593 results match your criteria Artificial Life[Journal]


Evolutionary Robotics Controllers with Proprioception Facilitated by Neural-Network-Based Simulators.

Artif Life 2020 25;26(4):455-483. Epub 2021 Jan 25.

Nelson Mandela University, Department of Computing Sciences.

Taking inspiration from the navigation ability of humans, this study investigated a method of providing robotic controllers with a basic sense of position. It incorporated robotic simulators into robotic controllers to provide them with a mechanism to approximate the effects their actions had on the robot. Controllers with and without internal simulators were tested and compared. Read More

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January 2021

Reality-Assisted Evolution of Soft Robots through Large-Scale Physical Experimentation: A Review.

Artif Life 2020 25;26(4):484-506. Epub 2021 Jan 25.

University of Cambridge, Bio-Inspired Robotics Lab.

We introduce the framework of reality-assisted evolution to summarize a growing trend towards combining model-based and model-free approaches to improve the design of physically embodied soft robots. , data-driven models build, adapt, and improve representations of the target system using real-world experimental data. By simulating huge numbers of virtual robots using these data-driven models, optimization algorithms can illuminate multiple design candidates for transference to the real world. Read More

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January 2021

The Effect of Social Information Use Without Learning on the Evolution of Social Behavior.

Artif Life 2020 7;26(4):431-454. Epub 2020 Dec 7.

Keele University, School of Computing and Mathematics.

In a recent article by Borg and Channon it was shown that social information alone, decoupled from any within-lifetime learning, can result in improved performance on a food-foraging task compared to when social information is unavailable. Here we assess whether access to social information leads to significant behavioral differences both when access to social information leads to improved performance on the task, and when it does not: Do any behaviors resulting from social information use, such as movement and increased agent interaction, persist even when the ability to discriminate between poisonous and non-poisonous food is no better than when social information is unavailable? Using a neuroevolutionary artificial life simulation, we show that social information use can lead to the emergence of behaviors that differ from when social information is unavailable, and that these behaviors act as a promoter of agent interaction. The results presented here suggest that the introduction of social information is sufficient, even when decoupled from within-lifetime learning, for the emergence of pro-social behaviors. Read More

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December 2020

Long-Term Progress and Behavior Complexification in Competitive Coevolution.

Artif Life 2020 7;26(4):409-430. Epub 2020 Dec 7.

Institute of Cognitive Sciences and Technologies, National Research Council (CNR-ISTC).

The possibility of using competitive evolutionary algorithms to generate long-term progress is normally prevented by the convergence on limit cycle dynamics in which the evolving agents keep progressing against their current competitors by periodically rediscovering solutions adopted previously. This leads to local but not to global progress (i.e. Read More

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December 2020

Symbiosis Promotes Fitness Improvements in the Game of Life.

Authors:
Peter D Turney

Artif Life 2020 10;26(3):338-365. Epub 2020 Aug 10.

Ronin Institute.

We present a computational simulation of evolving entities that includes symbiosis with shifting levels of selection. Evolution by natural selection shifts from the level of the original entities to the level of the new symbiotic entity. In the simulation, the fitness of an entity is measured by a series of one-on-one competitions in the Immigration Game, a two-player variation of Conway's Game of Life. Read More

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January 2021

Genetic Music System with Synthetic Biology.

Artif Life 2020 10;26(3):366-390. Epub 2020 Aug 10.

University of Plymouth, Interdisciplinary Centre for Computer Music Research (ICCMR).

This article introduces GeMS, a system for music composition informed by synthetic biology. GeMS generates music with simulations of genetic processes, such as transcription, translation, and protein folding, with which biological systems render chains of amino acids from DNA strands. The system comprises the following components: the , the , and the . Read More

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January 2021

Self-Organization and Artificial Life.

Artif Life 2020 22;26(3):391-408. Epub 2020 Jul 22.

Binghamton University, Center for Collective Dynamics of Complex Systems.

