Abstract

The investigation of a method for postulating counterfactual histories of science has led to the development of a theory of science based on general units of knowledge, which are called “advances”. Advances are passed on from scientist to scientist, and may be seen as “causing” the appearance of other advances. This results in networks which may be analyzed in terms of probabilistic causal models, which are readily encodable in computer language. The probability for a set of advances to give rise to another advance is taken to be invariant through history, but depends on a typical time span which is an inverse function of the degree of development of science. Examples are given from the early science of magnetism and from the 19th century physics.