"What a piece of work is a man!" is a phrase within a monologue by Prince Hamlet in William Shakespeare's play Hamlet. Hamlet is reflecting, at first admiringly, and then despairingly, on the human condition.
The speech is recited at the end of the film Withnail and I and the text was set to music by Galt MacDermot for the rock opera Hair.
The speech
The monologue, spoken in the play by Prince Hamlet to Rosencrantz and Guildenstern in Act II, Scene 2, follows in its entirety. Rather than appearing in blank verse, the typical mode of composition of Shakespeare's plays, the speech appears in straight prose:
I will tell you why; so shall my
anticipation prevent your discovery, and your secrecy to the King and
queene: moult no feather. I have of late, (but wherefore I know not)
lost all my mirth, forgone all custom of exercises; and indeed, it goes
so heavily with my disposition; that this goodly frame the earth, seems
to me a sterile promontory; this most excellent canopy the air, look
you, this brave o'er hanging firmament, this majestical roof, fretted
with golden fire: why, it appeareth no other thing to me, than a foul
and pestilent congregation of vapours. What a piece of work is a man,
How noble in reason, how infinite in faculty, In form and moving how
express and admirable, In action how like an Angel, In apprehension how
like a god, The beauty of the world, The paragon of animals. And yet to
me, what is this quintessence of dust? Man delights not me; no, nor
Woman neither; though by your smiling you seem to say so.
Yes faith, this great world you see contents me not, No nor the spangled heauens, nor earth, nor sea, No nor Man that is so glorious a creature, Contents not me, no nor woman too, though you laugh.
This version has been argued to have been a bad quarto, a tourbook copy, or an initial draft. By the 1604 Second Quarto, the speech is essentially present but punctuated differently:
What piece of work is a man, how noble in reason, how infinite in faculties, in form and moving, how express and admirable in action, how like an angel in apprehension, how like a god!
What a piece of worke is a man! how Noble in Reason? how infinite in faculty? in forme and mouing how expresse and admirable? in Action, how like an Angel? in apprehension, how like a God? ...
J. Dover Wilson, in his notes in the New Shakespeare
edition, observed that the Folio text "involves two grave
difficulties", namely that according to Elizabethan thought angels could
apprehend but not act, making "in action how like an angel"
nonsensical, and that "express" (which as an adjective means "direct and
purposive") makes sense applied to "action", but goes very awkwardly
with "form and moving".
These difficulties are remedied if we read it thus:
What a piece of worke is a man! how Noble in Reason? how infinite in faculty, in forme, and mouing how expresse and admirable in Action, how like an Angel in apprehension, how like a God?
Sources
A
source well known to Shakespeare is Psalm 8, especially verse 5: "You
have made [humans] a little lower than the heavenly beings and crowned
them with glory and honor."
Scholars have pointed out this section's similarities to lines written by Montaigne:
Qui luy a persuadé que ce branle
admirable de la voute celeste, la lumiere eternelle de ces flambeaux
roulans si fierement sur sa teste, les mouvemens espouventables de ceste
mer infinie, soyent establis et se continuent tant de siecles, pour sa
commodité et pour son service ? Est-il possible de rien imaginer si
ridicule, que ceste miserable et chetive creature, qui n’est pas
seulement maistresse de soy, exposée aux offences de toutes choses, se
die maistresse et emperiere de l’univers?
Who have persuaded [man] that this
admirable moving of heavens vaults, that the eternal light of these
lampes so fiercely rowling over his head, that the horror-moving and
continuall motion of this infinite vaste ocean were established, and
continue so many ages for his commoditie and service? Is it possible to
imagine so ridiculous as this miserable and wretched creature, which is
not so much as master of himselfe, exposed and subject to offences of
all things, and yet dareth call himself Master and Emperor.
However, rather than being a direct influence on Shakespeare,
Montaigne may have merely been reacting to the same general atmosphere
of the time, making the source of these lines one of context rather than
direct influence.
The Game of Life, also known as Conway's Game of Life or simply Life, is a cellular automaton devised by the British mathematicianJohn Horton Conway in 1970. It is a zero-player game,meaning that its evolution is determined by its initial state,
requiring no further input. One interacts with the Game of Life by
creating an initial configuration and observing how it evolves. It is Turing complete and can simulate a universal constructor or any other Turing machine.
