Thirty years of computational autopoiesis: a review

Aggregate Boid behavior to aid in artificial autopoietic organization

Analyzing carbon-based life on earth can lead to biased inferences on the nature of life as might exist in elsewhere in the universe in alternative forms, therefore, scientists have looked into either abstracting life into constituent systems it is comprised of, or logics of life, or lists of essential criteria, or essential dynamic patterning that characterizes the living. A system-level characterization that is and referred to as a general pattern of minimal life is autopoiesis (Varela et al., 1974) including production, maintenance and replacement of required constituents for setting up and maintaining an internal environment with self/other separation that regulates and is constitutive of processes that produce the environment and components for processes that comprise this ongoing activity of self-production in 'recursively', i.e., in a manner that allows the organizational pattern to continually reconstitute the conditions, components and processes required for its own perpetuation. This seminal concept of an autopoiesis is instantiated in life as we know it, but might also be instantiated in different media and in unforeseen ways. Other researchers have argued life is more than autopoiesis and that it is a co-emergent property of autopoiesis and cognition. Life produces many emergent properties such as synchronization and patterns as seen in flocks and herds of different animal species. The mechanics of this synchrony displayed in flocks and herd animals has been extracted by Craig Reynolds into a generative model referred to as "Boids". With these concepts in mind, we address the following research question: How can the synchronous maneuvers and aggregate behavior of Boids contribute to constitutive subsystems in realizing an autopoietic system? Can such a system exhibit minimal cognition? This work attempts to answer these questions with a bottom-up approach to constructing an artificial life system. We exhibit a computational model of autopoiesis and a minimal level of cognition in the sense of M. Bitbol and P. Luigi Luisi, whereby an autopoietic entity engages in active assimilation of external components as part of its activity of self-production.

Autocatalysis, Autopoiesis, and the Opportunity Cost of Individuality

Ever since Varela and Maturana proposed the concept of autopoiesis as the minimal requirement for life, there has been a focus on cellular systems that erect topological boundaries to separate themselves from their surrounding environment. Here, we reconsider whether the existence of such a spatial boundary is strictly necessary for self-producing entities. This work presents a novel computational model of a minimal autopoietic system inspired by dendrites and molecular dynamic simulations in three-dimensional space. A series of simulation experiments where the metabolic pathways of a particular autocatalytic set are successively inhibited until autocatalytic entities that could be considered autopoietic are produced. These entities maintain their distinctness in an environment containing multiple identical instances of the entities without the existence of a topological boundary. This gives rise to the concept of a metabolic boundary which manifests as emergent self-selection criteria for the processes of self-production without any need for unique identifiers. However, the adoption of such a boundary comes at a cost, as these autopoietic entities are less suited to their simulated environment than their autocatalytic counterparts. Finally, this work showcases a generalized metabolism-centered approach to the study of autopoiesis that can be applied to both physical and abstract systems alike.

The theoretical foundations of enaction: Precariousness

Enaction is an increasingly influential approach to cognition that grew out of Maturana and Varela's earlier work on autopoiesis and the biology of cognition. As with any relatively new scientific discipline, the enactive approach would benefit greatly from a careful analysis of its theoretical foundations. Here we initiate such an analysis for one of the core concepts of enaction, precariousness. Specifically, we consider three types of fragility: systemic, processual and thermodynamic. Using a glider in the Game of Life as a toy model, we illustrate each of these fragilities and examine the relationships between them. We also argue that each type of fragility is characterized by which aspects of a system are hardwired into its definition from the outset and which aspects are emergent and hence vulnerable to disintegration without ongoing maintenance.

