Design of a P System based Artificial Graph Chemistry

TL;DR

This paper introduces a P system based artificial graph chemistry framework to study the emergence of life-like structures, integrating probabilistic rule evolution within a formalism that captures semantic and organizational information.

Contribution

It presents a novel P system extension for artificial graph chemistry, incorporating probabilities to model molecular reactions and evolution of life-like structures.

Findings

Framework captures semantic and organizational info

Probabilistic rules model molecular evolution

Unified formalism classifies artificial chemistries

Abstract

Artificial Chemistries (ACs) are symbolic chemical metaphors for the exploration of Artificial Life, with specific focus on the origin of life. In this work we define a P system based artificial graph chemistry to understand the principles leading to the evolution of life-like structures in an AC set up and to develop a unified framework to characterize and classify symbolic artificial chemistries by devising appropriate formalism to capture semantic and organizational information. An extension of P system is considered by associating probabilities with the rules providing the topological framework for the evolution of a labeled undirected graph based molecular reaction semantics.