Answers.Body: <p>Due to the hexagonal arrangement, each cell in a hexagonal automaton has six neighboring cells, which can provide more complex interactions. This increased connectivity and symmetry can lead to more diverse and intricate patterns. Hexagonal cellular automata are also known to be more efficient in simulating certain natural phenomena, such as fluid flow and crystal growth.</p>
  
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Body: <p>A cellular automaton is a state machine that is controlled by external input. The input is given by geometrical space around a cell. In a square matrix, each automaton gets input from 4 surrounding cells, while a hexagon grid has 6 neighbor cells that can be used as automaton input. For example, a 4-cells input may be the string “1011”. This string specifies a state of the cellular automaton. The automaton will switch to a different state according to the lookup table. I want to know if increasing the number of input cells in a hexagon automaton will make the resulting computer more powerful.</p>
  <p><em>original message</em></p>
  <p>I'd like to learn more about the differences between <a href="https://en.wikipedia.org/wiki/Cellular_automaton#Related_automata" rel="nofollow noreferrer">related automata</a> which can be based on hexagonal cells instead of squares (rule 34/2), like in <a href="https://en.wikipedia.org/wiki/CoDi" rel="nofollow noreferrer">CoDi model</a> which uses spiking neural network (SNN).</p>
  <p>Is using a plane tiled with regular <a href="https://en.wikipedia.org/wiki/Hexagonal_tiling" rel="nofollow noreferrer">hexagons</a> more efficient and reliable than using square cells? What is the difference and how do I know which one to use in which scenario?</p>
  <hr />
  <p>In other words, the more efficiently flexible that it grows, the more difficult scenarios it can be used for (for me, hexagonal implicates more possibilities, because it can send/share the signal with/to more tiles). Or maybe one is more modern than the other, or they're both on the same level? In general, I'd like to learn the differences between them to know when I should use one over the other.</p>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-04-16T16:59:54.473Z
Comments.Text: @GuidoJorg I believe that should be an answer.
Comments.UserDisplayName: FreezePhoenix
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Comments.CreationDate: 2018-08-24T18:52:02.253Z
Comments.Text: Clearly it raises complexity, but, from some conversations with some skilled Go-variant designers, hexagons bring their own set of design problems.  (imo, this makes them especially worth pursuing.)
Comments.UserDisplayName: DukeZhou
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2016-08-05T23:11:18.030Z
Comments.Text: This seems more suited to Data Science, though I could be convinced otherwise. [It's being discussed on meta.](http://meta.ai.stackexchange.com/q/1097/75)
Comments.UserDisplayName: Ben N
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Comments.CreationDate: 2016-08-06T01:30:42.813Z
Comments.Text: No, I think this question would be closed on Data Science. It might be on topic in CSTheory, and I think it could be on topic here if we wanted it to be. I would be surprised if you could find anyone who could answer this question in more detail than "there are more sides". I think this is the kind of thing that has long since been abandoned in research.
  
  Cellular Automata are to the best of my knowledge not used anywhere for a practical application, so measuring their efficiency is not a well defined idea.
Comments.UserDisplayName: Harsh
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2016-08-07T19:34:15.200Z
Comments.Text: Interesting question! One thing that is known is that for example for games programming for Ai versus humans, hexagonal is preferred, because the Ai performs in a more interesting way. Does that mean it performs more efficiently? Well, it's also more susceptible to noise, or human bluffing of it...
Comments.UserDisplayName: Gottfried William
Tags: <evolutionary-algorithms><topology><efficiency>
Title: Number of input variables for a cellular automaton (was: Squares or hexagonal?)
UserDisplayName: kenorb
ThreadText: # Number of input variables for a cellular automaton (was: Squares or hexagonal?)
  
  (Asked by: username_0 on 2016-08-02)
  
  A cellular automaton is a state machine that is controlled by external input. The input is given by geometrical space around a cell. In a square matrix, each automaton gets input from 4 surrounding cells, while a hexagon grid has 6 neighbor cells that can be used as automaton input. For example, a 4-cells input may be the string “1011”. This string specifies a state of the cellular automaton. The automaton will switch to a different state according to the lookup table. I want to know if increasing the number of input cells in a hexagon automaton will make the resulting computer more powerful.
  
  *original message*
  
  I'd like to learn more about the differences between [related automata](https://en.wikipedia.org/wiki/Cellular_automaton#Related_automata) which can be based on hexagonal cells instead of squares (rule 34/2), like in [CoDi model](https://en.wikipedia.org/wiki/CoDi) which uses spiking neural network (SNN).
  
  Is using a plane tiled with regular [hexagons](https://en.wikipedia.org/wiki/Hexagonal_tiling) more efficient and reliable than using square cells? What is the difference and how do I know which one to use in which scenario?
  
  ---
  
  In other words, the more efficiently flexible that it grows, the more difficult scenarios it can be used for (for me, hexagonal implicates more possibilities, because it can send/share the signal with/to more tiles). Or maybe one is more modern than the other, or they're both on the same level? In general, I'd like to learn the differences between them to know when I should use one over the other.
  
  **Tags:** evolutionary-algorithms, topology, efficiency
  > **Comments:**
  > **username_3**: This seems more suited to Data Science, though I could be convinced otherwise. [It's being discussed on meta.](http://meta.ai.stackexchange.com/q/1097/75)  
  > **username_4**: No, I think this question would be closed on Data Science. It might be on topic in CSTheory, and I think it could be on topic here if we wanted it to be. I would be surprised if you could find anyone who could answer this question in more detail than "there are more sides". I think this is the kind of thing that has long since been abandoned in research.  Cellular Automata are to the best of my knowledge not used anywhere for a practical application, so measuring their efficiency is not a well defined idea.  
  > **username_5**: Interesting question! One thing that is known is that for example for games programming for Ai versus humans, hexagonal is preferred, because the Ai performs in a more interesting way. Does that mean it performs more efficiently? Well, it's also more susceptible to noise, or human bluffing of it...  
  > **username_1**: @GuidoJorg I believe that should be an answer.  
  > **username_2**: Clearly it raises complexity, but, from some conversations with some skilled Go-variant designers, hexagons bring their own set of design problems.  (imo, this makes them especially worth pursuing.)  
  
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  ## 1 answers
  
  ### Answer by username_6 on 2023-12-13. Score: -1
  
  Due to the hexagonal arrangement, each cell in a hexagonal automaton has six neighboring cells, which can provide more complex interactions. This increased connectivity and symmetry can lead to more diverse and intricate patterns. Hexagonal cellular automata are also known to be more efficient in simulating certain natural phenomena, such as fluid flow and crystal growth.
  
  
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