-
Simulating the Effect of Environmental Change on Evolving Populations Artif. Life (IF 2.6) Pub Date : 2024-03-13 John A. Bullinaria
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
-
A Spatial Artificial Chemistry Implementation of a Gene Regulatory Network Aimed at Generating Protein Concentration Dynamics Artif. Life (IF 2.6) Pub Date : 2024-02-29 Iliya Miralavy, Wolfgang Banzhaf
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
-
A Survey of Recent Practice of Artificial Life in Visual Art Artif. Life (IF 2.6) Pub Date : 2024-02-23 Zi-Wei Wu, Huamin Qu, Kang Zhang
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
-
Information, Coding, and Biological Function: The Dynamics of Life Artif. Life (IF 2.6) Pub Date : 2024-02-15 Julyan H. E. Cartwright, Jitka Čejková, Elena Fimmel, Simone Giannerini, Diego Luis Gonzalez, Greta Goracci, Clara Grácio, Jeanine Houwing-Duistermaat, Dragan Matić, Nataša Mišić, Frans A. A. Mulder, Oreste Piro
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
-
Motivations for Artificial Intelligence, for Deep Learning, for ALife: Mortality and Existential Risk Artif. Life (IF 2.6) Pub Date : 2024-02-12 Inman Harvey
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
-
An Afterword to Rise of the Self-Replicators: Placing John A. Etzler, Frigyes Karinthy, Fred Stahl, and Others in the Early History of Thought About Self-Reproducing Machines Artif. Life (IF 2.6) Pub Date : 2024-01-25 Tim Taylor
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
-
Emergent Resource Exchange and Tolerated Theft Behavior Using Multiagent Reinforcement Learning Artif. Life (IF 2.6) Pub Date : 2024-01-22 Jack Garbus, Jordan Pollack
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
-
Processionary Caterpillars at the Edge of Complexity Artif. Life (IF 2.6) Pub Date : 2024-01-16 Philippe Collard
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
-
Domain-Independent Lifelong Problem Solving Through Distributed ALife Actors Artif. Life (IF 2.6) Pub Date : 2023-12-04 Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen
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
-
Active Inference With Empathy Mechanism for Socially Behaved Artificial Agents in Diverse Situations Artif. Life (IF 2.6) Pub Date : 2023-11-29 Tadayuki Matsumura, Kanako Esaki, Shao Yang, Chihiro Yoshimura, Hiroyuki Mizuno
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
-
Pressure-Based Soft Agents Artif. Life (IF 2.6) Pub Date : 2023-11-21 Federico Pigozzi
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
-
The Dynamics of Social Interaction Among Evolved Model Agents Artif. Life (IF 2.6) Pub Date : 2023-11-21 Haily Merritt, Gabriel J. Severino, Eduardo J. Izquierdo
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
-
Editorial: A Word from the Editors Artif. Life (IF 2.6) Pub Date : 2023-11-01 Alan Dorin, Susan Stepney
We start this issue with a research article by Keith L. Downing, “The Evolution of Conformity, Malleability, and Influence in Simulated Online Agents.” The author uses an agent-based model to investigate the potential of positive feedback in personalized recommender systems for driving a population to polarization and conformity.
