Evolving Categories: Consistent Framework for Representation of Data and Algorithms

Abstract

A concept of "evolving categories" is suggested to build a simple, scalable, mathematically consistent framework for representing in uniform way both data and algorithms. A state machine for executing algorithms becomes clear, rich and powerful semantics, based on category theory, and still allows easy implementation. Moreover, it gives an original insight into the nature and semantics of algorithms.