Self-organization can be broadly defined as the ability of a system to display ordered spatiotemporal patterns solely as the result of the interactions among the system components. Processes of this kind characterize both living and artificial systems, making self-organization a concept that is at the basis of several disciplines, from physics to biology and engineering. Placed at the frontiers between disciplines, artificial life (ALife) has heavily borrowed concepts and tools from the study of self-organization, providing mechanistic interpretations of lifelike phenomena as well as useful constructivist approaches to artificial system design. Read More

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January 2021

Chemobrionics: From Self-Assembled Material Architectures to the Origin of Life.

Artif Life 2020 22;26(3):315-326. Epub 2020 Jul 22.

University of Szeged, Department of Physical Chemistry and Materials Science.

Self-organizing precipitation processes, such as chemical gardens forming biomimetic micro- and nanotubular forms, have the potential to show us new fundamental science to explore, quantify, and understand nonequilibrium physicochemical systems, and shed light on the conditions for life's emergence. The physics and chemistry of these phenomena, due to the assembly of material architectures under a flux of ions, and their exploitation in applications, have recently been termed chemobrionics. Advances in understanding in this area require a combination of expertise in physics, chemistry, mathematical modeling, biology, and nanoengineering, as well as in complex systems and nonlinear and materials sciences, giving rise to this new synergistic discipline of chemobrionics. Read More

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January 2021

Side Reactions Do Not Completely Disrupt Linear Self-Replicating Chemical Reaction Systems.

Artif Life 2020 22;26(3):327-337. Epub 2020 Jul 22.

Institut Mittag-Leffler.

A crucial question within the fields of origins of life and metabolic networks is whether or not a self-replicating chemical reaction system is able to persist in the presence of side reactions. Due to the strong nonlinear effects involved in such systems, they are often difficult to study analytically. There are however certain conditions that allow for a wide range of these reaction systems to be well described by a set of linear ordinary differential equations. Read More

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January 2021

Erratum.

Authors:

Artif Life 2020 ;26(2):314

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January 2020

Erratum.

Authors:

Artif Life 2020 ;26(1):152

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January 2020

MetaChem: An Algebraic Framework for Artificial Chemistries.

Artif Life 2020 9;26(2):153-195. Epub 2020 Apr 9.

University of York, Department of Computer Science, York Cross-disciplinary Centre for Systems Analysis.

We introduce MetaChem, a language for representing and implementing artificial chemistries. We motivate the need for modularization and standardization in representation of artificial chemistries. We describe a mathematical formalism for Static Graph MetaChem, a static-graph-based system. Read More

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January 2021

Report on Workshop: Planning the Future of Agent Simulation.

Artif Life 2020 9;26(2):307-313. Epub 2020 Apr 9.

King's College London, Bush House.

In May 2019, a workshop on principled development of future agent-based simulations was held at Keele University. Participants spanned companies and academia, and a range of domains of interest, as well as participant career stages. This report summarizes the discussions and main outcomes from this workshop. Read More

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January 2021

Decentralized Control for Swarm Robots That Can Effectively Execute Spatially Distributed Tasks.

Artif Life 2020 9;26(2):242-259. Epub 2020 Apr 9.

Tohoku University, Research Institute of Electrical Communication.

A swarm robotic system is a system in which multiple robots cooperate to fulfill a macroscopic function. Many swarm robots have been developed for various purposes. This study aims to design swarm robots capable of executing spatially distributed tasks effectively, which can be potentially used for tasks such as search-and-rescue operation and gathering scattered garbage in rooms. Read More

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January 2021

Alteration of (Frequency-Dependent) Fitness in Time-Shift Experiments Reveals Cryptic Coevolution and Uncoordinated Stasis in a Virtual Jurassic Park.

Artif Life 2020 9;26(2):196-216. Epub 2020 Apr 9.

Nanjing Agricultural University, Department of Zoology, College of Life Sciences.

Among the major unresolved questions in ecosystem evolution are whether coevolving multispecies communities are dominated more by biotic or by abiotic factors, and whether evolutionary stasis affects performance as well as ecological profile; these issues remain difficult to address experimentally. Digital evolution, a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve, is an excellent platform for investigating such topics in a rigorous experimental manner. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. Read More

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January 2021

Evolving Connectionist Models to Capture Population Variability across Language Development: Modeling Children's Past Tense Formation.