-
Assessing Model Requirements for Explainable AI: A Template and Exemplary Case Study Artif. Life (IF 2.6) Pub Date : 2023-11-01 Michael Heider, Helena Stegherr, Richard Nordsieck, Jörg Hähner
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
-
The Evolution of Conformity, Malleability, and Influence in Simulated Online Agents Artif. Life (IF 2.6) Pub Date : 2023-11-01 Keith L. Downing
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
-
Lessons from the Evolutionary Computation Bestiary Artif. Life (IF 2.6) Pub Date : 2023-11-01 Felipe Campelo, Claus Aranha
The field of metaheuristics has a long history of finding inspiration in natural systems, starting from evolution strategies, genetic algorithms, and ant colony optimization in the second half of the 20th century. In the last decades, however, the field has experienced an explosion of metaphor-centered methods claiming to be inspired by increasingly absurd natural (and even supernatural) phenomena—several
-
Artificial Collective Intelligence Engineering: A Survey of Concepts and Perspectives Artif. Life (IF 2.6) Pub Date : 2023-11-01 Roberto Casadei
Collectiveness is an important property of many systems—both natural and artificial. By exploiting a large number of individuals, it is often possible to produce effects that go far beyond the capabilities of the smartest individuals or even to produce intelligent collective behavior out of not-so-intelligent individuals. Indeed, collective intelligence, namely, the capability of a group to act collectively
-
Biology in AI: New Frontiers in Hardware, Software, and Wetware Modeling of Cognition Artif. Life (IF 2.6) Pub Date : 2023-08-01 Luisa Damiano, Pasquale Stano
The proposal for this special issue was inspired by the main themes around which we organize a series of satellite workshops at Artificial Life conferences (including some of the latest European Conferences on Artificial Life), the title of which is “SB-AI: What can Synthetic Biology (SB) offer to Artificial Intelligence (AI)?” The workshop themes are part of a larger scenario in which we are interested
-
Explorative Synthetic Biology in AI: Criteria of Relevance and a Taxonomy for Synthetic Models of Living and Cognitive Processes Artif. Life (IF 2.6) Pub Date : 2023-08-01 Luisa Damiano, Pasquale Stano
This article tackles the topic of the special issue “Biology in AI: New Frontiers in Hardware, Software and Wetware Modeling of Cognition” in two ways. It addresses the problem of the relevance of hardware, software, and wetware models for the scientific understanding of biological cognition, and it clarifies the contributions that synthetic biology, construed as the synthetic exploration of cognition
-
Design and Simulation of a Multilayer Chemical Neural Network That Learns via Backpropagation Artif. Life (IF 2.6) Pub Date : 2023-08-01 Matthew R. Lakin
The design and implementation of adaptive chemical reaction networks, capable of adjusting their behavior over time in response to experience, is a key goal for the fields of molecular computing and DNA nanotechnology. Mainstream machine learning research offers powerful tools for implementing learning behavior that could one day be realized in a wet chemistry system. Here we develop an abstract chemical
-
Understanding Social Robots: Attribution of Intentional Agency to Artificial and Biological Bodies Artif. Life (IF 2.6) Pub Date : 2023-08-01 Tom Ziemke
Much research in robotic artificial intelligence (AI) and Artificial Life has focused on autonomous agents as an embodied and situated approach to AI. Such systems are commonly viewed as overcoming many of the philosophical problems associated with traditional computationalist AI and cognitive science, such as the grounding problem (Harnad) or the lack of intentionality (Searle), because they have
-
Perspectives on Computation in Plants Artif. Life (IF 2.6) Pub Date : 2023-08-01 Emanuela Del Dottore, Barbara Mazzolai
Plants thrive in virtually all natural and human-adapted environments and are becoming popular models for developing robotics systems because of their strategies of morphological and behavioral adaptation. Such adaptation and high plasticity offer new approaches for designing, modeling, and controlling artificial systems acting in unstructured scenarios. At the same time, the development of artifacts
-
Does the Field of Nature-Inspired Computing Contribute to Achieving Lifelike Features? Artif. Life (IF 2.6) Pub Date : 2023-07-18 Alexandros Tzanetos
The main idea behind artificial intelligence was simple: what if we study living systems to develop new, practical computing systems that possess “lifelike” properties? And that’s exactly how evolutionary computing emerged. Researchers came up with ideas inspired by the principles of evolution to develop intelligent methods to tackle hard problems. The efficacy of these methods made researchers seek
-
Editorial: What Have Large-Language Models and Generative Al Got to Do With Artificial Life? Artif. Life (IF 2.6) Pub Date : 2023-05-01 Alan Dorin, Susan Stepney