Evolution of Autopoiesis and Multicellularity in the Game of Life

Recently we introduced a model of symbiosis, Model-S, based on the evolution of seed patterns in Conway's Game of Life. In the model, the fitness of a seed pattern is measured by one-on-one competitions in the Immigration Game, a two-player variation of the Game of Life. Our previous article showed that Model-S can serve as a highly abstract, simplified model of biological life: (1) The initial seed pattern is analogous to a genome. (2) The changes as the game runs are analogous to the development of the phenome. (3) Tournament selection in Model-S is analogous to natural selection in biology. (4) The Immigration Game in Model-S is analogous to competition in biology. (5) The first three layers in Model-S are analogous to biological reproduction. (6) The fusion of seed patterns in Model-S is analogous to symbiosis. The current article takes this analogy two steps further: (7) Autopoietic structures in the Game of Life (still lifes, oscillators, and spaceships-collectively known as ashes) are analogous to cells in biology. (8) The seed patterns in the Game of Life give rise to multiple, diverse, cooperating autopoietic structures, analogous to multicellular biological life. We use the apgsearch software (Ash Pattern Generator Search), developed by Adam Goucher for the study of ashes, to analyze autopoiesis and multicellularity in Model-S. We find that the fitness of evolved seed patterns in Model-S is highly correlated with the diversity and quantity of multicellular autopoietic structures.

Self-Reproduction and Darwinian Evolution in Autocatalytic Chemical Reaction Systems

Understanding the emergence of life from (primitive) abiotic components has arguably been one of the deepest and yet one of the most elusive scientific questions. Notwithstanding the lack of a clear definition for a living system, it is widely argued that heredity (involving self-reproduction) along with compartmentalization and metabolism are key features that contrast living systems from their non-living counterparts. A minimal living system may be viewed as "a self-sustaining chemical system capable of Darwinian evolution". It has been proposed that autocatalytic sets of chemical reactions (ACSs) could serve as a mechanism to establish chemical compositional identity, heritable self-reproduction, and evolution in a minimal chemical system. Following years of theoretical work, autocatalytic chemical systems have been constructed experimentally using a wide variety of substrates, and most studies, thus far, have focused on the demonstration of chemical self-reproduction under specific conditions. While several recent experimental studies have raised the possibility of carrying out some aspects of experimental evolution using autocatalytic reaction networks, there remain many open challenges. In this review, we start by evaluating theoretical studies of ACSs specifically with a view to establish the conditions required for such chemical systems to exhibit self-reproduction and Darwinian evolution. Then, we follow with an extensive overview of experimental ACS systems and use the theoretically established conditions to critically evaluate these empirical systems for their potential to exhibit Darwinian evolution. We identify various technical and conceptual challenges limiting experimental progress and, finally, conclude with some remarks about open questions.

Beyond planetary-scale feedback self-regulation: Gaia as an autopoietic system

The Gaia hypothesis states that the Earth is an instance of life. However, appraisals of it tend to focus on the claim that life is a feedback self-regulator that controls Earth's chemistry and climate dynamics, yet, self-regulation by feedbacks is not a definitive characteristic of living systems. Here, we consider the characterization of biological systems as autopoietic systems (causally organized to self-produce through metabolic efficient closure) and then ask whether the Gaia hypothesis is a tractable question from this standpoint. A proof-of-concept based on Chemical Organization Theory (COT) and the Zero Deficiency Theorem (ZDT) applied on a simple but representative Earth's molecular reaction network supports the thesis of Gaia as an autopoietic system. We identify the formation of self-producing organizations within the reaction network, corresponding to recognizable scenarios of Earth's history. These results provide further opportunities to discuss how the instantiation of autopoiesis at the planetary scale could manifests central features of biological phenomenon, such as autonomy and anticipation, and what this implies for the further development of the Gaia theory, Earth's climate modelling and geoengineering.

Hidden Concepts in the History and Philosophy of Origins-of-Life Studies: a Workshop Report

In this review, we describe some of the central philosophical issues facing origins-of-life research and provide a targeted history of the developments that have led to the multidisciplinary field of origins-of-life studies. We outline these issues and developments to guide researchers and students from all fields. With respect to philosophy, we provide brief summaries of debates with respect to (1) definitions (or theories) of life, what life is and how research should be conducted in the absence of an accepted theory of life, (2) the distinctions between synthetic, historical, and universal projects in origins-of-life studies, issues with strategies for inferring the origins of life, such as (3) the nature of the first living entities (the "bottom up" approach) and (4) how to infer the nature of the last universal common ancestor (the "top down" approach), and (5) the status of origins of life as a science. Each of these debates influences the others. Although there are clusters of researchers that agree on some answers to these issues, each of these debates is still open. With respect to history, we outline several independent paths that have led to some of the approaches now prevalent in origins-of-life studies. These include one path from early views of life through the scientific revolutions brought about by Linnaeus (von Linn.), Wöhler, Miller, and others. In this approach, new theories, tools, and evidence guide new thoughts about the nature of life and its origin. We also describe another family of paths motivated by a" circularity" approach to life, which is guided by such thinkers as Maturana & Varela, Gánti, Rosen, and others. These views echo ideas developed by Kant and Aristotle, though they do so using modern science in ways that produce exciting avenues of investigation. By exploring the history of these ideas, we can see how many of the issues that currently interest us have been guided by the contexts in which the ideas were developed. The disciplinary backgrounds of each of these scholars has influenced the questions they sought to answer, the experiments they envisioned, and the kinds of data they collected. We conclude by encouraging scientists and scholars in the humanities and social sciences to explore ways in which they can interact to provide a deeper understanding of the conceptual assumptions, structure, and history of origins-of-life research. This may be useful to help frame future research agendas and bring awareness to the multifaceted issues facing this challenging scientific question.

The Problem of Meaning in AI and Robotics: Still with Us after All These Years

In this essay we critically evaluate the progress that has been made in solving the problem of meaning in artificial intelligence (AI) and robotics. We remain skeptical about solutions based on deep neural networks and cognitive robotics, which in our opinion do not fundamentally address the problem. We agree with the enactive approach to cognitive science that things appear as intrinsically meaningful for living beings because of their precarious existence as adaptive autopoietic individuals. But this approach inherits the problem of failing to account for how meaning as such could make a difference for an agent’s behavior. In a nutshell, if life and mind are identified with physically deterministic phenomena, then there is no conceptual room for meaning to play a role in its own right. We argue that this impotence of meaning can be addressed by revising the concept of nature such that the macroscopic scale of the living can be characterized by physical indeterminacy. We consider the implications of this revision of the mind-body relationship for synthetic approaches.

Is Research on "Synthetic Cells" Moving to the Next Level?

"Synthetic cells" research focuses on the construction of cell-like models by using solute-filled artificial microcompartments with a biomimetic structure. In recent years this bottom-up synthetic biology area has considerably progressed, and the field is currently experiencing a rapid expansion. Here we summarize some technical and theoretical aspects of synthetic cells based on gene expression and other enzymatic reactions inside liposomes, and comment on the most recent trends. Such a tour will be an occasion for asking whether times are ripe for a sort of qualitative jump toward novel SC prototypes: is research on "synthetic cells" moving to a next level?

Exploring the Space of Viable Configurations in a Model of Metabolism-Boundary Co-construction

We introduce a spatial model of concentration dynamics that supports the emergence of spatiotemporal inhomogeneities that engage in metabolism-boundary co-construction. These configurations exhibit disintegration following some perturbations, and self-repair in response to others. We define robustness as a viable configuration's tendency to return to its prior configuration in response to perturbations, and plasticity as a viable configuration's tendency to change to other viable configurations. These properties are demonstrated and quantified in the model, allowing us to map a space of viable configurations and their possible transitions. Combining robustness and plasticity provides a measure of viability as the average expected survival time under ongoing perturbation, and allows us to measure how viability is affected as the configuration undergoes transitions. The framework introduced here is independent of the specific model we used, and is applicable for quantifying robustness, plasticity, and viability in any computational model of artificial life that demonstrates the conditions for viability that we promote.

Biological organisation as closure of constraints

We propose a conceptual and formal characterisation of biological organisation as a closure of constraints. We first establish a distinction between two causal regimes at work in biological systems: processes, which refer to the whole set of changes occurring in non-equilibrium open thermodynamic conditions; and constraints, those entities which, while acting upon the processes, exhibit some form of conservation (symmetry) at the relevant time scales. We then argue that, in biological systems, constraints realise closure, i.e. mutual dependence such that they both depend on and contribute to maintaining each other. With this characterisation in hand, we discuss how organisational closure can provide an operational tool for marking the boundaries between interacting biological systems. We conclude by focusing on the original conception of the relationship between stability and variation which emerges from this framework.

Characterizing autopoiesis in the game of life

Maturana and Varela's concept of autopoiesis defines the essential organization of living systems and serves as a foundation for their biology of cognition and the enactive approach to cognitive science. As an initial step toward a more formal analysis of autopoiesis, this article investigates its application to the compact, recurrent spatiotemporal patterns that arise in Conway's Game-of-Life cellular automaton. In particular, we demonstrate how such entities can be formulated as self-constructing networks of interdependent processes that maintain their own boundaries. We then characterize the specific organizations of several such entities, suggest a way to simplify the descriptions of these organizations, and briefly consider the transformation of such organizations over time.

The cognitive domain of a glider in the game of life

This article examines in some technical detail the application of Maturana and Varela's biology of cognition to a simple concrete model: a glider in the game of Life cellular automaton. By adopting an autopoietic perspective on a glider, the set of possible perturbations to it can be divided into destructive and nondestructive subsets. From a glider's reaction to each nondestructive perturbation, its cognitive domain is then mapped. In addition, the structure of a glider's possible knowledge of its immediate environment, and the way in which that knowledge is grounded in its constitution, are fully described. The notion of structural coupling is then explored by characterizing the paths of mutual perturbation that a glider and its environment can undergo. Finally, a simple example of a communicative interaction between two gliders is given. The article concludes with a discussion of the potential implications of this analysis for the enactive approach to cognition.

Rosen's (M,R) system in process algebra

Background

Robert Rosen’s Metabolism-Replacement, or (M,R), system can be represented as a compact network structure with a single source and three products derived from that source in three consecutive reactions. (M,R) has been claimed to be non-reducible to its components and algorithmically non-computable, in the sense of not being evaluable as a function by a Turing machine. If (M,R)-like structures are present in real biological networks, this suggests that many biological networks will be non-computable, with implications for those branches of systems biology that rely on in silico modelling for predictive purposes.

Results

We instantiate (M,R) using the process algebra Bio-PEPA, and discuss the extent to which our model represents a true realization of (M,R). We observe that under some starting conditions and parameter values, stable states can be achieved. Although formal demonstration of algorithmic computability remains elusive for (M,R), we discuss the extent to which our Bio-PEPA representation of (M,R) allows us to sidestep Rosen’s fundamental objections to computational systems biology.

Conclusions

We argue that the behaviour of (M,R) in Bio-PEPA shows life-like properties.

Living in living cities

This article presents an overview of current and potential applications of living technology to some urban problems. Living technology can be described as technology that exhibits the core features of living systems. These features can be useful to solve dynamic problems. In particular, urban problems concerning mobility, logistics, telecommunications, governance, safety, sustainability, and society and culture are presented, and solutions involving living technology are reviewed. A methodology for developing living technology is mentioned, and supraoptimal public transportation systems are used as a case study to illustrate the benefits of urban living technology. Finally, the usefulness of describing cities as living systems is discussed.

