Cellular automaton

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A cellular automaton is a certain class of mathematical objects (or, more specifically, a mathematical structure) of which Conway's Game of Life is an example.

Informally, a cellular automaton consists of:

  • A space of cells.
  • A set of allowed states for each cell. An assignment of an state to every cell is called a “configuration” or “pattern” (the first term is more common in mathematical discussion and the later in informal discussions).
  • A neighbourhood which defines which cells are considered to pass information to a given cell.
  • A transition rule which specifies how given a cell and the states of its neighbours, a new state is produced.

The state of the cellular automaton evolves in discrete time, with the state of each cell at time t+1 being determined by the state of its neighbourhood at time t in accordance with the transition rule.

There are some variations on the above definition. It is common to require that there be a quiescent state (i.e., a state such that if the whole universe is in that state at generation 0 then it will remain so in generation 1). In Conway's Game of Life, the "OFF" state is quiescent, but the "ON" state is not. Other variations allow spaces other than In, neighbourhoods that vary over space and/or time, probabilistic or other non-deterministic transition rules, and so on.

It is common for the neighbourhood of a cell to be the 3×...×3 hypercube centered on that cell, which is known as its Moore neighbourhood.

For a collection of cellular automata packaged for Golly, see [1].

Formal definition

Let us denote the set of integers by I and the length of any tuple x by |x|. For any tuples of integers x and y such that |x|=|y| we denote their element-wise addition by x+y.

A cellular automaton is a tuple (In,S,N,f) such that the dimension n is at least 1, the set of states S is finite, the neighbourhood N is a tuple of elements of In and f:S|N|S is the transition function.

A configuration of the cellular automaton (In,S,N,f) is any function InS.

The global transition function F of the cellular automaton (In,S,N,f) is a function F:InIn such that for any configuration c and element aIn we have F(c)(a)=f(a+N).

Let c and c' be configurations, then we say that c' is a translation of c if there exist an aIn such that for any xIn it holds that c'(a+x)=c(x). We say that the translation is proper if the condition holds for some n-tuple whose elements are not all 0.

Let c be a configuration. When the cellular automata is clear from the context, then by cn where n is a non-negative integer we denote the configuration Fn(c) where F is the corresponding global transition function.

For any configuration c, if there exists a n≥1 such that cn = c we call c an oscillator. If c is an oscillator and n is the least positive integer such that cn = c then we call n the period of c. If c is an oscillator with period 1 then we call c a still life. If c is an oscillator and is not a still life we call c a proper oscillator.

A glider is a configuration c such that cn is a proper translation of c for some n>0.

Self-replication in cellular automata

Informally, a configuration that creates a copy of itself after some number of generations is called a replicator.

John von Neumann investigated the possibility of building a self-replicating machine. He originally considered a mechanical approach, but decided that this was too hard to control. With the help of Stanislaw Ulam, he designed a new mathematical abstraction, the cellular automaton, in order to create a replicator. His CA was made in the late 1940s and is complex. It operates on the Von Neumann neighbourhood (a cell and its four orthogonally connected neighbours), and has 29 states. It is described in von Neumann, Burks (1966).

Subsequent to the von Neumann's cellular automaton new cellular automata have been produced capable of self-replication and universal computation with fewer states and using the same (von Neumann) neighborhood. Results include Codd (1968) with 8 states, Banks (1971) with 4 states and Serizawa (1987) with 3 states. As of 2017, Serizawa's CA appears to be the simplest (in terms of neighborhood size×number of states) cellular automaton known to have a non-trivial replicator.

Langton (1984) constructed a cellular automaton and a replicator. His cellular automaton is a simplification of Codd's. However, Langton's CA was not intended to support universal computation. The simplicity of the configuration is possible because of a novel method of self-replication. The replicator consists of a loop with circulating cell states that encode instructions to construct a new arm, then turn 90° and repeat until a new loop is formed. The new loop is then filled with the same circulating information and the connection between it and the loop that generated it is severed. The parent loop continues to build copies until no more space is available, then it becomes a still life.

Nehaniv (2002) presented a method that allows the transformation of conventional (synchronous) cellular automata to an equivalent asynchronous cellular automata (a case not covered by our definition above). In the same paper, a self-reproducing configuration is presented which is based on the described procedure applied to Langton's CA.

Conway's Game of Life is known to be universal, with 2 states and the Moore neighbourhood. Conway did not design Life for this purpose, unlike von Neumann's, Codd's, Banks' and Serizawa's rules, so it is purely coincidental that Life supports replicators. The Spartan universal computer-constructor could replicate, given a sufficient program tape.

Life-like cellular automata

A cellular automaton is said to be Life-like if it meets the following four criteria:

  • It has two dimensions (i.e., n = 2).
  • It has two states, usually called OFF and ON (i.e., |S| = 2).
  • The neighbourhood used is the Moore neighbourhood; it consists of the eight (orthogonally and diagonally) adjacent cells to the one under consideration and (possibly) the cell itself.
  • The new state of a cell in the next generation can be expressed as a function of the number of cells in its neighbourhood that are in the ON state and the cell's own state; that is, the rule is outer totalistic (or semitotalistic).

This class of cellular automata is named for Conway's Game of Life, the most famous cellular automaton, which Life-like cellular automata mimic. Many different terms are used to describe this class of cellular automata; it is also common to refer to it as the "Life family" or to simply use phrases like "similar to Life".


