4 ms·

Some rich person should offer a $1M prize for a single useful application, or example in nature or science, of cellular automata.

by aj7 6y ago

gnulinux 6y ago
You mean like procedural generation? I used cellular automata with custom rules to generate procedural generated universes for a video game I worked on.
asimpletune 6y ago
I don’t see why people are downvoting. I’m not pessimistic, I just don’t understand for myself the real life applications, so please educate instead of downvoting. That said, procedural generation is a great example thanks. Also, whatever happened of Wolfram’s “A New Kind of Science”, or whatever it was called. He literally wrote a gigantic book on sampling the computational universe, but I’m not really aware of it being used, probably because I’m ignorant.
- gnulinux 6y ago
  I mean please don't take this answer the wrong way, but this is like saying "Some rich person should give away $1M for finding an application of complex numbers". It feels condescending. If your area deals with cellular automata e.g. programming languages, computer simulation, procedural generation etc applications of cellular automata are numerous and well understood. It's niche sure, but it's not like this entertaining thing that strangely has no practical applications. I downvoted GP because of this, since it assumes it has no applications and offers a rich person to help us out to compensate for that.
- taliesinb 6y ago
  Disclosure: I worked on Mathematica for ~8 years. I think the value of Stephen's big book is that served as a kind of manifesto to "take computation seriously". By that I mean: to think about computations, in the abstract, as a kind of new mathematics about which we know almost nothing, and about which our naive intuitions from other domains is almost totally inapplicable. It is an injunction to explore the "computational universe", in other words, the "universe of simple computational systems", where CAs live as one of several kinds of maximally simple form of computation (which Wolfram made some attempt to categorize and explore). By analogy, think about the development of algebra. It didn't come naturally! Yet Algebra is one of the most natural ideas in abstract mathematics, incredibly simple and incredibly powerful, lying as a rosetta stone connecting so many other topics in mathematics. But people didn't immediately accept or describe it; it took many hundreds of years to crystalize and mature as a topic. It's a very old piece of the operating system of mathematics that underwent a lot of hacking and refactoring. Wolfram proposes we think about computational systems in the same way, as a nascent field that needs exploration, mapping, the irrigation of young minds and new ideas. It may be some time before it yields a harvest. We shouldn't expect it to immediately revolutionize everything. Even after Turing, computational systems existed as a kind of diaspora in mathematics, having sat unrecognized in all kinds of places, never having had a sort of independent state in which they are not considered as an aspect of something else, as somehow alien and unworthy of respect because of their confusing aspects. Largely, there were two reasons they were treated so shoddily: 1. they required computers (and good computer tools) to actually explore, since they produced complex and irreducible computations 2. they resisted any kind of analysis by prior mathematics In other words, we were not ready to really probe them until a few decades ago, and even now our software is not well suited to explore them (Mathematica remains the best tool for the job, though I anticipate Julia will surpass it rapidly). Furthermore, traditional mathematical fields have not adapted to the presence of computation very gracefully. I guess I would summarize: NKS is an imperfect book and Stephen an imperfect herald of the ideas within. But he was the first person to really articulate those ideas crisply and push them hard into the imagination, and I'm very glad he did. The hand he overplayed was the application to the natural world -- I think that will take longer to pay off than he predicted.
  - perardi 6y ago
    * The hand he overplayed was the application to the natural world—I think that will take longer to pay off than he predicted. * Not that I actually understand it, for I am a UI designer, but Wolfram’s recent physics projects seems to be taking a fresh run at that. https://www.wolframphysics.org/bulletins/2020/08/a-short-note-on-the-double-slit-experiment-and-other-quantum-interference-effects-in-the-wolfram-model/ https://www.wolframphysics.org/bulletins/2020/08/a-short-not... disclosure: worked for Wolfram for 7 years, forgive me promoting stuff I worked on
mensetmanusman 6y ago
Agree, like a Clay mathematics prize. The current answer is amazing screen saver, but part of me thinks the answer is in microbots that are super simple to build and have limited instructions, but could be placed in a configuration to do something useful (like build more?)
- algoholix 6y ago
  You should really take a look at the paper "Computation and Pattern Formation by Swarm Networks with Brownian Motion" or, more generally, any of the papers by Teijiro Isokawa and Ferdinand Peper. What they present is really close to (a theoretical version of) the microbots you're talking about. I even wrote a report and presentation on those papers for university, but sadly they're in German.
joycian 6y ago
https://en.m.wikipedia.org/wiki/Lattice_gas_automaton https://en.m.wikipedia.org/wiki/Lattice_gas_automaton
- aj7 6y ago
  I appreciate this response. However the “cellular” is represented by the minimal computational data structure to simulate the gas. There is no automata. Ordinary physics, adhered to as closely as possible, and not phantasmagoric creation and annihilation rules, are used to calculate the next state.
  - varjag 6y ago
    The automation is cellular, discrete (binary) and is driven by a set of activation rules. If that's your ordinary physics we had very different physics books.
Aerroon 6y ago
Aren't cellular automata used in video games? One of the simplest ways of doing fluid simulation in 2D works on similar principles. Eg http://www.jgallant.com/2d-liquid-simulator-with-cellular-automaton-in-unity/ http://www.jgallant.com/2d-liquid-simulator-with-cellular-au... A lot of simulations will likely be done in a manner that's similar to CAs. Pixel shaders run once per pixel, which make this type of abstraction quite attractive. You can take advantage of the massive parallelism of GPUs.
wcoenen 6y ago
> example in nature or science, of cellular automata Skin scales of ocellated lizards: https://www.nature.com/articles/nature22031 https://www.nature.com/articles/nature22031 edit: more accessible article about the above paper, with pictures: https://physicstoday.scitation.org/do/10.1063/PT.5.7369/full/ https://physicstoday.scitation.org/do/10.1063/PT.5.7369/full... My intuition is that a lot of embryology is also related to CA: cells have to build larger structures by using only local rules and state.
- jamiek88 6y ago
  The embryology of the brain is an obvious candidate. Very small instruction set to build it, the neuron pattern repeated, local rules and state.

