The standard Erdos-Renyi model of random graphs begins with n isolated vertices, and at each round a random edge is added. Parametrizing n/2 rounds as one time unit, a phase transition occurs at time t = 1 when a giant component (one of size constant times n) first appears. Under the inffuence of statistical mechanics, the investigation of related phase transitions has become an important topic in random graph theory. We define a broad class of graph evolutions in which at each round one chooses one of two random edges {v(1),v(2)}, {v(3),v(4)} to add to the graph. The selection is made by examining the sizes of the components of the four vertices. We consider the susceptibility S(t) at time t, being the expected component size of a uniformly chosen vertex. The expected change in S(t) is found which produces in the limit a differential equation for S(t). There is a critical time t(c) so that S(t) -> infinity as t approaches t(c) from below. We show that the discrete random process asymptotically follows the differential equation for all subcritical t<t(c). Employing classic results of Cramer on branching processes we show that the component sizes of the graph in the suberitical regime have an exponential tail. In particular, the largest component is only logarithmic in size. In the supercritical regime t > t(c) we show the existence of a giant component, so that t = t(c) may be fairly considered a phase transition. Computer aided solutions to the possible differential equations for susceptibility allow us to establish lower and upper bounds on the extent to which we can either delay or accelerate the birth of the giant component.
