Necessary conditions for density classification by cellular automata.

Classifying the initial configuration of a binary-state cellular automaton (CA) as to whether it contains a majority of 0s or 1s-the so-called density-classification problem-has been studied over the past decade by researchers wishing to glean an understanding of how locally interacting systems compute global properties. In this paper we prove two necessary conditions that a CA must satisfy in order to classify density: (1) the density of the initial configuration must be conserved over time, and (2) the rule table must exhibit a density of 0.5.

A statistical study of a class of cellular evolutionary algorithms.

Parallel evolutionary algorithms, over the past few years, have proven empirically worthwhile, but there seems to be a lack of understanding of their workings. In this paper we concentrate on cellular (fine-grained) models, our objectives being: (1) to introduce a suite of statistical measures, both at the genotypic and phenotypic levels, which are useful for analyzing the workings of cellular evolutionary algorithms; and (2) to demonstrate the application and utility of these measures on a specific example-the cellular programming evolutionary algorithm. The latter is used to evolve solutions to three distinct (hard) problems in the cellular-automata domain: density, synchronization, and random number generation. Applying our statistical measures, we are able to identify a number of trends common to all three problems (which may represent intrinsic properties of the algorithm itself), as well as a host of problem-specific features. We find that the evolutionary algorithm tends to undergo a number of phases which we are able to quantitatively delimit. The results obtained lead us to believe that the measures presented herein may prove useful in the general case of analyzing fine-grained evolutionary algorithms.

Design, observation, surprise! A test of emergence.

The field of artificial life (Alife) is replete with documented instances of emergence, though debate still persists as to the meaning of this term. We contend that, in the absence of an acceptable definition, researchers in the field would be well served by adopting an emergence certification mark that would garner approval from the Alife community. Toward this end, we propose an emergence test, namely, criteria by which one can justify conferring the emergence label.