops. See also: fireflies that synchronize their flashing patterns over time. > And any kind of closed object would cause problems because bloxels would only adhere to the surface, not build up bulk inside. Why can't they build up bulk, using each other for support? > Maybe better would be a kind of 3D printing model, where the shape is 2D and changes over time, which leads to accretion of a 3D shape. I'm not sure what you mean. That sounds like regular 3D printing using "dumb" matter? > Even so - without feedback and monitoring you'll get errors and holes. Bloxels would be active and reacting to each other - this is a feedback-full system. > unless you're using some novel form of programmable electrostatic bonding, adhesion between bloxels will be weak I have no good ideas here. I don't know of any programmable bonding system that isn't too energy intensive to use with current technology. AFAIK electromagnets are power hogs. Mechanical locking systems are also energy intensive, and also tricky to use (maneuvering the mating endpoints to meet, compensating torque, etc.)

Yes, something like that - and I'm wondering if there's a way to imprint a pattern on such flock of birds, so that they then flock into appropriate shape from whatever starting configuration they were in, and maintain the shape over time, even in the face of strong winds or some of the flock members dying. Here's one idea I'm thinking about: flocking-like equations in "boids" simulations are local, a pure function of (the observed state of) the neighbors. In a typical implementation, they just compute velocity/acceleration vectors out of position/velocity/acceleration/class of the neighbors[0]. And the result are pretty, fluid, and uniform in steady-state flocks. But what if we added more observable state and equations to this? Imagine each boid having a "color", a value that is a function of not just the color of the neighbors, but also of their position/velocity/acceleration/class. And then, the equations computing velocity/acceleration take this color into account too, e.g. by offsetting the result by some function of the neighbors' colors. Could we then design the f([colors]) -> v/a offset and f([everything]) -> color functions so that they end up forcing the flock into an arbitrary uniform shape? I believe we could, but I'm not sure how to define these functions for any particular shape. (Or, in short: I'm looking for a method to turn an arbitrary picture into an error term for boids rules that makes the flock assume the shape of the picture, instead of an uniform blob.) I'm sure there must be some pre-existing theoretical work behind finding such functions - this problem feels like a cousin of the "find a formula that draws a target picture on X/Y plot". I just don't know the right keywords to look this up. But this is kind of the idea on the back of my head - encoding desired group behavior in a function that is common to every member of the group and is entirely local (only a function of the immediate observed environment), but that forces the system to settle in a desired configuration. -- [0] - "class" being e.g. member of same species, a predator, or a prey.

Wildgoose 5y ago
Yes. Imagine that the "boids" change colour as well as alter their X, Y, Z position. That supplies additional "guiding" information to provide purpose and also alter behaviour, in much the same way that hormones act on a growing foetus. And this reminds me of those audience experiments with people holding up blue and red cards and using this "vote" to successfully steer a vehicle.
- TeMPOraL 5y ago
  Yup. Also nothing says the boids have to execute a single behavior all the time. In a parallel comment, I described an idea where boids first start doing nothing except publishing a "depth" value that's a function of their neighbors "depth" value, waiting for the system to settle (as detected by neighboring values not changing by more than some fixed epsilon over some fixed Δt). They could then record their individual values and continue to a second algorithm (e.g. traditional "boids"), that uses this (now fixed) "depth" value as a parameter. This is, in general, a pattern for individual unit to discover their role in the group, without ever knowing the whole group. I just realized this sounds like things the field of "distributed consensus" deals with - I'll add that to my research list. I remember the voting games and "Twitch plays X" events. It's kind of a different situation (external controllers voting on control input to a single actor), but there might be some parallels.
hnlmorg 5y ago
It might be worth first reading up on the research being drone performances. The current model is basically what I'd already described (https://eandt.theiet.org/content/articles/2021/04/there-s-no-business-like-drone-business/ https://eandt.theiet.org/content/articles/2021/04/there-s-no...) but research is happening to use "AI" to navigate swarms (eg https://www.youtube.com/watch?v=7KIa9FlmbRc https://www.youtube.com/watch?v=7KIa9FlmbRc) The real problem with such research is it might work on a quadcopter with room for a chipset capable of relatively powerful real time compution (be that an off the shelf CPU or something more bespoke), but that doesn't scale down to the grain of sand level. At that point you'll want to offload as much computation overhead as you can. Which, again, brings me back to my original post. Maybe one day in the distant future (if we haven't annihilated each other first) we'll have the technology to built smart grains of sand. But it's seems pointless theorising about something that might just as easily be deprecated by some other fantasy device by our current technological capabilities. Anyhow, if you're after a paper on the actual calculations you'd run to convert a database of nearest neighbour coordinates into a matrix that can be used to instruct those robots, then I don't have anything directly to hand on that. When I've looked this stuff up in the past I've found most of the time it was proprietary. Maybe there is a paper I've missed. However I have seen papers doing similar work (in the sense that there is transferable logic) in a two dimensional fields, eg matrix reordering.