Artif Life 2020 9;26(2):217-241. Epub 2020 Apr 9.

University of Londo,n Birkbeck College, Department of Psychological Sciences.

Children's acquisition of the English past tense has been widely studied as a testing ground for theories of language development, mostly because it comprises a set of quasi-regular mappings. English verbs are of two types: regular verbs, which form their past tense based on a productive rule, and irregular verbs, which form their past tenses through exceptions to that rule. Although many connectionist models exist for capturing language development, few consider individual differences. Read More

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January 2021

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities.

Artif Life 2020 9;26(2):274-306. Epub 2020 Apr 9.

Columbia University.

Evolution provides a creative fount of complex and subtle adaptations that often surprise the scientists who discover them. However, the creativity of evolution is not limited to the natural world: Artificial organisms evolving in computational environments have also elicited surprise and wonder from the researchers studying them. The process of evolution is an process that transcends the substrate in which it occurs. Read More

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January 2021

Engineering Life: A Review of Synthetic Biology.

Authors:
Martin M Hanczyc

Artif Life 2020 9;26(2):260-273. Epub 2020 Apr 9.

University of Trento, Department of Cellular, Computational, and Integrative Biology (CIBIO).

Synthetic biology is a field of scientific research that applies engineering principles to living organisms and living systems. It is a field that is increasing in scope with respect to organisms engineered, practical outcomes, and systems integration. There is a commercial dimension as well, where living organisms are engineered as green technologies that could offer alternatives to industrial standards in the pharmaceutical and petroleum-based chemical industries. Read More

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January 2021

Interpreting the Tape of Life: Ancestry-Based Analyses Provide Insights and Intuition about Evolutionary Dynamics.

Artif Life 2020 6;26(1):58-79. Epub 2020 Feb 6.

Michigan State University, BEACON Center for the Study of Evolution in Action, Department of Computer Science and Engineering, Ecology, Evolutionary Biology, and Behavior Program.

Fine-scale evolutionary dynamics can be challenging to tease out when focused on the broad brush strokes of whole populations over long time spans. We propose a suite of diagnostic analysis techniques that operate on lineages and phylogenies in digital evolution experiments, with the aim of improving our capacity to quantitatively explore the nuances of evolutionary histories in digital evolution experiments. We present three types of lineage measurements: lineage length, mutation accumulation, and phenotypic volatility. Read More

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The Complexity Ratchet: Stronger than Selection, Stronger than Evolvability, Weaker than Robustness.

Artif Life 2020 6;26(1):38-57. Epub 2020 Feb 6.

Inria Beagle Team.

Using the in silico experimental evolution platform Aevol, we have tested the existence of a by evolving populations of digital organisms under environmental conditions in which simple organisms can very well thrive and reproduce. We observed that in most simulations, organisms become complex although such organisms are a lot less fit than simple ones and have no robustness or evolvability advantage. This excludes selection from the set of possible explanations for the evolution of complexity. Read More

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Neural Autopoiesis: Organizing Self-Boundaries by Stimulus Avoidance in Biological and Artificial Neural Networks.

Artif Life 2020 6;26(1):130-151. Epub 2020 Feb 6.

University of Tokyo, Department of General Systems Sciences, Graduate School of Arts and Sciences.

Living organisms must actively maintain themselves in order to continue existing. Autopoiesis is a key concept in the study of living organisms, where the boundaries of the organism are not static but dynamically regulated by the system itself. To study the autonomous regulation of a self-boundary, we focus on neural homeodynamic responses to environmental changes using both biological and artificial neural networks. Read More

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Death and Progress: How Evolvability is Influenced by Intrinsic Mortality.

Artif Life 2020 6;26(1):90-111. Epub 2020 Feb 6.

IT University of Copenhagen.