Accessible generative artificial intelligence (AI) tools like large-language models (LLMs) (e.g., ChatGPT,11 Minerva22) are raising a flurry of questions about the potential and implications of generative algorithms and the ethical use of AI-generated text in a variety of contexts, including open science (Bugbee & Ramachandran, 2023), student assessment (Heidt, 2023), and medicine (Harrer, 2023). Similarly
-
On the Stability and Behavioral Diversity of Single and Collective Bernoulli Balls Artif. Life (IF 2.6) Pub Date : 2023-05-01 Toby Howison, Harriet Crisp, Simon Hauser, Fumiya Iida
The ability to express diverse behaviors is a key requirement for most biological systems. Underpinning behavioral diversity in the natural world is the embodied interaction between the brain, body, and environment. Dynamical systems form the basis of embodied agents, and can express complex behavioral modalities without any conventional computation. While significant study has focused on designing
-
Interdependent Self-Organizing Mechanisms for Cooperative Survival Artif. Life (IF 2.6) Pub Date : 2023-05-01 Matthew Scott, Jeremy Pitt
Cooperative survival “games” are situations in which, during a sequence of catastrophic events, no one survives unless everyone survives. Such situations can be further exacerbated by uncertainty over the timing and scale of the recurring catastrophes, while the resource management required for survival may depend on several interdependent subgames of resource extraction, distribution, and investment
-
DigiHive: Artificial Chemistry Environment for Modeling of Self-Organization Phenomena Artif. Life (IF 2.6) Pub Date : 2023-05-01 Rafał Sienkiewicz, Wojciech Jędruch
The article presents the DigiHive system, an artificial chemistry simulation environment, and the results of preliminary simulation experiments leading toward building a self-replicating system resembling a living cell. The two-dimensional environment is populated by particles that can bond together and form complexes of particles. Some complexes can recognize and change the structures of surrounding
-
Emergence in Artificial Life Artif. Life (IF 2.6) Pub Date : 2023-05-01 Carlos Gershenson
Even when concepts similar to emergence have been used since antiquity, we lack an agreed definition. However, emergence has been identified as one of the main features of complex systems. Most would agree on the statement “life is complex.” Thus understanding emergence and complexity should benefit the study of living systems. It can be said that life emerges from the interactions of complex molecules
-
A Generalised Dropout Mechanism for Distributed Systems Artif. Life (IF 2.6) Pub Date : 2023-05-01 Larry Bull, Haixia Liu
This letter uses a modified form of the NK model introduced to explore aspects of distributed control. In particular, a previous result suggesting the use of dynamically formed subgroups within the overall system can be more effective than global control is further explored. The conditions under which the beneficial distributed control emerges are more clearly identified, and the reason for the benefit
-
How Lévy Flights Triggered by the Presence of Defectors Affect Evolution of Cooperation in Spatial Games Artif. Life (IF 2.6) Pub Date : 2023-05-01 Genki Ichinose, Daiki Miyagawa, Erika Chiba, Hiroki Sayama
Cooperation among individuals has been key to sustaining societies. However, natural selection favors defection over cooperation. Cooperation can be favored when the mobility of individuals allows cooperators to form a cluster (or group). Mobility patterns of animals sometimes follow a Lévy flight. A Lévy flight is a kind of random walk but it is composed of many small movements with a few big movements
-
An Ansatz for Computational Undecidability in RNA Automata Artif. Life (IF 2.6) Pub Date : 2023-05-01 Adam J. Svahn, Mikhail Prokopenko
In this ansatz we consider theoretical constructions of RNA polymers into automata, a form of computational structure. The bases for transitions in our automata are plausible RNA enzymes that may perform ligation or cleavage. Limited to these operations, we construct RNA automata of increasing complexity; from the Finite Automaton (RNA-FA) to the Turing machine equivalent 2-stack PDA (RNA-2PDA) and
-
On the Open-Endedness of Detecting Open-Endedness Artif. Life (IF 2.6) Pub Date : 2023-02-27 Susan Stepney, Simon Hickinbotham
We argue that attempting to quantify open-endedness misses the point: The nature of open-endedness is such that an open-ended system will eventually move outside its current model of behavior, and hence outside any measure based on that model. This presents a challenge for analyzing Artificial Life systems, leading us to conclude that the focus should be on understanding the mechanisms underlying open-endedness
-
The “Agent-Based Modeling for Human Behavior” Special Issue Artif. Life (IF 2.6) Pub Date : 2023-01-02 Soo Ling Lim, Peter J. Bentley
Agent-based modeling
-
The Effects of Information on the Formation of Migration Routes and the Dynamics of Migration Artif. Life (IF 2.6) Pub Date : 2023-01-02 Martin Hinsch, Jakub Bijak