Some rich person should offer a $1M prize for a single useful application, or example in nature or science, of cellular automata.

by aj7 6y ago

Some rich person should offer a $1M prize for a single useful application, or example in nature or science, of cellular automata.

gnulinux 6y ago

You mean like procedural generation? I used cellular automata with custom rules to generate procedural generated universes for a video game I worked on.

asimpletune 6y ago

I don’t see why people are downvoting. I’m not pessimistic, I just don’t understand for myself the real life applications, so please educate instead of downvoting. That said, procedural generation is a great example thanks. Also, whatever happened of Wolfram’s “A New Kind of Science”, or whatever it was called. He literally wrote a gigantic book on sampling the computational universe, but I’m not really aware of it being used, probably because I’m ignorant.

gnulinux 6y ago
I mean please don't take this answer the wrong way, but this is like saying "Some rich person should give away $1M for finding an application of complex numbers". It feels condescending. If your area deals with cellular automata e.g. programming languages, computer simulation, procedural generation etc applications of cellular automata are numerous and well understood. It's niche sure, but it's not like this entertaining thing that strangely has no practical applications. I downvoted GP because of this, since it assumes it has no applications and offers a rich person to help us out to compensate for that.
taliesinb 6y ago
Disclosure: I worked on Mathematica for ~8 years. I think the value of Stephen's big book is that served as a kind of manifesto to "take computation seriously". By that I mean: to think about computations, in the abstract, as a kind of new mathematics about which we know almost nothing, and about which our naive intuitions from other domains is almost totally inapplicable. It is an injunction to explore the "computational universe", in other words, the "universe of simple computational systems", where CAs live as one of several kinds of maximally simple form of computation (which Wolfram made some attempt to categorize and explore). By analogy, think about the development of algebra. It didn't come naturally! Yet Algebra is one of the most natural ideas in abstract mathematics, incredibly simple and incredibly powerful, lying as a rosetta stone connecting so many other topics in mathematics. But people didn't immediately accept or describe it; it took many hundreds of years to crystalize and mature as a topic. It's a very old piece of the operating system of mathematics that underwent a lot of hacking and refactoring. Wolfram proposes we think about computational systems in the same way, as a nascent field that needs exploration, mapping, the irrigation of young minds and new ideas. It may be some time before it yields a harvest. We shouldn't expect it to immediately revolutionize everything. Even after Turing, computational systems existed as a kind of diaspora in mathematics, having sat unrecognized in all kinds of places, never having had a sort of independent state in which they are not considered as an aspect of something else, as somehow alien and unworthy of respect because of their confusing aspects. Largely, there were two reasons they were treated so shoddily: 1. they required computers (and good computer tools) to actually explore, since they produced complex and irreducible computations 2. they resisted any kind of analysis by prior mathematics In other words, we were not ready to really probe them until a few decades ago, and even now our software is not well suited to