Many factors influence the evolvability of populations, and this article illustrates how intrinsic mortality (death induced through internal factors) in an evolving population contributes favorably to evolvability on a fixed deceptive fitness landscape. We test for evolvability using the hierarchical if-and-only-if (h-iff) function as a deceptive fitness landscape together with a steady state genetic algorithm (SSGA) with a variable mutation rate and indiscriminate intrinsic mortality rate. The mutation rate and the intrinsic mortality rate display a relationship for finding the global maximum. Read More

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Autonomously Moving Pine-Cone Robots: Using Pine Cones as Natural Hygromorphic Actuators and as Components of Mechanisms.

Artif Life 2020 6;26(1):80-89. Epub 2020 Feb 6.

Waseda University, The Department of Intermedia Art and Science.

We have developed autonomously moving pine-cone robots, which are made of multiple joined pine-cone scales for outdoor natural environments. We achieved these natural robots by using pine cones as both natural hygromorphic actuators and components of the mechanisms. When they are put in outdoor places where moist periods (e. Read More

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Evolution Towards Criticality in Ising Neural Agents.

Artif Life 2020 6;26(1):112-129. Epub 2020 Feb 6.

Cross Compass Ltd., Cross Labs.

Criticality is thought to be crucial for complex systems to adapt at the boundary between regimes with different dynamics, where the system may transition from one phase to another. Numerous systems, from sandpiles to gene regulatory networks to swarms to human brains, seem to work towards preserving a precarious balance right at their critical point. Understanding criticality therefore seems strongly related to a broad, fundamental theory for the physics of life as it could be, which still lacks a clear description of how life can arise and maintain itself in complex systems. Read More

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How Computational Experiments Can Improve Our Understanding of the Genetic Architecture of Common Human Diseases.

Artif Life 2020 6;26(1):23-37. Epub 2020 Feb 6.

University of Pennsylvania, Institute for Biomedical Informatics, Perelman School of Medicine.

Susceptibility to common human diseases such as cancer is influenced by many genetic and environmental factors that work together in a complex manner. The state of the art is to perform a genome-wide association study (GWAS) that measures millions of single-nucleotide polymorphisms (SNPs) throughout the genome followed by a one-SNP-at-a-time statistical analysis to detect univariate associations. This approach has identified thousands of genetic risk factors for hundreds of diseases. Read More

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An Investigation into the Origin of Autopoiesis.

Authors:
Randall D Beer

Artif Life 2020 6;26(1):5-22. Epub 2020 Feb 6.

Indiana University, Cognitive Science Program.

Using a glider in the Game of Life cellular automaton as a toy model of minimal persistent individuals, this article explores how questions regarding the origin of life might be approached from the perspective of autopoiesis. Specifically, I examine how the density of gliders evolves over time from random initial conditions and then develop a statistical mechanics of gliders that explains this time evolution in terms of the processes of glider creation, persistence, and destruction that underlie it. Read More

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Evolving Complexity in Cooperative and Competitive Noisy Prediction Games.

Artif Life 2019 7;25(4):366-382. Epub 2019 Nov 7.

Brandeis University, DEMO Lab.

We examine the effect of cooperative and competitive interactions on the evolution of complex strategies in a prediction game. We extend previous work to the domain of noisy games, defining a new organism and mutation model, and an accompanying novel complexity metric. We find that a mix of cooperation and competition is the most effective in driving complexity growth, confirming prior results. Read More

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Reinforcement Learning for Improving Agent Design.

Authors:
David Ha

Artif Life 2019 7;25(4):352-365. Epub 2019 Nov 7.

Google Brain, Tokyo, Japan.

In many reinforcement learning tasks, the goal is to learn a policy to manipulate an agent, whose design is fixed, to maximize some notion of cumulative reward. The design of the agent's physical structure is rarely optimized for the task at hand. In this work, we explore the possibility of learning a version of the agent's design that is better suited for its task, jointly with the policy. Read More

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Measuring Time with Minimal Clocks.

Artif Life 2019 7;25(4):383-409. Epub 2019 Nov 7.

University of Hertfordshire, School of Computer Science, Adaptive Systems Research Group.

Being able to measure time, whether directly or indirectly, is a significant advantage for an organism. It allows for timely reaction to regular or predicted events, reducing the pressure for fast processing of sensory input. Thus, clocks are ubiquitous in biology. Read More

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