The study of self-replicating structures or machines has been taking place now for almost half a century. My goal in this article is to present an overview of research carried out in the domain of self-replication over the past 50 years, starting from von Neumann's work in the late 1940s and continuing to the most recent research efforts. I shall concentrate on computational models, that is, ones that have been studied from a computer science point of view, be it theoretical or experimental. The systems are divided into four major classes, according to the model on which they are based: cellular automata, computer programs, strings (or strands), or an altogether different approach. With the advent of new materials, such as synthetic molecules and nanomachines, it is quite possible that we shall see this somewhat theoretical domain of study producing practical, real-world applications.
Abstract-If one considers life on Earth since its very beginning, three levels of organization can be distinguished: the phylogenetic level concerns the temporal evolution of the genetic programs within individuals and species, the ontogenetic level concerns the developmental process of a single multicellular organism, and the epigenetic level concerns the learning processes during an individual organism's lifetime. In analogy to nature, the space of bio-inspired hardware systems can be partitioned along these three axes, phylogeny, ontogeny, and epigenesis, giving rise to the POE model. This paper is an exposition and examination of bio-inspired systems within the POE framework, with our goals being: 1) to present an overview of current-day research, 2) to demonstrate that the POE model can be used to classify bioinspired systems, and 3) to identify possible directions for future research, derived from a POE outlook. We first discuss each of the three axes separately, considering the systems created to date and plotting directions for continued progress along the axis in question. We end our exposition by a discussion of possible research directions, involving the construction of bio-inspired systems that are situated along two, and ultimately all three axes. This could give rise to novel systems endowed with evolutionary, reproductive, regenerative, and learning capabilities.
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