Autopoiesis Concepts for Chemical Origins of Life and Synthetic Biology [Stenogram of the popular lecture on the foreign bibliographic seminar]

The monograph (Luisi P.L. "The Emergence of Life: From Chemical Origins to Synthetic Biology", 2010, Cambridge University Press, Cambridge, New York etc., 315 p.) is a well-written, informative book providing a novel view on the interrelation between the abiogenesis as the natural origin of life and synthetic biology as the artificial synthesis of life. This concept is specially known as autopoiesis. As its name implies, it is a correlate of self-organization, but this word has quite a broad meaning in the literature. Consequently, some further restriction is required for this term in abiogenetic, as well as in "biogenetic" applications. There is, in fact, one basic reason for considering the abiogenetic problem in terms of self-organization theory. It follows from the extremely boundless complexity of biological systems

The Past, Present, and Future of Artificial Life

For millennia people have wondered what makes the living different from the non-living. Beginning in the mid-1980s, artificial life has studied living systems using a synthetic approach: build life in order to understand it better, be it by means of software, hardware, or wetware. This review provides a summary of the advances that led to the development of artificial life, its current research topics, and open problems and opportunities. We classify artificial life research into fourteen themes: origins of life, autonomy, self-organization, adaptation (including evolution, development, and learning), ecology, artificial societies, behavior, computational biology, artificial chemistries, information, living technology, art, and philosophy. Being interdisciplinary, artificial life seems to be losing its boundaries and merging with other fields

Cognition as Embodied Morphological Computation

Cognitive science is considered to be the study of mind (consciousness and thought) and intelligence in humans. Under such definition variety of unsolved/unsolvable problems appear. This article argues for a broad understanding of cognition based on empirical results from i.a. natural sciences, self-organization, artificial intelligence and artificial life, network science and neuroscience, that apart from the high level mental activities in humans, includes sub-symbolic and sub-conscious processes, such as emotions, recognizes cognition in other living beings as well as extended and distributed/social cognition. The new idea of cognition as complex multiscale phenomenon evolved in living organisms based on bodily structures that process information, linking cognitivists and EEEE (embodied, embedded, enactive, extended) cognition approaches with the idea of morphological computation (info-computational self-organisation) in cognizing agents, emerging in evolution through interactions of a (living/cognizing) agent with the environment

Emergence and criticality in spatiotemporal synchronization: the complementarity model

This work concerns the long-term dynamics of a spatiotemporal many-body deterministic model that exhibits emergence and self-organization, and which has been recently proposed as a new paradigm for Artificial Life. Collective structures emerge in the form of dynamic networks, created by bursts of spatiotemporal activity (avalanches) at the edge of a synchronization phase transition. The spatiotemporal dynamics is portraited by a motion picture and quantified by time varying collective parameters, which revealed that the dynamic networks undergo a "life cycle", made of self-creation, self-regulation, and self-destruction. The power spectra of the collective parameters show 1/f power-law tails, and the statistical properties of the avalanches, evaluated in terms of their size and durations, show power laws with characteristic exponents in agreement with those values found in the literature concerning neural networks. The mechanism underlying avalanches is discussed in terms of local-to-collective excitability. Finally, the connections that link the present work to self-organized criticality, neural networks and artificial life are discussed

Aqueous Self-Sorting in Extended Supramolecular Aggregates

Self-organization and self-sorting processes are responsible for the regulation and control of the vast majority of biological processes that eventually sustain life on our planet. Attempts to unveil the complexity of these systems have been devoted to the investigation of the binding processes between artificial molecules, complexes or aggregates within multicomponent mixtures, which has facilitated the emergence of the field of self-sorting in the last decade. Since, artificial systems involving discrete supramolecular structures, extended supramolecular aggregates or gel-phase materials in organic solvents or—to a lesser extent—in water have been investigated. In this review, we have collected diverse strategies employed in recent years to construct extended supramolecular aggregates in water upon self-sorting of small synthetic molecules. We have made particular emphasis on co-assembly processes in binary mixtures leading to supramolecular structures of remarkable complexity and the influence of different external variables such as solvent and concentration to direct recognition or discrimination processes between these species. The comprehension of such recognition phenomena will be crucial for the organization and evolution of complex matter