Nature's spectacular inventiveness, reflected in the enormous diversity of form and function displayed by the biosphere, is a feature of life that distinguishes living most strongly from nonliving . It is, therefore, not surprising that this aspect of life should become a central focus of artificial life. We have known since Darwin that the diversity is produced dynamically, through the process of evolution; this has led life's creative productivity to be called Open-Ended Evolution (OEE) in the field. This article introduces the second of two special issues on current research in OEE and provides an overview of the contents of both special issues. Most of the work was presented at a workshop on open-ended evolution that was held as a part of the 2018 Conference on Artificial Life in Tokyo, and much of it had antecedents in two previous workshops on open-ended evolution at artificial life conferences in Cancun and York. We present a simplified categorization of OEE and summarize progress in the field as represented by the articles in this special issue.

We document and discuss two different modes of evolution across multiple systems, optimization and expansion . The former suffices in systems whose size and interactions do not change substantially over time, while the latter is a key property of open-ended evolution, where new players and interaction types enter the game. We first investigate systems from physics, biology, and engineering and argue that their evolutionary optimization dynamics is the cumulative effect of multiple independent events, or quakes , which are uniformly distributed on a logarithmic time scale and produce a decelerating fitness improvement when using the appropriate independent variable. The appropriate independent variable can be physical time for a disordered magnetic system, the number of generations for a bacterial system, or the number of produced units for a particular technological product. We then derive and discuss a simple microscopic theory that explains the nature of the involved optimization processes, and provide simulation results as illustration. Finally, we explore the evolution of human culture and technology, using empirical economic data as a proxy for human fitness. Assuming the overall dynamics is a combined optimization and expansion process, the two processes can be separated and quantified by superimposing the mathematical form of an optimization process on the empirical data and thereby transforming the independent variable. This variable turns out to increase faster than any exponential function of time, a property likely due to strong historical changes in the web of human interactions and to the associated increase in the amount of available knowledge. A microscopic theory for this time dependence remains, however, a challenging open problem.

Nature's spectacular inventiveness, reflected in the enormous diversity of form and function displayed by the biosphere, is a feature of life that distinguishes living most strongly from nonliving . It is, therefore, not surprising that this aspect of life should become a central focus of artificial life. We have known since Darwin that the diversity is produced dynamically, through the process of evolution; this has led life's creative productivity to be called Open-Ended Evolution (OEE) in the field. This article introduces the first of two special issues on current research on OEE and on the more general concept of open-endedness. Most of the papers presented in these special issues are elaborations of work presented at the Third Workshop on Open-Ended Evolution, held in Tokyo as part of the 2018 Conference on Artificial Life.

We summarize the results and perspectives from a companion article, where we presented and evaluated an alternative architecture for data storage in distributed networks. We name the bio-inspired architecture RAIN, and it offers file storage service that, in contrast with current centralized cloud storage, has privacy by design, is open source, is more secure, is scalable, is more sustainable, has community ownership, is inexpensive, and is potentially faster, more efficient, and more reliable. We propose that a RAIN-style architecture could form the backbone of the Internet of Things that likely will integrate multiple current and future infrastructures ranging from online services and cryptocurrency to parts of government administration.

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 .

The concept of living technology—that is, technology that is based on the powerful core features of life—is explained and illustrated with examples from artificial life software, reconfigurable and evolvable hardware, autonomously self-reproducing robots, chemical protocells, and hybrid electronic-chemical systems. We define primary (secondary) living technology according as key material components and core systems are not (are) derived from living organisms. Primary living technology is currently emerging, distinctive, and potentially powerful, motivating this review. We trace living technology's connections with artificial life (soft, hard, and wet), synthetic biology (top-down and bottom-up), and the convergence of nano-, bio-, information, and cognitive (NBIC) technologies. We end with a brief look at the social and ethical questions generated by the prospect of living technology.

A key requirement of an autonomous self-replicating molecular machine, a protocell, is the ability to digest resources and turn them into building blocks. Thus a protocell needs a set of metabolic processes fueled by external free energy in the form of available chemical redox potential or light. We introduce and investigate a minimal photodriven metabolic system, which is based on photofragmentation of resource molecules catalyzed by genetic molecules. We represent and analyze the full metabolic set of reaction-kinetic equations and, through a set of approximations, simplify the reaction kinetics so that analytical expressions can be obtained for the building block production. The analytical approximations are compared with the full equation set and with corresponding experimental results to the extent they are available. It should be noted, however, that the proposed metabolic system has not been experimentally implemented, so this investigation is conducted to obtain a deeper understanding of its dynamics and perhaps to anticipate its limitations. We demonstrate that this type of minimal photodriven metabolic scheme is typically rate-limited by the front-end photoexcitation process, while its yield is determined by the genetic catalysis. We further predict that gene-catalyzed metabolic reactions can undergo evolutionary selection only for certain combinations of the involved reaction rates due to their intricate interactions. We finally discuss how the expected range of metabolic rates likely affects other key protocellular processes such as container growth and division as well as gene replication.