- TeMPOraL 5y ago
  Thanks! I haven't thought about drone performances. In retrospect, it's a good starting point. I've seen plenty of videos of drone swarms being synced up to produce shapes and animations. > Maybe one day in the distant future (if we haven't annihilated each other first) we'll have the technology to built smart grains of sand. But it's seems pointless theorising about something that might just as easily be deprecated by some other fantasy device by our current technological capabilities. Maybe. But I feel this isn't pointless - I find myself constantly returning to this topic whenever I follow seemingly unrelated avenues of idle curiosity (e.g. "how to build self-maintaining systems", "how to do in-orbit construction" , "how to get rid of household cleaning chores", "how to build a food replicator", "ooh isn't biotech kind of fun", etc.). I think we'll eventually start building "smart matter" at some scale. Might be nanometer. Might be millimeter. Might be meter. Each of those scales has its own physics regime, but I think the concepts behind self-organization will be common. And we're already working on those ideas when studying biology at molecular and cellular level. > When I've looked this stuff up in the past I've found most of the time it was proprietary. Do you remember any names? Might be that some of the research is released. Or maybe my employer has access. > However I have seen papers doing similar work (in the sense that there is transferable logic) in a two dimensional fields, eg matrix reordering. Thanks, I'll look it up.
TheOtherHobbes 5y ago
I don't think that would work. Bloxels would need to know their location in the grid. And any kind of closed object would cause problems because bloxels would only adhere to the surface, not build up bulk inside. Maybe better would be a kind of 3D printing model, where the shape is 2D and changes over time, which leads to accretion of a 3D shape. Even so - without feedback and monitoring you'll get errors and holes. And you'll still have the problem that unless you're using some novel form of programmable electrostatic bonding, adhesion between bloxels will be weak. So you won't be able to do much with your finished shape except look at it. Probably not even pick it up, in fact.
- TeMPOraL 5y ago
  > Bloxels would need to know their location in the grid. That's the thing I'm trying to work around. If bloxels are like boids in the flocking simulations, they don't care about their location - they move and change state based on the movement and state of their neighbors. In the flocking simulations, boids automatically form stable shapes and recover from disruptions, and none of them have assigned positions or even any kind of unique identifier. It's the repulsion and attraction functions - identical in every boid - that determine the steady state shape of the flock. That said, I think there's a way for bloxels to tell where they are in their "flock". Imagine each bloxel continuously publishing a "depth" value that's computed as e.g. length of the vector \Sigma_{n}^{Neighbors}: Depth(n) x DirectionTo(n). The values would initially fluctuate, but I feel it's possible to set this up so that over short time the system will settle, with every boid's "depth" value being a correct indication of how far it is from the centre of the group. So e.g. upon activation, a pile of bloxels could wait for "depth" values to stabilize, and then each bloxel would remember its value as its designated position, and execute some different algorithm with that bit of state fixed. Note to self: there's a bunch of free "agent-based simulation" programs I saw on the Internet the other day; such "depth" calculation should be a simple thing to simulate and verify. Related keyword: phase-locked loops. See also: fireflies that synchronize their flashing patterns over time. > And any kind of closed object would cause problems because bloxels would only adhere to the surface, not build up bulk inside. Why can't they build up bulk, using each other for support? > Maybe better would be a kind of 3D printing model, where the shape is 2D and changes over time, which leads to accretion of a 3D shape. I'm not sure what you mean. That sounds like regular 3D printing using "dumb" matter? > Even so - without feedback and monitoring you'll get errors and holes. Bloxels would be active and reacting to each other - this is a feedback-full system. > unless you're using some novel form of programmable electrostatic bonding, adhesion between bloxels will be weak I have no good ideas here. I don't know of any programmable bonding system that isn't too energy intensive to use with current technology. AFAIK electromagnets are power hogs. Mechanical locking systems are also energy intensive, and also tricky to use (maneuvering the mating endpoints to meet, compensating torque, etc.)