Rules
The universe of the Game of Life is an infinite, two-dimensional orthogonal grid of squarecells, each of which is in one of two possible states, live or dead (or populated and unpopulated, respectively). Every cell interacts with its eight neighbours,
which are the cells that are horizontally, vertically, or diagonally
adjacent. At each step in time, the following transitions occur:
Any live cell with fewer than two live neighbours dies, as if by underpopulation.
Any live cell with two or three live neighbours lives on to the next generation.
Any live cell with more than three live neighbours dies, as if by overpopulation.
Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction.
The initial pattern constitutes the seed of the system. The
first generation is created by applying the above rules simultaneously
to every cell in the seed, live or dead; births and deaths occur
simultaneously, and the discrete moment at which this happens is
sometimes called a tick. Each generation is a pure function of the preceding one. The rules continue to be applied repeatedly to create further generations.
Origins
Stanisław Ulam, while working at the Los Alamos National Laboratory in the 1940s, studied the growth of crystals, using a simple lattice network as his model. At the same time, John von Neumann, Ulam's colleague at Los Alamos, was working on the problem of self-replicating systems.
Von Neumann's initial design was founded upon the notion of one robot
building another robot. This design is known as the kinematic model. As he developed this design, von Neumann came to realize the great
difficulty of building a self-replicating robot, and of the great cost
in providing the robot with a "sea of parts" from which to build its
replicant. Von Neumann wrote a paper entitled "The general and logical
theory of automata" for the Hixon Symposium in 1948. Ulam was the one who suggested using a discrete system for creating a reductionist model of self-replication.
Ulam and von Neumann created a method for calculating liquid motion in
the late 1950s. The driving concept of the method was to consider a
liquid as a group of discrete units and calculate the motion of each
based on its neighbours' behaviours. Thus was born the first system of cellular automata. Like Ulam's lattice network, von Neumann's cellular automata are two-dimensional, with his self-replicator implemented algorithmically. The result was a universal copier and constructor
working within a cellular automaton with a small neighbourhood (only
those cells that touch are neighbours; for von Neumann's cellular
automata, only orthogonal cells), and with 29 states per cell. Von Neumann gave an existence proof
that a particular pattern would make endless copies of itself within
the given cellular universe by designing a 200,000 cell configuration
that could do so. This design is known as the tessellation model, and is called a von Neumann universal constructor.
Motivated by questions in mathematical logic and in part by work on simulation games by Ulam, among others, John Conway
began doing experiments in 1968 with a variety of different
two-dimensional cellular automaton rules. Conway's initial goal was to
define an interesting and unpredictable cellular automaton. According to Martin Gardner,
Conway experimented with different rules, aiming for rules that would
allow for patterns to "apparently" grow without limit, while keeping it
difficult to prove that any given pattern would do so. Moreover,
some "simple initial patterns" should "grow and change for a
considerable period of time" before settling into a static configuration
or a repeating loop. Conway later wrote that the basic motivation for Life was to create a "universal" cellular automaton.
The game made its first public appearance in the October 1970 issue of Scientific American, in Martin Gardner's "Mathematical Games" column, which was based on personal conversations with Conway. Theoretically, the Game of Life has the power of a universal Turing machine: anything that can be computed algorithmically can be computed within the Game of Life. Gardner wrote, "Because of Life's analogies with the rise, fall, and
alterations of a society of living organisms, it belongs to a growing
class of what are called 'simulation games' (games that resemble
real-life processes)."
Since its publication, the Game of Life has attracted much
interest because of the surprising ways in which the patterns can
evolve. It provides an example of emergence and self-organization. A version of Life that incorporates random fluctuations has been used in physics to study phase transitions and nonequilibrium dynamics. The game can also serve as a didactic analogy,
used to convey the somewhat counter-intuitive notion that design and
organization can spontaneously emerge in the absence of a designer. For
example, philosopher Daniel Dennett
has used the analogy of the Game of Life "universe" extensively to
illustrate the possible evolution of complex philosophical constructs,
such as consciousness and free will, from the relatively simple set of deterministic physical laws which might govern our universe.
The popularity of the Game of Life was helped by its coming into
being at the same time as increasingly inexpensive computer access. The
game could be run for hours on these machines, which would otherwise
have remained unused at night. In this respect, it foreshadowed the
later popularity of computer-generated fractals. For many, the Game of Life was simply a programming challenge: a fun way to use otherwise wasted CPU
cycles. For some, however, the Game of Life had more philosophical
connotations. It developed a cult following through the 1970s and
beyond; current developments have gone so far as to create theoretic
emulations of computer systems within the confines of a Game of Life
board.
