On Solving the System

Abstract

Mathematically a system is said to be solved if its future states can be predicted from the information provided by the present and past state history. In this paper we present a way of solving artificial life systems using the principles of state-machines. We present the view of manipulating the artificial systems considering them as being embedded in external program entities. Further, we discuss the technique of using algorithmic transformations to understand the behavioral complexity of virtual organisms. Finally, we relate the complexity of virtual systems with the algorithmic complexity and establish that open-ended evolution requires programs with ever increasing algorithmic complexity