Abstract:In previous work I proposed a framework for thinking about open-ended evolution. The framework characterised the basic processes required for Darwinian evolution as: (1) the generation of a phenotype from a genetic description; (2) the evaluation of that phenotype; and (3) the reproduction with variation of successful genotype-phenotypes. My treatment emphasized the potential influence of the biotic and abiotic environment, and of the laws of physics/chemistry, on each of these processes. I demonstrated the conditions under which these processes can allow for ongoing exploration of a space of possible phenotypes (which I labelled exploratory open-endedness). However, these processes by themselves cannot expand the space of possible phenotypes and therefore cannot account for the more interesting and unexpected kinds of evolutionary innovation (such as those I labelled expansive and transformational open-endedness). In the previous work I looked at ways in which expansive and transformational innovations could arise. I proposed transdomain bridges and non-additive compositional systems as two mechanisms by which these kinds of innovations could arise. In the current paper I wish to generalise and expand upon these two concepts. I do this by adopting the Parameter Space-Organisation Space-Action Space (POA) perspective, as suggested at in my previous work, and proposing that all evolutionary innovations can be viewed as either capturing some novel physical phenomena that had previously been unused, or as the creation of new persistent systems within the environment.
Abstract:A paper in the recent Artificial Life journal special issue on open-ended evolution (OEE) presents a simple evolving computational system that, it is claimed, satisfies all proposed requirements for OEE (Hintze, 2019). Analysis and discussion of the system are used to support the further claims that complexity and diversity are the crucial features of open-endedness, and that we should concentrate on providing proper definitions for those terms rather than engaging in "the quest for open-endedness for the sake of open-endedness" (Hintze, 2019, p. 205). While I wholeheartedly support the pursuit of precise definitions of complexity and diversity in relation to OEE research, I emphatically reject the suggestion that OEE is not a worthy research topic in its own right. In the same issue of the journal, I presented a "high-level conceptual framework to help orient the discussion and implementation of open-endedness in evolutionary systems" (Taylor, 2019). In the current brief contribution I apply my framework to Hinzte's model to understand its limitations. In so doing, I demonstrate the importance of studying open-endedness for the sake of open-endedness.
Abstract: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.
Abstract:This paper presents a high-level conceptual framework to help orient the discussion and implementation of open-endedness in evolutionary systems. Drawing upon work by Banzhaf et al., three different kinds of open-endedness are identified: exploratory, expansive, and transformational. These are characterised in terms of their relationship to the search space of phenotypic behaviours. A formalism is introduced to describe three key processes required for an evolutionary process: the generation of a phenotype from a genetic description, the evaluation of that phenotype, and the reproduction with variation of individuals according to their evaluation. The formalism makes explicit various influences in each of these processes that can easily be overlooked. The distinction is made between intrinsic and extrinsic implementations of these processes. A discussion then investigates how various interactions between these processes, and their modes of implementation, can lead to open-endedness. However, it is demonstrated that these considerations relate to exploratory open-endedness only. Conditions for the implementation of the more interesting kinds of open-endedness - expansive and transformational - are also discussed, emphasizing factors such as multiple domains of behaviour, transdomain bridges, and non-additive compositional systems. In contrast to a traditional population genetics analysis, these factors relate not to the generic evolutionary properties of individuals and populations, but rather to the nature of the building blocks out of which individual organisms are constructed, and the laws and properties of the environment in which they exist. The paper ends with suggestions of how the framework can be used to categorise and compare the open-ended evolutionary potential of different systems, and how it might guide the design of systems with greater capacity for open-ended evolution.
Abstract:The influence of Artificial Intelligence (AI) and Artificial Life (ALife) technologies upon society, and their potential to fundamentally shape the future evolution of humankind, are topics very much at the forefront of current scientific, governmental and public debate. While these might seem like very modern concerns, they have a long history that is often disregarded in contemporary discourse. Insofar as current debates do acknowledge the history of these ideas, they rarely look back further than the origin of the modern digital computer age in the 1940s-50s. In this paper we explore the earlier history of these concepts. We focus in particular on the idea of self-reproducing and evolving machines, and potential implications for our own species. We show that discussion of these topics arose in the 1860s, within a decade of the publication of Darwin's The Origin of Species, and attracted increasing interest from scientists, novelists and the general public in the early 1900s. After introducing the relevant work from this period, we categorise the various visions presented by these authors of the future implications of evolving machines for humanity. We suggest that current debates on the co-evolution of society and technology can be enriched by a proper appreciation of the long history of the ideas involved.
Abstract:This chapter discusses the possibility of instilling a virtual world with mechanisms for evolution and natural selection in order to generate rich ecosystems of complex organisms in a process akin to biological evolution. Some previous work in the area is described, and successes and failures are discussed. The components of a more comprehensive framework for designing such worlds are mapped out, including the design of the individual organisms, the properties and dynamics of the environmental medium in which they are evolving, and the representational relationship between organism and environment. Some of the key issues discussed include how to allow organisms to evolve new structures and functions with few restrictions, and how to create an interconnectedness between organisms in order to generate drives for continuing evolutionary activity.
Abstract:The application of evolution in the digital realm, with the goal of creating artificial intelligence and artificial life, has a history as long as that of the digital computer itself. We illustrate the intertwined history of these ideas, starting with the early theoretical work of John von Neumann and the pioneering experimental work of Nils Aall Barricelli. We argue that evolutionary thinking and artificial life will continue to play an integral role in the future development of the digital world.
Abstract:Open-ended evolutionary dynamics remains an elusive goal for artificial evolutionary systems. Many ideas exist in the biological literature beyond the basic Darwinian requirements of variation, differential reproduction and inheritance. I argue that these ideas can be seen as aspects of five fundamental requirements for open-ended evolution: (1) robustly reproductive individuals, (2) a medium allowing the possible existence of a practically unlimited diversity of individuals and interactions, (3) individuals capable of producing more complex offspring, (4) mutational pathways to other viable individuals, and (5) drive for continued evolution. I briefly discuss implications of this view for the design of artificial systems with greater evolutionary potential.
Abstract:Proceedings of WebAL-1: Workshop on Artificial Life and the Web 2014, held at the 14th International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14), New York, NY, 31 July 2014.
Abstract:A brief survey is presented of the first 18 years of web-based Artificial Life ("WebAL") research and applications, covering the period 1995-2013. The survey is followed by a short discussion of common methodologies employed and current technologies relevant to WebAL research. The paper concludes with a quick look at what the future may hold for work in this exciting area.