Self-organization can be broadly defined as the ability of a system to display ordered spatio-temporal patterns solely as the result of the interactions among the system components. Processes of this kind characterize both living and artificial systems, making self-organization a concept that is at the basis of several disciplines, from physics to biology to engineering. Placed at the frontiers between disciplines, Artificial Life (ALife) has heavily borrowed concepts and tools from the study of self-organization, providing mechanistic interpretations of life-like phenomena as well as useful constructivist approaches to artificial system design. Despite its broad usage within ALife, the concept of self-organization has been often excessively stretched or misinterpreted, calling for a clarification that could help with tracing the borders between what can and cannot be considered self-organization. In this review, we discuss the fundamental aspects of self-organization and list the main usages within three primary ALife domains, namely "soft" (mathematical/computational modeling), "hard" (physical robots), and "wet" (chemical/biological systems) ALife. Finally, we discuss the usefulness of self-organization within ALife studies, point to perspectives for future research, and list open questions.
Chalmer's famously identified pinpointing an explanation for our subjective experience as the "hard problem of consciousness". He argued that subjective experience constitutes a "hard problem" in the sense that its explanation will ultimately require new physical laws or principles. Here, we propose a corresponding "hard problem of life" as the problem of how `information' can affect the world. In this essay we motivate both why the problem of information as a causal agent is central to explaining life, and why it is hard - that is, why we suspect that a full resolution of the hard problem of life will, similar to as has been proposed for the hard problem of consciousness, ultimately not be reducible to known physical principles.
Comments: To appear in "From Matter to Life: Information and Causality". S.I. Walker, P.C.W. Davies and G.F.R. Ellis (eds). Cambridge University Press