This paper focuses on the phenomena of evolution whose appearance is notable because no explicit mutation, recombination or artificial selection operators are introduced. We call the system self-evolving because every variation is performed by the objects themselves in their machine form. Keywords: artificial chemistry, autocatalytic reaction system, molecular computing, prebiotic evolution, self-organization, self-programming 1

This article reviews the growing body of scientific work in Artificial Chemistry. First, common motivations and fundamental concepts are introduced. Second, current research activities are discussed along three application dimensions: modelling, information processing and optimization. Finally, common phenomena among the different systems are summarized. It is argued here that Artificial Chemistries are "the right stuff" for the study of pre-biotic and bio-chemical evolution, and they provide a productive framework for questions regarding the origin and evolution of organizations in general. Furthermore, Artificial Chemistries have a broad application range to practical problems as shown in this review.

We discuss a system of autocatalytic sequences of binary numbers. Sequences come in two forms, a 1dimensional form (operands) and a 2-dimensional form (operators) that are able to react with each other. The resulting reaction network shows signs of emerging metabolisms. We discuss the general framework and examine specific interactions for a system with strings of length 4 bits. A selfmaintaining network of string types and parasitic interactions are shown to exist. Introduction Published in: Proceedings ARTIFICIAL LIFE IV R. Brooks and P. Maes (Eds.) MIT Press, Cambridge, MA, 1994 pp. 109 --- 118 Sequences of binary numbers are the most primitive form of information storage we know today. They are able to code any kind of man-made information, be it still or moving images, sound waves and other sensory stimulations, be it written language or the rules of mathematics, just to name a few. As the success of vonNeumann computers has shown over the last 50 years, binary sequences are also...

Recently, biochemical systems have been shown to possess interesting computational properties. In a parallel development, the chemical computation metaphor is becoming more and more frequently used as part of the emergent computation paradigm in Computer Science. We review in this contribution the idea behind the chemical computational metaphor and outline its relevance for nanotechnology. We set up a simulated reaction system of mathematical objects and examine its dynamics by computer experiments. Typical problems of computer science, like sorting, parity checking or prime number computation are placed within this context. The implications of this approach for nanotechnology, parallel computers based on molecular devices and DNA-RNA-protein information processing are discussed. 1 Introduction The idea of using natural systems for computational purposes has long been pondered. Haken, for instance, has proposed to use laser mode competition as a way to recognize patterns [1]. Others h...

Abstract. Genetic Programming has been slow at realizing other programming paradigms than conventional, deterministic, sequential von-Neumann type algorithms. In this contribution we discuss a new method of execution of programs introduced recently: Algorithmic Chemistries. Therein, register machine instructions are executed in a non–deterministic order, following a probability distribution. Program behavior is thus highly dependent on frequency of instructions and connectivity between registers. Here we demonstrate the performance of GP on evolving solutions to a parity problem in a system of this type. 1

In an algorithmic artificial chemistry the objects (molecules) are data and the interactions (reactions) among them are defined by an algorithm. The same object can appear in two forms: (1) as a machine (operator) or (2) as data (operand). Thus, the same object can, on the one hand, process other objects or, on the other hand, it can be processed. This dualism enables to implicitly define a constructive artificial chemistry which exhibits quite complex behavior. Remarkably, even evolutionary behavior emerged in our experiments, without defining any explicit variation operators or fitness-function. In addition to microscopic methods (e.g., monitoring the actions of single molecules) and macroscopic measures (e.g., diversity or complexity) we developed a stepwise mesoscopic analysis method based on classification and dynamic clustering. Knowledge about the system is accumulated by an iterative process in which measuring tools (classificators) extract information which i...

A topological structure based on hashing for an algorithmic reaction system is introduced. Hashing, as a very efficient storage method for certain problems, uses an important property of the computer: Its ability to accurately access a specific address in memory space. It is shown, how a selforganising system can be built with this method. We discuss experiments with a reaction system based on the resulting hash topology. Keywords: artificial life, self-evolution, prebiotic evolution, molecular computer, self-programming, autokatalytic reaction system, hypercycle, self-replication 1 Introduction Computer models can be used to study complex phenomena of self-organization. Life itself has become the topic of such studies in recent years [13]. A sub-class of models are systems that are inspired by chemical reaction systems [8, 15, 18]. Other simulations intend to model other levels of life-like behavior, e.g. the evolution of cells and organisms [14, 16]. These models nearly always app...