Most models of migration simply assume that migrants somehow make their way from their point of origin to their chosen destination. We know, however, that—especially in the case of asylum migration—the migrant journey often is a hazardous, difficult process where migrants make decisions based on limited information and under severe material constraints. Here we investigate the dynamics of the migration
-
Self-Isolation and Testing Behaviour During the COVID-19 Pandemic: An Agent-Based Model Artif. Life (IF 2.6) Pub Date : 2023-01-02 Umberto Gostoli, Eric Silverman
Since the beginning of the COVID-19 pandemic, various models of virus spread have been proposed. While most of these models focused on the replication of the interaction processes through which the virus is passed on from infected agents to susceptible ones, less effort has been devoted to the process through which agents modify their behaviour as they adapt to the risks posed by the pandemic. Understanding
-
Social Search and Resource Clustering as Emergent Stable States Artif. Life (IF 2.6) Pub Date : 2023-01-02 Mahi Luthra, Peter M. Todd
Social search has stably evolved across various species and is often used by humans to search for resources (such as food, information, social partners). In turn, these resources frequently come distributed in patches or clusters. In the current work, we use an ecologically inspired agent-based model to investigate whether social search and clustering are stable outcomes of the dynamical mutual interactions
-
Adapting the Exploration–Exploitation Balance in Heterogeneous Swarms: Tracking Evasive Targets Artif. Life (IF 2.6) Pub Date : 2023-01-02 Hian Lee Kwa, Victor Babineau, Julien Philippot, Roland Bouffanais
There has been growing interest in the use of multi-robot systems in various tasks and scenarios. The main attractiveness of such systems is their flexibility, robustness, and scalability. An often overlooked yet promising feature is system modularity, which offers the possibility of harnessing agent specialization, while also enabling system-level upgrades. However, altering the agents’ capacities
-
Expertise, Social Influence, and Knowledge Aggregation in Distributed Information Processing Artif. Life (IF 2.6) Pub Date : 2023-01-02 Asimina Mertzani, Jeremy Pitt, Andrzej Nowak, Tomasz Michalak
In many social, cyber-physical, and socio-technical systems, a group of autonomous peers can encounter a knowledge aggregation problem, requiring them to organise themselves, without a centralised authority, as a distributed information processing unit (DIP). In this article, we specify and implement a new algorithm for knowledge aggregation based on Nowak’s psychological theory Regulatory Theory of
-
Explaining the Neuroevolution of Fighting Creatures Through Virtual fMRI Artif. Life (IF 2.6) Pub Date : 2023-01-02 Kevin Godin-Dubois, Sylvain Cussat-Blanc, Yves Duthen
While interest in artificial neural networks (ANNs) has been renewed by the ubiquitous use of deep learning to solve high-dimensional problems, we are still far from general artificial intelligence. In this article, we address the problem of emergent cognitive capabilities and, more crucially, of their detection, by relying on co-evolving creatures with mutable morphology and neural structure. The
-
Using the Comparative Hybrid Approach to Disentangle the Role of Substrate Choice on the Evolution of Cognition Artif. Life (IF 2.6) Pub Date : 2022-11-01 Clifford Bohm, Sarah Albani, Charles Ofria, Acacia Ackles
Understanding the structure and evolution of natural cognition is a topic of broad scientific interest, as is the development of an engineering toolkit to construct artificial cognitive systems. One open question is determining which components and techniques to use in such a toolkit. To investigate this question, we employ agent-based AI, using simple computational substrates (i.e., digital brains)
-
A Genome-Wide Evolutionary Simulation of the Transcription-Supercoiling Coupling Artif. Life (IF 2.6) Pub Date : 2022-11-01 Théotime Grohens, Sam Meyer, Guillaume Beslon
DNA supercoiling, the level of under- or overwinding of the DNA polymer around itself, is widely recognized as an ancestral regulation mechanism of gene expression in bacteria. Higher levels of negative supercoiling facilitate the opening of the DNA double helix at gene promoters and thereby increase gene transcription rates. Different levels of supercoiling have been measured in bacteria exposed to
-
When to Be Critical? Performance and Evolvability in Different Regimes of Neural Ising Agents Artif. Life (IF 2.6) Pub Date : 2022-11-01 Sina Khajehabdollahi, Jan Prosi, Emmanouil Giannakakis, Georg Martius, Anna Levina
It has long been hypothesized that operating close to the critical state is beneficial for natural and artificial evolutionary systems. We put this hypothesis to test in a system of evolving foraging agents controlled by neural networks that can adapt the agents’ dynamical regime throughout evolution. Surprisingly, we find that all populations that discover solutions evolve to be subcritical. By a
