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Conway's Game of Life is a cellular automaton in which a simple local rule produces patterns that remain still, pulse, or travel across a square grid. Choose the starting pattern; after that there are no player decisions. The Life blinker and Life glider below make the surprise concrete: the rule mentions only births and survival, yet repeated applications create a clock and a moving shape.

The standard board is infinite, with cells at ordered pairs $(x,y)\in {\mathbb{Z}}^2$ of integers. At generation $t\in \{0,1,2,\dots \}$ let $a_t(x,y)$ be $1$ for a live cell and $0$ for a dead cell. Count all eight cells sharing an edge or a corner, excluding the center itself:The local Boolean function defining the next generation isThis is the rule B3/S23: a dead cell is born with exactly three live neighbors; a live cell survives with exactly two or three. A live cell with zero or one, or with four through eight, dies. A dead cell with two stays dead. All counts and center states come from generation $t$: this is a synchronous update, even if an algorithm computes its cells one at a time.^[ref]

In particular, the two births in the Life blinker do not help any other cell survive until the following generation. Writing each answer over its old value and then reading that new value for another count changes the rule. The simplest correct algorithm reads one array and writes the next generation into a second array; swap their roles after the entire step. The one-row in-place Life update achieves the same rule with less auxiliary storage by preserving the old values that later counts still need.

A finite implementation must specify its boundary convention. Holding all cells outside the rectangle permanently dead can destroy a Life glider when it reaches the edge. Wrapping neighbor coordinates from one edge to the opposite edge allows interaction with patterns on the other side. Neither convention is the infinite board. The figures display finite windows into an infinite board initially dead everywhere except the stated live cells; the windows do not impose walls.

Conway's Game of Life illustrates emergence in a precise, modest sense: the Life glider's motion is a collective pattern derived from local birth and death, without a motion command. It has deterministic evolution; visually surprising behavior introduces no random choices. Nor do the words "alive" and "dead" make it an experimentally validated model of biology. The beauty is that the same rule yields a stable four-cell square, the Life blinker, and the Life glider: three qualitatively different behaviors from a handful of cells.

For the stable square, take the live set $\{(0,0),(1,0),(0,1),(1,1)\}$. Each live cell has three live neighbors, and every dead cell has at most two. The next generation is identical: this configuration is a fixed point of the global update function. In contrast, the Life blinker returns after two generations, and the Life glider returns only after allowing a translation.

The patterns are useful as small, exact checks of an algorithm: the square checks survival without births, the Life blinker checks births and deaths in one simultaneous step, and the Life glider checks several steps and diagonal neighbors. More elaborate constructions can encode data and assemble Boolean circuits; Johnston and Greene develop constructions that simulate arbitrary computation in their chapter 9. This is a statement about suitably designed patterns with enough space and time, not a claim that every starting pattern computes something useful or that a fixed finite board has unlimited computer memory.^[ref]

Martin Gardner introduced Conway's Game of Life to his Scientific American readers in October 1970, reporting that Conway selected the rules after experimentation with patterns. The aim was sustained, varied behavior rather than immediate extinction or trivially demonstrable unlimited growth. These were mathematical explorations of chosen rules.^[ref]

Gardner's hands-on procedure is still a useful experiment: place black counters for the current live cells; mark doomed counters by stacking another black counter; mark births with white counters; finish checking before removing the doomed stacks and turning white counters black. Count only the original black occupants. Repeat with three adjacent counters to obtain the Life blinker, then with the five coordinates of the Life glider. Recording each generation tests whether the procedure implements the rule; it does not measure a natural population.^[ref]

The Life blinker alternates between horizontal and vertical lines of three live cells. Start with $B_0=\{(-1,0),(0,0),(1,0)\}$ and every other cell dead. The two endpoints each have one live neighbor and die; the center has two and survives. The dead cells $(0,-1)$ and $(0,1)$ each have three live neighbors and are born. No other dead cell has three. ThereforeThe same neighbor-count argument with horizontal and vertical exchanged gives the second step. Since $B_1\ne B_0$, the period is exactly two, rather than merely a divisor of two.

The Life blinker is a minimal hands-on check of synchronous updating. Mark both endpoints for death and both births before changing anything. Removing an endpoint early would make a prospective birth see only two neighbors; adding a birth early would alter other counts. A correct implementation reproduces both sets above exactly, rather than merely keeping the live population equal to three.

A Life oscillator is a nonconstant periodic orbit of the Conway's Game of Life update function $F$. Its period is the least positive integer $p$ for which $F^p(A)=A$, comparing the entire live-cell set at the same coordinates. A configuration that never changes is instead a fixed point; a Life glider is not a Life oscillator on the infinite board because it returns at displaced coordinates. The Life blinker has period two.^[ref]

On a finite rectangular Conway's Game of Life board stored as an array of Boolean variables, retain the preceding row's old values in one auxiliary row. Before overwriting a column, retain rolling sums of the old three-cell vertical columns. Their sum minus the old center is the old neighbor count. Read the next column before changing the current one; replace the saved row entry by the old current cell. The invariant is that every count uses the previous generation, just as in the two-array algorithm. For a board with $H$ rows and $W$ columns this uses $O(W)$ auxiliary storage and $O(HW)$ time. The boundary convention must still be implemented explicitly. The Life blinker and Life glider provide exact expected generations for checking it.