Evolving Complexity and Similarity in an Artificial Life Framework based on Formal Language Theory

Abstract

In this thesis, a formal framework where the evolution of biological complexity can be studied in an objective way is defined. That objectivity is due to state complexity for regular languages is used and it is a well-known and rigorous complexity measure. Such a framework is composed of a population of cyclic unary regular languages (individuals) that try to adapt to a given environment (that also consists of cyclic unary regular languages) by means of evolutionary computation.