Cross-reactions and other systematic difficulties generated by the coupling of functional chemical subsystems pose the largest challenge for assembling a viable protocell in the laboratory. Our current work seeks to identify and clarify such key issues as we represent and analyze in simulation a full implementation of a minimal protocell. Using a 3D dissipative particle dynamics simulation method, we are able to address the coupled diffusion, self-assembly, and chemical reaction processes required to model a full life cycle of a protocell composed of coupled genetic, metabolic, and container subsystems. Utilizing this minimal structural and functional representation of the constituent molecules, their interactions, and their reactions, we identify and explore the nature of the many linked processes for the full protocellular system. Obviously the simplicity of this simulation method combined with the inherent system complexity prevents us from expecting quantitative simulation predictions from these investigations. However, we report important findings on systemic processes, some previously predicted and some newly discovered, as we couple the protocellular self-assembly processes and chemical reactions.

Assembling non-biological materials (geomaterials) into a proto-organism constitutes a bridge between nonliving and living matter. In this article we present a simple step-by-step route to assemble a proto-organism. Many pictures have been proposed to describe this transition within the origins-of-life and artificial life communities, and more recently alternative pictures have been emerging from advances in nanoscience and biotechnology. The proposed proto-organism lends itself to both traditions and defines a new picture based on a simple idea: Given a set of required functionalities, minimize the physicochemical structures that support these functionalities, and make sure that all structures self-assemble and mutually enhance each other's existence. The result is the first concrete, rational design of a simple physicochemical system that integrates the key functionalities in a thermodynamically favorable manner as a lipid aggregate integrates proto-genes and a proto-metabolism. Under external pumping of free energy, the metabolic processes produce the required building blocks, and only specific gene sequences enhance the metabolic kinetics sufficiently for the whole system to survive. We propose an experimental implementation of the proto-organism with a discussion of our experimental results, together with relevant results produced by other experimental groups, and we specify what is still missing experimentally. Identifying the missing steps is just as important as providing the road map for the transition. We derive the kinetic and thermodynamic conditions of each of the proto-organism subsystems together with relevant theoretical and computational results about these subsystems. We present and discuss detailed 3D simulations of the lipid aggregation processes. From the reaction kinetics we derive analytical aggregate size distributions, and derive key properties of the metabolic efficiency and stability. Thermodynamics and kinetics of the ligation directed self-replication of the proto-genes is discussed, and we summarize the full life cycle of the proto-organism by comparing size, replication time, and energy with the biomass efficiency of contemporary unicells. Finally, we also compare our proto-organism picture with existing origins-of-life and protocell pictures. By assembling one possible bridge between nonliving and living matter we hope to provide a piece in the ancient puzzle about who we are and where we come from.

We describe a novel Internet-based method for building consensus and clarifying conflicts in large stakeholder groups facing complex issues, and we use the method to survey and map the scientific and organizational perspectives of the artificial life community during the Seventh International Conference on Artificial Life (summer 2000). The issues addressed in this survey included artificial life's main successes, main failures, main open scientific questions, and main strategies for the future, as well as the benefits and pitfalls of creating a professional society for artificial life. By illuminating the artificial life community's collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups.

Complex, robust functionalities can be generated naturally in at least two ways: by the assembly of structures and by the evolution of structures. This work is concerned with spontaneous formation of structures. We define the notion of dynamical hierarchies in natural systems and show the importance of this particular kind of organization for living systems. We then define a framework that enables us to formulate, investigate, and manipulate such dynamical hierarchies. This framework allows us to simultaneously investigate different levels of description together with their interrelationship, which is necessary to understand the nature of dynamical hierarchies. Our framework is then applied to a concrete and very simple formal, physicochemical, dynamical hierarchy involving water and monomers at level one, polymers and water at level two, and micelles (polymer aggregates) and water at level three. Formulating this system as a simple two-dimensional molecular dynamics (MD) lattice gas allows us within one dynamical system to demonstrate the successive emergence of two higher levels (three levels all together) of robust structures with associated properties. Second, we demonstrate how the framework for dynamical hierarchies can be used for realistic (predictive) physicochemical simulation of molecular self-assembly and self-organization processes. We discuss the detailed process of micellation using the three-dimensional MD lattice gas. Finally, from these examples we can infer principles about formal dynamical hierarchies. We present an ansatz for how to generate robust, higher-order emergent properties in formal dynamical systems that is based on a conjecture of a necessary minimal complexity within the fundamental interacting structures once a particular simulation framework is chosen.

Gross and McMullin [ Artificial Life, 7 , 355–365] criticize the conclusions of our article on dynamical hierarchies [ Artificial Life, 7 , 329–353]. In this note we respond to their criticisms. After clarifying our ansatz , we argue that the simulations presented by Gross and McMullin present no evidence against the ansatz , in part because their simulations use a different simulation framework, and in part because their simulations are no less complex than ours. We also clarify why the micelles in our simulations are third-order emergent structures, and why we emphasize realism in our simulation.

This article lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated.