Behaviour and the Origin of Organisms.

It is common in origins of life research to view the first stages of life as the passive result of particular environmental conditions. This paper considers the alternative possibility: that the antecedents of life were already actively regulating their environment to maintain the conditions necessary for their own persistence. In support of this proposal, we describe 'viability-based behaviour': a way that simple entities can adaptively regulate their environment in response to their health, and in so doing, increase the likelihood of their survival. Drawing on empirical investigations of simple self-preserving abiological systems, we argue that these viability-based behaviours are simple enough to precede neo-Darwinian evolution. We also explain how their operation can reduce the demanding requirements that mainstream theories place upon the environment(s) in which life emerged.

Embracing sensorimotor history: Time-synchronous and time-unrolled Markov blankets in the free-energy principle.

The free-energy principle (FEP) builds on an assumption that sensor-motor loops exhibit Markov blankets in stationary state. We argue that there is rarely reason to assume a system's internal and external states are conditionally independent given the sensorimotor states, and often reason to assume otherwise. However, under mild assumptions internal and external states are conditionally independent given the sensorimotor history.

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.

On the Potential for Open-Endedness in Neural Networks.

Natural evolution gives the impression of leading to an open-ended process of increasing diversity and complexity. If our goal is to produce such open-endedness artificially, this suggests an approach driven by evolutionary metaphor. On the other hand, techniques from machine learning and artificial intelligence are often considered too narrow to provide the sort of exploratory dynamics associated with evolution. In this article, we hope to bridge that gap by reviewing common barriers to open-endedness in the evolution-inspired approach and how they are dealt with in the evolutionary case-collapse of diversity, saturation of complexity, and failure to form new kinds of individuality. We then show how these problems map onto similar ones in the machine learning approach, and discuss how the same insights and solutions that alleviated those barriers in evolutionary approaches can be ported over. At the same time, the form these issues take in the machine learning formulation suggests new ways to analyze and resolve barriers to open-endedness. Ultimately, we hope to inspire researchers to be able to interchangeably use evolutionary and gradient-descent-based machine learning methods to approach the design and creation of open-ended systems.

Horizontal transfer of code fragments between protocells can explain the origins of the genetic code without vertical descent.

Theories of the origin of the genetic code typically appeal to natural selection and/or mutation of hereditable traits to explain its regularities and error robustness, yet the present translation system presupposes high-fidelity replication. Woese's solution to this bootstrapping problem was to assume that code optimization had played a key role in reducing the effect of errors caused by the early translation system. He further conjectured that initially evolution was dominated by horizontal exchange of cellular components among loosely organized protocells ("progenotes"), rather than by vertical transmission of genes. Here we simulated such communal evolution based on horizontal transfer of code fragments, possibly involving pairs of tRNAs and their cognate aminoacyl tRNA synthetases or a precursor tRNA ribozyme capable of catalysing its own aminoacylation, by using an iterated learning model. This is the first model to confirm Woese's conjecture that regularity, optimality, and (near) universality could have emerged via horizontal interactions alone.

The Biological Foundations of Enactivism: A Report on a Workshop Held at Artificial Life XV.

This is a report on the Biological Foundations of Enactivism Workshop, which was held as part of Artificial Life XV. The workshop aimed to revisit enactivism's contributions to biology and to revitalize the discussion of autonomy with the goal of grounding it in quantitative definitions based in observable phenomena. This report summarizes some of the important issues addressed in the workshop's talks and discussions, which include how to identify emergent individuals out of an environmental background, what the roles of autonomy and normativity are in biological theory, how new autonomous agents can spontaneously emerge at the origins of life, and what science can say about subjective experience.

Bulk measurements of messy chemistries are needed for a theory of the origins of life.

A feature of many of the chemical systems plausibly involved in the origins of terrestrial life is that they are complex and messy-producing a wide range of compounds via a wide range of mechanisms. However, the fundamental behaviour of such systems is currently not well understood; we do not have the tools to make statistical predictions about such complex chemical networks. This is, in part, due to a lack of quantitative data from which such a theory could be built; specifically, functional measurements of messy chemical systems. Here, we propose that the pantheon of experimental approaches to the origins of life should be expanded to include the study of 'functional measurements'-the direct study of bulk properties of chemical systems and their interactions with other compounds, the formation of structures and other behaviours, even in cases where the precise composition and mechanisms are unknown.This article is part of the themed issue 'Reconceptualizing the origins of life'.

Open-Ended Evolution: Perspectives from the OEE Workshop in York.

We describe the content and outcomes of the First Workshop on Open-Ended Evolution: Recent Progress and Future Milestones (OEE1), held during the ECAL 2015 conference at the University of York, UK, in July 2015. We briefly summarize the content of the workshop's talks, and identify the main themes that emerged from the open discussions. Two important conclusions from the discussions are: (1) the idea of pluralism about OEE-it seems clear that there is more than one interesting and important kind of OEE; and (2) the importance of distinguishing observable behavioral hallmarks of systems undergoing OEE from hypothesized underlying mechanisms that explain why a system exhibits those hallmarks. We summarize the different hallmarks and mechanisms discussed during the workshop, and list the specific systems that were highlighted with respect to particular hallmarks and mechanisms. We conclude by identifying some of the most important open research questions about OEE that are apparent in light of the discussions. The York workshop provides a foundation for a follow-up OEE2 workshop taking place at the ALIFE XV conference in Cancún, Mexico, in July 2016. Additional materials from the York workshop, including talk abstracts, presentation slides, and videos of each talk, are available at http://alife.org/ws/oee1 .

Complex Autocatalysis in Simple Chemistries.

Life on Earth must originally have arisen from abiotic chemistry. Since the details of this chemistry are unknown, we wish to understand, in general, which types of chemistry can lead to complex, lifelike behavior. Here we show that even very simple chemistries in the thermodynamically reversible regime can self-organize to form complex autocatalytic cycles, with the catalytic effects emerging from the network structure. We demonstrate this with a very simple but thermodynamically reasonable artificial chemistry model. By suppressing the direct reaction from reactants to products, we obtain the simplest kind of autocatalytic cycle, resulting in exponential growth. When these simple first-order cycles are prevented from forming, the system achieves superexponential growth through more complex, higher-order autocatalytic cycles. This leads to nonlinear phenomena such as oscillations and bistability, the latter of which is of particular interest regarding the origins of life.

A Strategy for Origins of Life Research.

Contents 1. Introduction 1.1. A workshop and this document 1.2. Framing origins of life science 1.2.1. What do we mean by the origins of life (OoL)? 1.2.2. Defining life 1.2.3. How should we characterize approaches to OoL science? 1.2.4. One path to life or many? 2. A Strategy for Origins of Life Research 2.1. Outcomes-key questions and investigations 2.1.1. Domain 1: Theory 2.1.2. Domain 2: Practice 2.1.3. Domain 3: Process 2.1.4. Domain 4: Future studies 2.2. EON Roadmap 2.3. Relationship to NASA Astrobiology Roadmap and Strategy documents and the European AstRoMap Appendix I Appendix II Supplementary Materials References.

Many hands make light work: further studies in group evolution.

When niching or speciation is required to perform a task that has several different component parts, standard genetic algorithms (GAs) struggle. They tend to evaluate and select all individuals on the same part of the task, which leads to genetic convergence within the population. The goal of evolutionary niching methods is to enforce diversity in the population so that this genetic convergence is avoided. One drawback with some of these niching methods is that they require a priori knowledge or assumptions about the specific fitness landscape in order to work; another is that many such methods are not set up to work on cooperative tasks where fitness is only relevant at the group level. Here we address these problems by presenting the group GA, described earlier by the authors, which is a group-based evolutionary algorithm that can lead to emergent niching. After demonstrating the group GA on an immune system matching task, we extend the previous work and present two modified versions where the number of niches does not need to be specified ahead of time. In the random-group-size GA, the number of niches is varied randomly during evolution, and in the evolved-group-size GA the number of niches is optimized by evolution. This provides a framework in which we can evolve groups of individuals to collectively perform tasks with minimal a priori knowledge of how many subtasks there are or how they should be shared out.

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.

Evolvable physical self-replicators.

Building an evolvable physical self-replicating machine is a grand challenge. The main problem is that the device must be capable of hereditary variation, that is, replicating in many configurations-configurations into which it enters unpredictably by mutation. Template replication is the solution found by nature. A scalable device must also be capable of miniaturization, and so have few or no moving and electronic parts. Here a significant step toward this goal is presented in the form of a physical template replicator made from small plastic pieces containing embedded magnets that float on an air-hockey-type table and undergo stochastic motion. Our units replicate by a process analogous to the replication of DNA, except without the involvement of enzymes. Building a physical rather than a computational model forces us to confront several problems that have analogues on the nano scale. In particular, replication must be maintained by preventing side reactions such as spontaneous ligation, cyclization, product inhibition, and elongation at staggered ends. The last of these results in ever-lengthening sequences in a process known as the elongation catastrophe. The extreme specificity of structure required by the monomers is indirect evidence that some kind of natural selection took place prior to the existence of nucleotide analogues during the origin of life.

Sequentially assembled food webs and extremum principles in ecosystem ecology.

1. Successional changes during sequential assembly of food webs were examined. This was carried out by numerical methods, drawing one species at a time from a species pool and obtaining the permanent (persistent) community emerging at each step. Interactions among species were based on some simple rules about body sizes of consumers and their prey, and community dynamics were described in terms of flows of biomass density. 2. Sequential assembly acted as a sieve on the communities, assembled communities having many properties different on average from those of feasible, stable communities taken at random from the species pools. 3. Time-series of community development were consistent with certain functions thought to go to an extremum (maximum or minimum) in ecosystem ecology, including a rapid early increase in net primary productivity and ascendency, although a clear trend in total biomass density was not evident and resilience decreased rather than increased. 4. In addition, more gradual changes in food web structure took place during succession to which the ecosystem goal functions were relatively insensitive. These changes included gradual increases in the number of species, invasion resistance, number of loops of length > 2 and number of prey species per consumer species. 5. We therefore argue that ecosystem and community dynamics can offer complementary insights into the process of ecological succession. The extremum principles of ecosystem ecology highlight some of the major properties of succession, whereas the community ecology sheds light on some more subtle changes taking place within the networks.