Artificial Life

Tokyo Type 1 open-ended evolution (OEE) is a category of OEE that includes systems exhibiting the ongoing generation of adaptive novelty and ongoing growth in complexity. It can be considered as a necessary foundation for Tokyo Type 2 OEE (ongoing evolution of evolvability) and Tokyo Type 3 OEE (ongoing generation of major transitions). This article brings together five methods of analysis to form a procedure for testing for Tokyo Type 1 OEE. The procedure is presented as simply as possible, isolated from the complexities of any particular evolutionary system, and with a clear rationale for each step...

This study uses evolutionary simulations to explore the strategies that emerge to enable populations to cope with random environmental changes in situations where lifetime learning approaches are not available to accommodate them. In particular, it investigates how the average magnitude of change per unit time and the persistence of the changes (and hence the resulting autocorrelation of the environmental time series) affect the change tolerances, population diversities, and extinction timescales that emerge...

Kuhnian philosophy of science implies that progress in the study of open-ended evolution (OEE) would be accelerated if the OEE science community were to agree on some examples of striking success in OEE science. This article recounts the important role of scientific paradigms and scientific exemplars in creating the productivity of what Kuhn, in The Structure of Scientific Revolutions, calls "normal" science, and it describes how the study of OEE today would benefit from exhibiting more of the hallmarks of normal science...

Gene regulatory networks are networks of interactions in organisms responsible for determining the production levels of proteins and peptides. Mathematical and computational models of gene regulatory networks have been proposed, some of them rather abstract and called artificial regulatory networks. In this contribution, a spatial model for gene regulatory networks is proposed that is biologically more realistic and incorporates an artificial chemistry to realize the interaction between regulatory proteins called the transcription factors and the regulatory sites of simulated genes...

Nowadays, interdisciplinary fields between Artificial Life, artificial intelligence, computational biology, and synthetic biology are increasingly emerging into public view. It is necessary to reconsider the relations between the material body, identity, the natural world, and the concept of life. Art is known to pave the way to exploring and conveying new possibilities. This survey provides a literature review on recent works of Artificial Life in visual art during the past 40 years, specifically in the computational and software domain...

In the mid-20th century, two new scientific disciplines emerged forcefully: molecular biology and information-communication theory. At the beginning, cross-fertilization was so deep that the term genetic code was universally accepted for describing the meaning of triplets of mRNA (codons) as amino acids. However, today, such synergy has not taken advantage of the vertiginous advances in the two disciplines and presents more challenges than answers. These challenges not only are of great theoretical relevance but also represent unavoidable milestones for next-generation biology: from personalized genetic therapy and diagnosis to Artificial Life to the production of biologically active proteins...

We survey the general trajectory of artificial intelligence (AI) over the last century, in the context of influences from Artificial Life. With a broad brush, we can divide technical approaches to solving AI problems into two camps: GOFAIstic (or computationally inspired) or cybernetic (or ALife inspired). The latter approach has enabled advances in deep learning and the astonishing AI advances we see today-bringing immense benefits but also societal risks. There is a similar divide, regrettably unrecognized, over the very way that such AI problems have been framed...

This article is an afterword to the book Rise of the Self-Replicators: Early Visions of Machines, AI and Robots That Can Reproduce and Evolve, coauthored by Tim Taylor and Alan Dorin (2020). The book covered the early history of thought about self-reproducing and evolving machines, from initial speculations in the 17th century up to the early 1960s (from which point onward the more recent history is already well covered elsewhere). This article supplements the material discussed in the book by presenting several relevant sources that have come to the author's attention since the book was published...

No abstract text is available yet for this article.

For decades, the evolution of cooperation has piqued interest in numerous academic disciplines, such as game theory, economics, biology, and computer science. In this work, we demonstrate the emergence of a novel and effective resource exchange protocol formed by dropping and picking up resources in a foraging environment. This form of cooperation is made possible by the introduction of a campfire, which adds an extended period of congregation and downtime for agents to explore otherwise unlikely interactions...

This article deals with individuals moving in procession in real and artificial societies. A procession is a minimal form of society in which individual behavior is to go in a given direction and the organization is structured by the knowledge of the one ahead. This simple form of grouping is common in the living world, and, among humans, procession is a very circumscribed social activity whose origins are certainly very remote. This type of organization falls under microsociology, where the focus is on the study of direct interactions between individuals within small groups...

A domain-independent problem-solving system based on principles of Artificial Life is introduced. In this system, DIAS, the input and output dimensions of the domain are laid out in a spatial medium. A population of actors, each seeing only part of this medium, solves problems collectively in it. The process is independent of the domain and can be implemented through different kinds of actors. Through a set of experiments on various problem domains, DIAS is shown able to solve problems with different dimensionality and complexity, to require no hyperparameter tuning for new problems, and to exhibit lifelong learning, that is, to adapt rapidly to run-time changes in the problem domain, and to do it better than a standard, noncollective approach...

This article proposes a method for an artificial agent to behave in a social manner. Although defining proper social behavior is difficult because it differs from situation to situation, the agent following the proposed method adaptively behaves appropriately in each situation by empathizing with the surrounding others. The proposed method is achieved by incorporating empathy into active inference. We evaluated the proposed method regarding control of autonomous mobile robots in diverse situations. From the evaluation results, an agent controlled by the proposed method could behave more adaptively socially than an agent controlled by the standard active inference in the diverse situations...

No abstract text is available yet for this article.

We offer three advances to the perceptual crossing simulation studies, which are aimed at challenging methodological individualism in the analysis of social cognition. First, we evolve and systematically test agents in rigorous conditions, identifying a set of 26 "robust circuits" with consistently high and generalizing performance. Next, we transform the sensor from discrete to continuous, facilitating a bifurcation analysis of the dynamics that shows that nonequilibrium dynamics are key to the mutual maintenance of interaction...

Biological agents have bodies that are composed mostly of soft tissue. Researchers have resorted to soft bodies to investigate Artificial Life (ALife)-related questions; similarly, a new era of soft-bodied robots has just begun. Nevertheless, because of their infinite degrees of freedom, soft bodies pose unique challenges in terms of simulation, control, and optimization. Herein I propose a novel soft-bodied agents formalism, namely, pressure-based soft agents (PSAs): spring-mass membranes containing a pressurized medium...

No abstract text is available yet for this article.

In sociotechnical settings, human operators are increasingly assisted by decision support systems. By employing such systems, important properties of sociotechnical systems, such as self-adaptation and self-optimization, are expected to improve further. To be accepted by and engage efficiently with operators, decision support systems need to be able to provide explanations regarding the reasoning behind specific decisions. In this article, we propose the use of learning classifier systems (LCSs), a family of rule-based machine learning methods, to facilitate and highlight techniques to improve transparent decision-making...

The prevalence of artificial intelligence (AI) tools that filter the information given to internet users, such as recommender systems and diverse personalizers, may be creating troubling long-term side effects to the obvious short-term conveniences. Many worry that these automated influencers can subtly and unwittingly nudge individuals toward conformity, thereby (somewhat paradoxically) restricting the choices of each agent and/or the population as a whole. In its various guises, this problem has labels such as filter bubble, echo chamber, and personalization polarization...

No abstract text is available yet for this article.