explore them (Mathematica remains the best tool for the job, though I anticipate Julia will surpass it rapidly). Furthermore, traditional mathematical fields have not adapted to the presence of computation very gracefully. I guess I would summarize: NKS is an imperfect book and Stephen an imperfect herald of the ideas within. But he was the first person to really articulate those ideas crisply and push them hard into the imagination, and I'm very glad he did. The hand he overplayed was the application to the natural world -- I think that will take longer to pay off than he predicted.
- perardi 6y ago
  * The hand he overplayed was the application to the natural world—I think that will take longer to pay off than he predicted. * Not that I actually understand it, for I am a UI designer, but Wolfram’s recent physics projects seems to be taking a fresh run at that. https://www.wolframphysics.org/bulletins/2020/08/a-short-note-on-the-double-slit-experiment-and-other-quantum-interference-effects-in-the-wolfram-model/ https://www.wolframphysics.org/bulletins/2020/08/a-short-not... disclosure: worked for Wolfram for 7 years, forgive me promoting stuff I worked on

mensetmanusman 6y ago

Agree, like a Clay mathematics prize. The current answer is amazing screen saver, but part of me thinks the answer is in microbots that are super simple to build and have limited instructions, but could be placed in a configuration to do something useful (like build more?)

algoholix 6y ago
You should really take a look at the paper "Computation and Pattern Formation by Swarm Networks with Brownian Motion" or, more generally, any of the papers by Teijiro Isokawa and Ferdinand Peper. What they present is really close to (a theoretical version of) the microbots you're talking about. I even wrote a report and presentation on those papers for university, but sadly they're in German.

joycian 6y ago

https://en.m.wikipedia.org/wiki/Lattice_gas_automaton https://en.m.wikipedia.org/wiki/Lattice_gas_automaton

aj7 6y ago
I appreciate this response. However the “cellular” is represented by the minimal computational data structure to simulate the gas. There is no automata. Ordinary physics, adhered to as closely as possible, and not phantasmagoric creation and annihilation rules, are used to calculate the next state.
- varjag 6y ago
  The automation is cellular, discrete (binary) and is driven by a set of activation rules. If that's your ordinary physics we had very different physics books.

Aerroon 6y ago

Aren't cellular automata used in video games? One of the simplest ways of doing fluid simulation in 2D works on similar principles. Eg http://www.jgallant.com/2d-liquid-simulator-with-cellular-automaton-in-unity/ http://www.jgallant.com/2d-liquid-simulator-with-cellular-au... A lot of simulations will likely be done in a manner that's similar to CAs. Pixel shaders run once per pixel, which make this type of abstraction quite attractive. You can take advantage of the massive parallelism of GPUs.

wcoenen 6y ago

> example in nature or science, of cellular automata Skin scales of ocellated lizards: https://www.nature.com/articles/nature22031 https://www.nature.com/articles/nature22031 edit: more accessible article about the above paper, with pictures: https://physicstoday.scitation.org/do/10.1063/PT.5.7369/full/ https://physicstoday.scitation.org/do/10.1063/PT.5.7369/full... My intuition is that a lot of embryology is also related to CA: cells have to build larger structures by using only local rules and state.

jamiek88 6y ago
The embryology of the brain is an obvious candidate. Very small instruction set to build it, the neuron pattern repeated, local rules and state.