Motility at the origin of life: its characterization and a model

Due to recent advances in synthetic biology and artificial life, the origin of life is currently a hot topic of research. We review the literature and argue that the two traditionally competing replicator-first and metabolism-first approaches are merging into one integrated theory of individuation and evolution. We contribute to the maturation of this more inclusive approach by highlighting some problematic assumptions that still lead to an ximpoverished conception of the phenomenon of life. In particular, we argue that the new consensus has so far failed to consider the relevance of intermediate time scales. We propose that an adequate theory of life must account for the fact that all living beings are situated in at least four distinct time scales, which are typically associated with metabolism, motility, development, and evolution. In this view, self-movement, adaptive behavior, and morphological changes could have already been present at the origin of life. In order to illustrate this possibility, we analyze a minimal model of lifelike phenomena, namely, of precarious, individuated, dissipative structures that can be found in simple reaction-diffusion systems. Based on our analysis, we suggest that processes on intermediate time scales could have already been operative in prebiotic systems. They may have facilitated and constrained changes occurring in the faster- and slower-paced time scales of chemical self-individuation and evolution by natural selection, respectively.

Autopoiesis 40 years later. A review and a reformulation

The concept of autopoiesis was proposed 40 years ago as a definition of a living being, with the aim of providing a unifying concept for biology. The concept has also been extended to the theory of knowledge and to different areas of the social and behavioral sciences. Given some ambiguities of the original definitions of autopoiesis, the concept has been criticized and has been interpreted in diverse and even contradictory ways, which has prevented its integration into the biological sciences where it originated. Here I present a critical review and conceptual analysis of the definition of autopoiesis, and propose a new definition that is more precise, clear, and concise than the original ones. I argue that the difficulty in understanding the term lies in its refined conceptual subtlety and not, as has been claimed by some authors, because it is a vacuous, trivial or very complex concept. I also relate the concept of autopoiesis to the concepts of closed systems, boundaries, homeostasis, self-reproduction, causal circularity, organization and multicellularity. I show that under my proposed definition the concept of a molecular autopoietic system is a good demarcation criterion of a living being, allowing its general integration into the biological sciences and enhancing its interdisciplinary use.

From L'Homme Machine to metabolic closure: steps towards understanding life

The nature of life has been a topic of interest from the earliest of times, and efforts to explain it in mechanistic terms date at least from the 18th century. However, the impressive development of molecular biology since the 1950s has tended to have the question put on one side while biologists explore mechanisms in greater and greater detail, with the result that studies of life as such have been confined to a rather small group of researchers who have ignored one another's work almost completely, often using quite different terminology to present very similar ideas. Central among these ideas is that of closure, which implies that all of the catalysts needed for an organism to stay alive must be produced by the organism itself, relying on nothing apart from food (and hence chemical energy) from outside. The theories that embody this idea to a greater or less degree are known by a variety of names, including (M,R) systems, autopoiesis, the chemoton, the hypercycle, symbiosis, autocatalytic sets, sysers and RAF sets. These are not all the same, but they are not completely different either, and in this review we examine their similarities and differences, with the aim of working towards the formulation of a unified theory of life.

Intramolecular energy-transfer processes in a bis(porphyrin)-ruthenium(ii) bis(2,2′:6′,2″-terpyridine) molecular array

A molecular triad has been synthesized comprising two free-base porphyrin terminals linked to a central ruthenium(II) bis(2,2':6',2''-terpyridine) subunit via meso-phenylene groups. Illumination into the ruthenium(II) complex is accompanied by rapid intramolecular energy transfer from the metal-to-ligand, charge-transfer (MLCT) triplet to the lowest-energy pi-pi* triplet state localized on one of the porphyrin subunits. Transfer takes place from a vibrationally excited level which lowers the activation energy. The electronic coupling matrix element for this process is 73 cm(-1). Selective illumination into the lowest-energy singlet excited state (S1) localized on the porphyrin leads to fast singlet-triplet energy transfer that populates the MLCT triplet state with high efficiency. This latter process occurs via Dexter-type electron exchange at room temperature, but the activation energy is high and the reaction is prohibited at low temperature. For this latter process, the electronic coupling matrix element is only 8 cm(-1).