-
Lexicase Selection for Multi-Task Evolutionary Robotics Artif. Life (IF 2.6) Pub Date : 2022-11-01 Adam Stanton, Jared M. Moore
In Evolutionary Robotics, Lexicase selection has proven effective when a single task is broken down into many individual parameterizations. Evolved individuals have generalized across unique configurations of an overarching task. Here, we investigate the ability of Lexicase selection to generalize across multiple tasks, with each task again broken down into many instances. There are three objectives:
-
Intrinsic Evolution of Analog Circuits Using Field Programmable Gate Arrays Artif. Life (IF 2.6) Pub Date : 2022-11-01 Derek Whitley, Jason Yoder, Nicklas Carpenter
Evolvable hardware is a field of study exploring the application of evolutionary algorithms to hardware systems during design, operation, or both. The work presented here focuses on the use of field programmable gate arrays (FPGAs), a type of dynamically reconfigurable hardware device typically used for electronic prototyping in conjunction with a newly created open-source platform for performing intrinsic
-
Crowd-Sourced Identification of Characteristics of Collective Human Motion Artif. Life (IF 2.6) Pub Date : 2022-11-01 Martyn Amos, Jamie Webster
Crowd simulations are used extensively to study the dynamics of human collectives. Such studies are underpinned by specific movement models, which encode rules and assumptions about how people navigate a space and handle interactions with others. These models often give rise to macroscopic simulated crowd behaviours that are statistically valid, but which lack the noisy microscopic behaviours that
-
Evolving Modularity in Soft Robots Through an Embodied and Self-Organizing Neural Controller Artif. Life (IF 2.6) Pub Date : 2022-08-04 Federico Pigozzi, Eric Medvet
Modularity is a desirable property for embodied agents, as it could foster their suitability to different domains by disassembling them into transferable modules that can be reassembled differently. We focus on a class of embodied agents known as voxel-based soft robots (VSRs). They are aggregations of elastic blocks of soft material; as such, their morphologies are intrinsically modular. Nevertheless
-
Braitenberg Vehicles as Developmental Neurosimulation Artif. Life (IF 2.6) Pub Date : 2022-08-04 Stefan Dvoretskii, Ziyi Gong, Ankit Gupta, Jesse Parent, Bradly Alicea
Connecting brain and behavior is a longstanding issue in the areas of behavioral science, artificial intelligence, and neurobiology. As is standard among models of artificial and biological neural networks, an analogue of the fully mature brain is presented as a blank slate. However, this does not consider the realities of biological development and developmental learning. Our purpose is to model the
-
Machines That Feel and Think: The Role of Affective Feelings and Mental Action in (Artificial) General Intelligence Artif. Life (IF 2.6) Pub Date : 2022-08-04 George Deane
What role do affective feelings (feelings/emotions/moods) play in adaptive behaviour? What are the implications of this for understanding and developing artificial general intelligence? Leading theoretical models of brain function are beginning to shed light on these questions. While artificial agents have excelled within narrowly circumscribed and specialised domains, domain-general intelligence has
-
An Embodied Intelligence-Based Biologically Inspired Strategy for Searching a Moving Target Artif. Life (IF 2.6) Pub Date : 2022-08-04 Julian K. P. Tan, Chee Pin Tan, Surya G. Nurzaman
Bacterial chemotaxis in unicellular Escherichia coli, the simplest biological creature, enables it to perform effective searching behaviour even with a single sensor, achieved via a sequence of “tumbling” and “swimming” behaviours guided by gradient information. Recent studies show that suitable random walk strategies may guide the behaviour in the absence of gradient information. This article presents
-
The Enactive and Interactive Dimensions of AI: Ingenuity and Imagination Through the Lens of Art and Music Artif. Life (IF 2.6) Pub Date : 2022-08-04 Maki Sato, Jonathan McKinney
Dualisms are pervasive. The divisions between the rational mind, the physical body, and the external natural world have set the stage for the successes and failures of contemporary cognitive science and artificial intelligence.1 Advanced machine learning (ML) and artificial intelligence (AI) systems have been developed to draw art and compose music. Many take these facts as calls for a radical shift
-
Editorial Introduction to the Special Issue on Embodied Intelligence. Artif. Life (IF 2.6) Pub Date : 2022-08-04 Fumiya Iida,Josie Hughes
-
Editorial: The 2019 Conference on Artificial Life Special Issue Artif. Life (IF 2.6) Pub Date : 2022-06-28 Harold Fellermann, Rudolf M. Füchslin
This special issue highlights key selections from the 2019 Conference on Artificial Life, ALIFE’19, hosted by Newcastle University in Newcastle upon Tyne, UK. The annual conference addresses the synthesis and simulation of living systems.