Examples of patterns
Many
different types of patterns occur in the Game of Life, which are
classified according to their behaviour. Common pattern types include: still lifes, which do not change from one generation to the next; oscillators, which return to their initial state after a finite number of generations; and spaceships, which translate themselves across the grid.
The earliest interesting patterns in the Game of Life were
discovered without the use of computers. The simplest still lifes and
oscillators were discovered while tracking the fates of various small
starting configurations using graph paper, blackboards, and physical game boards, such as those used in Go. During this early research, Conway discovered that the R-pentomino
failed to stabilize in a small number of generations. In fact, it takes
1103 generations to stabilize, by which time it has a population of 116
and has generated six escaping gliders; these were the first spaceships ever discovered.
Frequently occurring examples (in that they emerge frequently from a random starting
configuration of cells) of the three aforementioned pattern types are
shown below, with live cells shown in black and dead cells in white. Period refers to the number of ticks a pattern must iterate through before returning to its initial configuration.
Still lifes
Block
Bee- hive
Loaf
Boat
Tub
Oscillators
Blinker (period 2)
Toad (period 2)
Beacon (period 2)
Pulsar (period 3)
Penta- decathlon (period 15)
Spaceships
Glider
Light- weight spaceship (LWSS)
Middle- weight spaceship (MWSS)
Heavy- weight spaceship (HWSS)
The pulsar is the most common period-3 oscillator. The great majority of naturally
occurring oscillators have a period of 2, like the blinker and the
toad, but oscillators of all periods are known to exist, and oscillators of periods 4, 8, 14, 15, 30, and a few others have been seen to arise from random initial conditions. Patterns which evolve for long periods before stabilizing are called Methuselahs, the first-discovered of which was the R-pentomino. Diehard
is a pattern that disappears after 130 generations. Starting patterns
of eight or more cells can be made to die after an arbitrarily long
time. Acorn takes 5,206 generations to generate 633 cells, including 13 escaped gliders.
The R-pentomino
Diehard
Acorn
Conway originally conjectured that no pattern can grow
indefinitely—i.e. that for any initial configuration with a finite
number of living cells, the population cannot grow beyond some finite
upper limit. In the game's original appearance in "Mathematical Games",
Conway offered a prize of fifty dollars (equivalent to $400 in 2024) to
the first person who could prove or disprove the conjecture before the
end of 1970. The prize was won in November by a team from the Massachusetts Institute of Technology, led by Bill Gosper;
the "Gosper glider gun" produces its first glider on the 15th
generation, and another glider every 30th generation from then on. For
many years, this glider gun was the smallest one known. In 2015, a gun called the "Simkin glider gun", which releases a glider
every 120th generation, was discovered that has fewer live cells but
which is spread out across a larger bounding box at its extremities.
Gosper glider gun
Simkin glider gun
Smaller patterns were later found that also exhibit infinite growth.
All three of the patterns shown below grow indefinitely. The first two
create a single block-laying switch engine: a configuration that leaves behind two-by-two still life blocks as it translates itself across the game's universe. The third configuration creates two such patterns. The first has only ten live cells, which has been proven to be minimal. The second fits in a five-by-five square, and the third is only one cell high.
Later discoveries included other guns, which are stationary, and which produce gliders or other spaceships; puffer trains, which move along leaving behind a trail of debris; and rakes, which move and emit spaceships. Gosper also constructed the first pattern with an asymptotically optimalquadratic growth rate, called a breeder or lobster, which worked by leaving behind a trail of guns.
It is possible for gliders to interact with other objects in
interesting ways. For example, if two gliders are shot at a block in a
specific position, the block will move closer to the source of the
gliders. If three gliders are shot in just the right way, the block will
move farther away. This sliding block memory can be used to simulate a counter. It is possible to construct logic gates such as AND, OR, and NOT using gliders. It is possible to build a pattern that acts like a finite-state machine connected to two counters. This has the same computational power as a universal Turing machine, so the Game of Life is theoretically as powerful as any computer with unlimited memory and no time constraints; it is Turing complete. In fact, several different programmable computer architectures have been implemented in the Game of Life, including a pattern that simulates Tetris.
Oblique spaceships
Until
the 2010s, all known spaceships could only move orthogonally or
diagonally. Spaceships which move neither orthogonally nor diagonally
are commonly referred to as oblique spaceships. On May 18, 2010, Andrew J. Wade announced the first oblique spaceship,
dubbed "Gemini", that creates a copy of itself on (5,1) further while
destroying its parent. This pattern replicates in 34 million generations, and uses an
instruction tape made of gliders oscillating between two stable
configurations made of Chapman–Greene construction arms. These, in turn,
create new copies of the pattern, and destroy the previous copy. In
December 2015, diagonal versions of the Gemini were built.
