Our concepts of biology, evolution and complexity are constrained by having observed only a single instance of life, life on Earth. A truly comparative biology is needed to extend these concepts. Because we can not observe life on other planets, we are left with the alternative of creating artificial life forms on Earth. I will discuss the approach of inoculating evolution by natural selection into the medium of the digital computer. This is not a physical/chemical medium, it is a logical/informational medium. Thus these new instances of evolution are not subject to the same physical laws as organic evolution (e.g., the laws of thermodynamics), and therefore exist in what amounts to another universe, governed by the "physical laws" of the logic of the computer. This exercise gives us a broader perspective on what evolution is and what it does. An evolutionary approach to synthetic biology consists of inoculating the process of evolution by natural selection into an artificial medium. E...

This paper lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained and, where deemed helpful, some promising paths to its solution are indicated. Introduction At the dawn of the last century, Hilbert proposed a set of open mathematical problems. They proved to be an extraordinarily effective guideline for mathematical research in the following century. Based on a substantial body of existing mathematical theory, the challenges were both precisely formulated and positioned so that a significant body of missing theory needed to be developed to achieve their solution, thereby enriching mathematics as a whole. In contrast with mathematics, artificial life is quite young and essentially interdisciplinary. The phrase artificial life was coined by C. Langton [13], who envisaged an investigation of life as it is in the context of life as it could be. Although artifi...

CA rules can be classied automatically for a spectrum of ordered, complex and chaotic dynamics, by a measure of the variance of input-entropy over time. Rules that support interacting gliders and related complex dynamics can be identied, giving an unlimited source for further study. The distribution of rule classes in rule-space can be shown. A byproduct of the method allows the automatic \ltering" of CA space-time patterns to show up gliders and related emergent congurations more clearly. The classication seems to correspond to our subjective judgment of space-time dynamics. There are also approximate correlations with global measures on convergence in attractor basins, characterized by the distribution of in-degree sizes in their branching structure, and to the rule parameter, Z. Based on computer experiments using the software Discrete Dynamics Lab (DDLab)[22], this paper explains the methods and presents results for 1d CA. 1 Introduction Cellular automata (CA) are a much stud...

We constructed a simple evolutionary system, "evoloop," on a deterministic nine-state five-neighbor cellular automata (CA) space by improving the structurally dissolvable self-reproducing loop we had previously contrived [14] after Langton's self-reproducing loop [7]. The principal role of this improvement is to enhance the adaptability (a degree of the variety of situations in which structures in the CA space can operate regularly) of the self-reproductive mechanism of loops. The experiment with evoloop met with the intriguing result that, though no mechanism was explicitly provided to promote evolution, the loops varied through direct interaction of their phenotypes, smaller individuals were naturally selected thanks to their quicker self-reproductive ability, and the whole population gradually evolved toward the smallest ones. This result gives a unique example of evolution of self-replicators where genotypical variation is caused by precedent phenotypical variation. Such interrelation of genotype and phenotype would be one of the important factors driving the evolutionary process of primitive life forms that might have actually occurred in ancient times.

This article describes in detail an implementation of John von Neumann's self-reproducing machine. Self-reproduction is achieved as a special case of construction by a universal constructor. The theoretical proof of the existence of such machines was given by John von Neumann in the early 1950s [6], but was first implemented in 1994, by the author in collaboration with R. Nobili. Our implementation relies on an extension of the state-transition rule of von Neumann's original cellular automaton. This extension was introduced to simplify the design of the constructor. The main operations in our constructor can be mapped into operations of von Neumann's machine. 1 Introduction Von Neumann [6] introduced constructive universality in cellular automata to study the implementability of self-reproducing machines and to extend the concept of computational universality, introduced by A. Turing [5]. A computing machine is said to be computationally universal if it is capable of simu...

We define several qualitative classes of cellular automata (CA) behavior, based on various statistical measures, and describe how the space of all cellular automata is organized. As a cellular automaton...

This paper presents a new approach to image feature extraction which utilizes evolutionary autonomous agents. Image features are often mathematically defined in terms of the gray-level intensity at image pixels. The optimality of image feature extraction is to find all the feature pixels from the image. In the proposed approach, the autonomous agents, being distributed computational entities, operate directly in the two-dimensional lattice of a digital image, and exhibit a number of reactive behaviors. In order to effectively locate the feature pixels, individual agents sense the local stimuli from their image environment by means of evaluating the gray-level intensity of locally connected pixels, and accordingly activate their behaviors. The behavioral repository of the agents consists of: (1) featuremarking at local pixels and self-reproduction of offspring agents in the neighboring regions if the local stimuli are found to satisfy feature conditions, (2) diffusion to adjacent image ...

The structure of the elementary cellular automata rule space is investigated. The probabilities for a rule to be connected to other rules in the same class #intra-class#, as well as rules in di#erent classes #inter-class#, are determined. The intra-class connection probabilities vary from around 0.3 to 0.5, an indication of the strong tendency for rules with the similar behavior to be next to each other. Rules are also grouped according to the mean- #eld descriptions. The mean-#eld clusters are classi#ed into three classes #nonlinear, linear, and inversely linear# according to the #hot bits" in the rule table. It is shown that such classi#cation provides another easy way to describe the rule space.

Self-reproducing, cellular automata-based systems developed to date broadly fall under two categories; the first consists of machines which are capable of performing elaborate tasks, yet are too complex to simulate, while the second consists of extremely simple machines which can be entirely implemented, yet lack any additional functionality aside from self-reproduction. In this paper we present a self-reproducing system which is completely realizable, while capable of executing any desired program, thereby exhibiting universal computation. Our starting point is a simple self-reproducing loop structure onto which we "attach" an executable program (Turing machine) along with its data. The three parts of our system (loop, program, data) are all reproduced, after which the program is run on the given data. The system reported in this paper has been simulated in its entirety; thus, we attain a viable, self-reproducing machine with programmable capabilities. 1 Introduction The study of art...

Cellular automata are dynamical systems in which space and time are discrete, where each cell obeys the same rule and has a finite number of states. In this paper we study non-uniform cellular automata, i.e. with non-uniform local interaction rules. Two different models are described. In the first a cell's rule may be regarded as a genotype whose phenotypic effect is achieved by rule application. Our focus is on evolution in rule space starting from a random gene pool, i.e. rule population. The second model focuses on the study of complex structures formed by a small number of rules, where the term `complex' denotes a structure consisting of simple grid cells, acting as a single "organism ". 1 Introduction Cellular automata (CA) are dynamical systems in which space and time are discrete. The states of cells in a regular grid are updated synchronously according to a local interaction rule. Each cell obeys the same rule and has a finite (usually small) number of states (Toffoli and Marg...