Understanding self-replication from an information processing perspective is important because, among other things, it can shed light on molecular mechanisms of biological reproduction and on prebiotic chemical evolution. Intuition, biological knowledge, and early computational models of self-replication all suggested that self-replication is an inherently complex process. In this paper we describe recent computational studies that challenge this viewpoint. We summarize our recent work with cellular automata models of simple yet non-trivial self-replicating structures called unsheathed loops. For example, one unsheathed loop consists of only six components and requires only 20 rules to specify the local intercomponent interactions needed to bring about replication. The implication of this work is that, when viewed as an emergent property of numerous local, concurrent interactions between components, self-replicating systems can be substantially simpler than is generally recognized. 1 Developing molecular systems that can self-replicate is currently an area of intense research interest to organic chemists and others. Although it has not proven possible at present to realize any "informational replicating systems" in the laboratory [Orgel, 1992], substantial progress has been made in developing some self-replicating molecules. Much of this work has been motivated by a desire to demonstrate the feasability of self-replicating molecular systems important in the origins of life [Oro et al, 1990; Ponnamperuma et al, 1992]. In conjunction with this experimental work, it seems reasonable to explore the feasibility of developing computational models of self-replicating systems. While a number of approaches have been taken, the most
['James A. Reggia', 'Hui-Hsien Chou', 'Steven L. Armentrout', 'Yun Peng']
Minimizing Complexity in Cellular Automata Models of Self-Replication