A more specific case is a knightship, a spaceship that moves two squares left for every one square it moves down (like a knight in chess), whose existence had been predicted by Elwyn Berlekamp since 1982. The first elementary knightship, Sir Robin, was discovered in 2018 by Adam P. Goucher. This is the first new spaceship movement pattern for an elementary
spaceship found in forty-eight years. "Elementary" means that it cannot
be decomposed into smaller interacting patterns such as gliders and
still lifes.
Self-replication
A
pattern can contain a collection of guns that fire gliders in such a
way as to construct new objects, including copies of the original
pattern. A universal constructor can be built which contains a
Turing complete computer, and which can build many types of complex
objects, including more copies of itself. On November 23, 2013, Dave Greene built the first replicator in the Game of Life that creates a complete copy of itself, including the instruction tape. In October 2018, Adam P. Goucher finished his construction of the 0E0P
metacell, a metacell capable of self-replication. This differed from
previous metacells, such as the OTCA metapixel by Brice Due, which only
worked with already constructed copies near them. The 0E0P metacell
works by using construction arms to create copies that simulate the
programmed rule. The actual simulation of the Game of Life or other Moore neighbourhood rules is done by simulating an equivalent rule using the von Neumann neighbourhood with more states. The name 0E0P is short for "Zero Encoded by Zero Population", which
indicates that instead of a metacell being in an "off" state simulating
empty space, the 0E0P metacell removes itself when the cell enters that
state, leaving a blank space.
Undecidability
Many
patterns in the Game of Life eventually become a combination of still
lifes, oscillators, and spaceships; other patterns may be called
chaotic. A pattern may stay chaotic for a very long time until it
eventually settles to such a combination.
The Game of Life is undecidable,
which means that given an initial pattern and a later pattern, no
algorithm exists that can tell whether the later pattern is ever going
to appear. Given that the Game of Life is Turing-complete, this is a
corollary of the halting problem: the problem of determining whether a given program will finish running or continue to run forever from an initial input.
Iteration
From
most random initial patterns of living cells on the grid, observers
will find the population constantly changing as the generations tick by.
The patterns that emerge from the simple rules may be considered a form
of mathematical beauty.
Small isolated subpatterns with no initial symmetry tend to become
symmetrical. Once this happens, the symmetry may increase in richness,
but it cannot be lost unless a nearby subpattern comes close enough to
disturb it. In a very few cases, the society eventually dies out, with
all living cells vanishing, though this may not happen for a great many
generations. Most initial patterns eventually burn out, producing either
stable figures or patterns that oscillate forever between two or more
states; many also produce one or more gliders or spaceships that travel
indefinitely away from the initial location. Because of the
nearest-neighbour based rules, no information can travel through the
grid at a greater rate than one cell per unit time, so this velocity is
said to be the cellular automaton speed of light and denoted c.
Algorithms
Early
patterns with unknown futures, such as the R-pentomino, led computer
programmers to write programs to track the evolution of patterns in the
Game of Life. Most of the early algorithms
were similar: they represented the patterns as two-dimensional arrays
in computer memory. Typically, two arrays are used: one to hold the
current generation, and one to calculate its successor. Often 0 and 1
represent dead and live cells, respectively. A nested for loop
considers each element of the current array in turn, counting the live
neighbours of each cell to decide whether the corresponding element of
the successor array should be 0 or 1. The successor array is displayed.
For the next iteration, the arrays may swap roles so that the successor
array in the last iteration becomes the current array in the next
iteration, or one may copy the values of the second array into the first
array then update the second array from the first array again.
A variety of minor enhancements to this basic scheme are
possible, and there are many ways to save unnecessary computation. A
cell that did not change at the last time step, and none of whose
neighbours changed, is guaranteed not to change at the current time step
as well, so a program that keeps track of which areas are active can
save time by not updating inactive zones.
To avoid decisions and branches in the counting loop, the rules can be rearranged from an egocentric
approach of the inner field regarding its neighbours to a scientific
observer's viewpoint: if the sum of all nine fields in a given
neighbourhood is three, the inner field state for the next generation
will be life; if the all-field sum is four, the inner field retains its
current state; and every other sum sets the inner field to death.
