Finite state complexity

In this paper we develop a version of Algorithmic Information Theory (AIT) based on finite transducers instead of Turing machines; the complexity induced is called finite-state complexity. In spite of the fact that the Universality Theorem (true for Turing machines) is false for finite transducers, the Invariance Theorem holds true for finite-state complexity. We construct a class of finite-state complexities based on various enumerations of the set of finite transducers. In contrast with descriptional complexities (plain, prefix-free) from AIT, finite-state complexity is computable and there is no a priori upper bound for the number of states used for minimal descriptions of arbitrary strings. Upper and lower bounds for the finite-state complexity of arbitrary strings, and for strings of particular types, are given and incompressible strings are studied.