A Physical and Mathematical Framework for the Semantic Theory of Evolution
This work provides a foundational framework for understanding evolution through communication codes, potentially impacting biology and AI, but it is incremental in applying existing theories to a new context.
The paper tackles the problem of grounding the Semantic Theory of Evolution (STE) in physical and mathematical frameworks, showing that arbitrary communication codes in life can be expressed using Evidence Theory and linking ambiguity reduction to entropy principles.
The Semantic Theory of Evolution (STE) takes the existence of a number of arbitrary communication codes as a fundamental feature of life, from the genetic code to human cultural communication codes. Their arbitrariness enables, at each level, the selection of one out of several possible correspondences along with the generation of meaning. STE enables more novelties to emerge and suggests a greater variety of potential life forms. With this paper I ground STE on physical theories of meaningful information. Furthermore, I show that key features of the arbitrary communication codes employed by living organisms can be expressed by means of Evidence Theory (ET). In particular, I adapt ET to organisms that merely react to sequences of stimuli, explain its basics for organisms that are capable of prediction, and illustrate an unconventional version suitable for the most intricate communication codes employed by humans. Finally, I express the natural trend towards ambiguity reduction in terms of information entropy minimization along with thermodynamic entropy maximization.