To save memory, the storage can be reduced to one array plus two
line buffers. One line buffer is used to calculate the successor state
for a line, then the second line buffer is used to calculate the
successor state for the next line. The first buffer is then written to
its line and freed to hold the successor state for the third line. If a toroidal
array is used, a third buffer is needed so that the original state of
the first line in the array can be saved until the last line is
computed.
Glider gun within a toroidal array. The stream of gliders eventually wraps around and destroys the gun.Red glider on a square lattice with periodic boundary conditions
In principle, the Game of Life field is infinite, but computers have
finite memory. This leads to problems when the active area encroaches on
the border of the array. Programmers have used several strategies to
address these problems. The simplest strategy is to assume that every
cell outside the array is dead. This is easy to program but leads to
inaccurate results when the active area crosses the boundary. A more
sophisticated trick is to consider the left and right edges of the field
to be stitched together, and the top and bottom edges also, yielding a toroidal
array. The result is that active areas that move across a field edge
reappear at the opposite edge. Inaccuracy can still result if the
pattern grows too large, but there are no pathological edge effects.
Techniques of dynamic storage allocation may also be used, creating
ever-larger arrays to hold growing patterns. The Game of Life on a
finite field is sometimes explicitly studied; some implementations, such
as Golly,
support a choice of the standard infinite field, a field infinite only
in one dimension, or a finite field, with a choice of topologies such as
a cylinder, a torus, or a Möbius strip.
Alternatively, programmers may abandon the notion of representing
the Game of Life field with a two-dimensional array, and use a
different data structure, such as a vector of coordinate pairs
representing live cells. This allows the pattern to move about the field
unhindered, as long as the population does not exceed the size of the
live-coordinate array. The drawback is that counting live neighbours
becomes a hash-table lookup or search operation, slowing down simulation
speed. With more sophisticated data structures this problem can also be
largely solved.
For exploring large patterns at great time depths, sophisticated algorithms such as Hashlife
may be useful. There is also a method for implementation of the Game of
Life and other cellular automata using arbitrary asynchronous updates
while still exactly emulating the behaviour of the synchronous game. Source code examples that implement the basic Game of Life scenario in various programming languages, including C, C++, Java and Python can be found at Rosetta Code.
Since the Game of Life's inception, new, similar cellular automata
have been developed. The standard Game of Life is symbolized in
rule-string notation as B3/S23. A cell is born if it has exactly three
neighbours, survives if it has two or three living neighbours, and dies
otherwise. The first number, or list of numbers, is what is required for
a dead cell to be born. The second set is the requirement for a live
cell to survive to the next generation. Hence B6/S16 means "a cell is
born if there are six neighbours, and lives on if there are either one
or six neighbours". Cellular automata on a two-dimensional grid that can
be described in this way are known as Life-like cellular automata. Another common Life-like automaton, Highlife,
is described by the rule B36/S23, because having six neighbours, in
addition to the original game's B3/S23 rule, causes a birth. HighLife is
best known for its frequently occurring replicators.
Additional Life-like cellular automata exist. The vast majority of these 218 different rules produce universes that are either too chaotic or too desolate to be of
interest, but a large subset do display interesting behaviour. A further
generalization produces the isotropic rulespace, with 2102 possible cellular automaton rules (the Game of Life again being one of them). These are rules that use
the same square grid as the Life-like rules and the same eight-cell
neighbourhood, and are likewise invariant under rotation and reflection.
However, in isotropic rules, the positions of neighbour cells relative
to each other may be taken into account in determining a cell's future
state—not just the total number of those neighbours.
A
sample of a 48-step oscillator along with 2-step and 4-step oscillators
from a two-dimensional hexagonal Game of Life (rule H:B2/S34)
Some variations on the Game of Life modify the geometry of the
universe as well as the rules. The above variations can be thought of as
a two-dimensional square, because the world is two-dimensional and laid
out in a square grid. One-dimensional square variations, known as elementary cellular automata, and three-dimensional square variations have been developed, as have two-dimensional hexagonal and triangular variations. A variant using aperiodic tiling grids has also been made.
Conway's rules may also be generalized such that instead of two states, live and dead,
there are three or more. State transitions are then determined either
by a weighting system or by a table specifying separate transition rules
for each state; for example, Mirek's Cellebration's multi-coloured
Rules Table and Weighted Life rule families each include sample rules
equivalent to the Game of Life.