-
Self-Replication in Neural Networks Artif. Life (IF 2.6) Pub Date : 2022-06-28 Thomas Gabor, Steffen Illium, Maximilian Zorn, Cristian Lenta, Andy Mattausch, Lenz Belzner, Claudia Linnhoff-Popien
A key element of biological structures is self-replication. Neural networks are the prime structure used for the emergent construction of complex behavior in computers. We analyze how various network types lend themselves to self-replication. Backpropagation turns out to be the natural way to navigate the space of network weights and allows non-trivial self-replicators to arise naturally. We perform
-
How the History of Changing Environments Affects Traits of Evolvable Robot Populations Artif. Life (IF 2.6) Pub Date : 2022-06-28 Karine Miras, A. E. Eiben
The environment is one of the key factors in the emergence of intelligent creatures, but it has received little attention within the Evolutionary Robotics literature. This article investigates the effects of changing environments on morphological and behavioral traits of evolvable robots. In particular, we extend a previous study by evolving robot populations under diverse changing-environment setups
-
Long-Term Evolution Experiment with Genetic Programming Artif. Life (IF 2.6) Pub Date : 2022-06-28 William B. Langdon, Wolfgang Banzhaf
We evolve floating point Sextic polynomial populations of genetic programming binary trees for up to a million generations. We observe continued innovation but this is limited by tree depth. We suggest that deep expressions are resilient to learning as they disperse information, impeding evolvability, and the adaptation of highly nested organisms, and we argue instead for open complexity. Programs
-
Deterministic Response Threshold Models of Reproductive Division of Labor Are More Robust Than Probabilistic Models in Artificial Ants Artif. Life (IF 2.6) Pub Date : 2022-06-28 Chris Marriott, Peter Bae, Jobran Chebib
We implement an agent-based simulation of the response threshold model of reproductive division of labor. Ants in our simulation must perform two tasks in their environment: forage and reproduce. The colony is capable of allocating ant resources to these roles using different division of labor strategies via genetic architectures and plasticity mechanisms. We find that the deterministic allocation
-
Resolving Anomalies in the Behaviour of a Modularity-Inducing Problem Domain with Distributional Fitness Evaluation Artif. Life (IF 2.6) Pub Date : 2022-06-28 Zhenyue Qin, Tom Gedeon, R. I. McKay
Discrete gene regulatory networks (GRNs) play a vital role in the study of robustness and modularity. A common method of evaluating the robustness of GRNs is to measure their ability to regulate a set of perturbed gene activation patterns back to their unperturbed forms. Usually, perturbations are obtained by collecting random samples produced by a predefined distribution of gene activation patterns
-
From Dynamics to Novelty: An Agent-Based Model of the Economic System Artif. Life (IF 2.6) Pub Date : 2022-05-18 Gustavo Recio, Wolfgang Banzhaf, Roger White
The modern economy is both a complex self-organizing system and an innovative, evolving one. Contemporary theory, however, treats it essentially as a static equilibrium system. Here we propose a formal framework to capture its complex, evolving nature. We develop an agent-based model of an economic system in which firms interact with each other and with consumers through market transactions. Production
-
Effect of Environmental Change Distribution on Artificial Life Simulations Artif. Life (IF 2.6) Pub Date : 2022-05-17 John A. Bullinaria
It is already well known that environmental variation has a big effect on real evolution, and similar effects have been found in evolutionary artificial life simulations. In particular, a lot of research has been carried out on how the various evolutionary outcomes depend on the noise distributions representing the environmental changes, and how important it is for models to use inverse power-law distributions
-
A Response to Paolo Euron’s “Uncanny Beauty: Aesthetics of Companionship, Love, and Sex Robots” Artif. Life (IF 2.6) Pub Date : 2022-05-13 Maria O’Sullivan
The emergence of sex robots raises important issues about what it means to be human and the commodification of love, companionship, and sex. This commentary discusses the following question: If some members of society relate to robots as “humans,” what does this mean for society’s conceptualisation of personhood and intimate relationships? How love is expressed between individuals is normally considered