A common notation used to describe these automata is referred to as "S/B", which is known as its rule (or rulestring). S (for survival) is a list of all the numbers of ON cells that cause an ON cell to remain ON. B (for birth) is a list of all the numbers of ON cells that cause an OFF cell to turn on. If 0 is in the list, then blank regions of the universe will turn on in one generation. S/B is often referred to as the rule or rulestring of the given cellular automata.

As an example, the seeds rulestring is /2. All OFF cells that have exactly two adjacent ON cells will turn on in the next generation, while every ON cell dies in every generation, since the survival list is empty. The rulestring of Conway's Game of Life is 23/3.

Other notations are sometimes used to describe the rules of the given Life-like cellular automaton. The most common other format is "B{number list}/S{number list}", where the number lists are the numbers of neighbours that cause a dead cell to be born and cause an alive cell to stay alive, respectively. In this format, Conway's Game of Life would have the rulestring B3/S23.

There are 262144 (= 218) distinct Life-like rules. Each rule has a complementary rule which behaves identically under on-off reversal; namely the rule in which birth occurs on all N except those for which 8-N is a survival condition in the original rule, and survival occurs on all N except those for which 8-N is a birth condition in the original rule. For example, the rule complementary to Conway's Life is 01234678/0123478. This however does not quite halve the number of effectively distinct rules, as there are 512 (= 29) rules which are unaffected by on-off reversal.

Some straightforward inferences on the behavior of different kinds of rules can be made:

  • In all rules where the lowest birth condition is 1 neighboring ON cell, all finite patterns grow at the speed of light in all directions. No still lifes, oscillators or spaceships are possible in these rules. Several have replicators, however. There are 65536 (= 216) rules of the B1 type.
  • All rules where the lowest birth condition is 2 neighboring ON cells are exploding or expanding in character; this is largely due to the fact that a domino at the corner of a pattern will give rise to a new domino, also located at the corner of the daughter pattern. Spaceships (such as the moon) and oscillators (such as the duoplet) do exist in many of these rules. There are 32768 (= 215) rules of the B2 type.
  • All rules where the lowest birth condition (if any) is 4 or more neighboring ON cells are stable in character, since no patterns ever grow beyond their initial bounding box. In particular, no spaceships can exist. There are 16384 (= 214) rules of the B4+ type.
  • In all rules where the lowest birth condition is 0 neighboring ON cells, and the highest survival condition is 8 neighboring ON cells, the vacuum is unstable and will be immediately filled (and remain filled) with ON cells; thus, there are no patterns that remain finite. All of these rules have distinct complementary rules, and they are not commonly studied on their own.
  • This leaves 16384 rules in which the lowest birth condition is 3 neighboring ON cells, as well as 65536 rules in which the lowest birth condition is 0 neighboring cells, and 8 neighbors is not a survival condition. All chaotic rules must fall in either of these two areas of the rulespace. Most well-studied examples fall in the first one, since for long no commonly available software existed that could simulate the evolution of rules containing B0.

Non-totalistic rules

Main article: Non-totalistic Life-like cellular automaton

Various generalizations of Life-like cellular automata are possible. In non-totalistic rules, the transition function considers not just the number of cells in a given cell's neighborhood but also their alignment; for example, a cell might be born if bordered by three live cells in a row, but not by three live cells in other configurations. Non-totalistic rules are described using Hensel notation, an extension of B/S notation additionally describing allowed or forbidden configurations.

Well-known Life-like cellular automata

Main article: List of Life-like cellular automata

The following table lists life-like cellular automata that are particularly well-known or well-studied.

Rulestring Name Description
B1357/S1357 Replicator A rule in which every pattern is a replicator.
B1357/S02468 Fredkin A rule in which, like Replicator, every pattern is a replicator.
B2/S Seeds An exploding rule in which every cell dies in every generation. It has many simple orthogonal spaceships, though it is in general difficult to create patterns that don't explode.
B2/S0 Live Free or Die An exploding rule in which only cells with no neighbors survive. It has many spaceships, puffers, and oscillators, some of infinitely extensible size and period.
B3/S012345678 Life without death An expanding rule that produces complex flakes. It also has important ladder patterns.
B3/S12 Flock A rule which decays into small still lifes and oscillators
B3/S1234 Mazectric An expanding rule that crystalizes to form maze-like designs that tend to be straighter (ie. have longer "halls") than the standard maze rule.
B3/S12345 Maze An expanding rule that crystalizes to form maze-like designs.
B3/S23 Conway's Life A chaotic rule that is by far the most well-known and well-studied. It exhibits highly complex behavior.
B36/S125 2x2 A chaotic rule with many simple still lifes, oscillators and spaceships. Its name comes from the fact that it sends patterns made up of 2x2 blocks to patterns made up of 2x2 blocks.
B36/S23 HighLife A chaotic rule very similar to Conway's Life that is of interest because it has a simple replicator.
B368/S245 Move A rule in which random patterns tend to stabilize extremely quickly. Has a very common slow-moving spaceship and slow-moving puffer.
B3678/34678 Day & Night A stable rule that is symmetric under on-off reversal. Many patterns exhibiting highly complex behavior have been found for it.


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