Patterns relating to fractals and fractal systems may also be
observed in certain Life-like variations. For example, the automaton
B1/S12 generates four very close approximations to the Sierpinski triangle
when applied to a single live cell. The Sierpinski triangle can also be
observed in the Game of Life by examining the long-term growth of an
infinitely long single-cell-thick line of live cells, as well as in Highlife, Seeds (B2/S), and Stephen Wolfram's Rule 90.
Immigration is a variation that is very similar to the Game of Life, except that there are two on
states, often expressed as two different colours. Whenever a new cell
is born, it takes on the on state that is the majority in the three
cells that gave it birth. This feature can be used to examine
interactions between spaceships and other objects within the game. Another similar variation, called QuadLife, involves four different on
states. When a new cell is born from three different on neighbours, it
takes the fourth value, and otherwise, like Immigration, it takes the
majority value. Except for the variation among on cells, both of these variations act identically to the Game of Life.
Music
Various musical composition techniques use the Game of Life, especially in MIDI sequencing. A variety of programs exist for creating sound from patterns generated in the Game of Life.
Notable programs
The 6366548773467669985195496000th (6×1027) generation of a Turing machine, made in the Game of Life, computed in less than 30 seconds on an Intel Core Duo 2 GHz CPU using Golly in Hashlife mode
Computers have been used to follow and simulate the Game of Life
since it was first publicized. When John Conway was first investigating
how various starting configurations developed, he tracked them by hand
using a go
board with its black and white stones. This was tedious and prone to
errors. The first interactive Game of Life program was written in an
early version of ALGOL 68C for the PDP-7 by M. J. T. Guy and S. R. Bourne. The results were published in the October 1970 issue of Scientific American, along with the statement: "Without its help, some discoveries about the game would have been difficult to make."
A color version of the Game of Life was written by Ed Hall in 1976 for Cromemco microcomputers, and a display from that program filled the cover of the June 1976 issue of Byte. The advent of microcomputer-based color graphics from Cromemco has been credited with a revival of interest in the game.
Two early implementations of the Game of Life on home computers were by Malcolm Banthorpe written in BBC BASIC. The first was in the January 1984 issue of Acorn User magazine, and Banthorpe followed this with a three-dimensional version in the May 1984 issue. Susan Stepney, Professor of Computer Science at the University of York, followed this up in 1988 with Life on the Line, a program that generated one-dimensional cellular automata.
There are now thousands of Game of Life programs online, so a
full list will not be provided here. The following is a small selection
of programs with some special claim to notability, such as popularity or
unusual features. Most of these programs incorporate a graphical user
interface for pattern editing and simulation, the capability for
simulating multiple rules including the Game of Life, and a large
library of interesting patterns in the Game of Life and other cellular
automaton rules.
Golly
is a cross-platform (Windows, Macintosh, Linux, iOS, and Android)
open-source simulation system for the Game of Life and other cellular
automata (including all Life-like cellular automata, the Generations
family of cellular automata from Mirek's Cellebration, and John von
Neumann's 29-state cellular automaton) built by Andrew Trevorrow and
Tomas Rokicki. It includes the Hashlife algorithm for extremely fast
generation, and Lua or Python scriptability for both editing and simulation.
Mirek's Cellebration is a freeware one- and two-dimensional cellular
automata viewer, explorer, and editor for Windows. It includes powerful
facilities for simulating and viewing a wide variety of cellular
automaton rules, including the Game of Life, and a scriptable editor.
Xlife is a cellular-automaton laboratory by Jon Bennett. The
standard UNIX X11 Game of Life simulation application for a long time,
it has also been ported to Windows. It can handle cellular automaton
rules with the same neighbourhood as the Game of Life, and up to eight
possible states per cell.
Dr. Blob's Organism is a Shoot 'em up based on Conway's Life. In the game, Life continually generates on a group of cells within a "petri dish". The patterns formed are smoothed and rounded to look like a growing amoeba
spewing smaller ones (actually gliders). Special "probes" zap the
"blob" to keep it from overflowing the dish while destroying its
nucleus.
Google implemented an easter egg of the Game of Life in 2012. Users who search for the term are shown an implementation of the game in the search results page.
The visual novel Anonymous;Code includes a basic implementation of the Game of Life in it, which is connected to the plot of the novel. Near the end of Anonymous;Code,
a certain pattern that appears throughout the game as a tattoo on the
heroine Momo Aizaki has to be entered into the Game of Life to complete
the game (Kok's galaxy, the same pattern used as the logo for the open-source Game of Life program Golly).
