584 results match your criteria Artificial Life[Journal]


Erratum.

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Artif Life 2020 ;26(2):314

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http://dx.doi.org/10.1162/artl_x_00322DOI Listing
January 2020

Erratum.

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Artif Life 2020 ;26(1):152

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http://dx.doi.org/10.1162/artl_e_00321DOI Listing
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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http://dx.doi.org/10.1162/artl_a_00315DOI Listing

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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http://dx.doi.org/10.1162/artl_a_00320DOI Listing

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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http://dx.doi.org/10.1162/artl_a_00317DOI Listing

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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http://dx.doi.org/10.1162/artl_a_00305DOI Listing

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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http://dx.doi.org/10.1162/artl_a_00316DOI Listing

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.

Uber AI Labs.

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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http://dx.doi.org/10.1162/artl_a_00319DOI Listing

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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http://dx.doi.org/10.1162/artl_a_00318DOI Listing

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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http://dx.doi.org/10.1162/artl_a_00313DOI Listing
February 2020

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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http://dx.doi.org/10.1162/artl_a_00312DOI Listing
February 2020

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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http://dx.doi.org/10.1162/artl_a_00314DOI Listing
February 2020

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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http://dx.doi.org/10.1162/artl_a_00311DOI Listing
February 2020

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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http://dx.doi.org/10.1162/artl_a_00310DOI Listing
February 2020

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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http://dx.doi.org/10.1162/artl_a_00309DOI Listing
February 2020

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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http://dx.doi.org/10.1162/artl_a_00308DOI Listing
February 2020

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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http://dx.doi.org/10.1162/artl_a_00307DOI Listing
February 2020

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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http://dx.doi.org/10.1162/artl_a_00302DOI Listing

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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http://dx.doi.org/10.1162/artl_a_00301DOI Listing

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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http://dx.doi.org/10.1162/artl_a_00303DOI Listing

Introduction to the ECAL 2017 Special Issue.

Artif Life 2019 7;25(4):313-314. Epub 2019 Nov 7.

Center for Research and Interdisciplinarity.

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http://dx.doi.org/10.1162/artl_a_00298DOI Listing

Circular Causation, Circular Cognition: A Tour Around Some Common Confusions.

Authors:
Inman Harvey

Artif Life 2019 7;25(4):334-351. Epub 2019 Nov 7.

University of Sussex, Evolutionary and Adaptive Systems Group.

Life and cognition are inherently circular dynamical processes, and people have difficulty understanding circular causation. I give case studies illustrating some resulting confusions, and propose that the problems may lie in failing to properly distinguish between similar concepts used to describe both local and global features of a system. I analyze how explanations in terms of circular causation work and how they rely on principles of . Read More

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http://dx.doi.org/10.1162/artl_a_00300DOI Listing

Can Signal Delay be Functional? Including Delay in Evolved Robot Controllers.

Artif Life 2019 7;25(4):315-333. Epub 2019 Nov 7.

University of Auckland, Department of Mathematics.

Engineers, control theorists, and neuroscientists often view the delay imposed by finite signal propagation velocities as a problem that needs to be compensated for or avoided. In this article, we consider the alternative possibility that in some cases, signal delay can be used , that is, as an essential component of a cognitive system. To investigate this idea, we evolve a minimal robot controller to solve a basic stimulus-distinction task. Read More

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http://dx.doi.org/10.1162/artl_a_00299DOI Listing

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review.

Artif Life 2019 ;25(3):263-311

Guangzhou University, School of Mechanical and Electrical Engineering; Machine Life and Intelligence Research Centre.

Motion perception is a critical capability determining a variety of aspects of insects' life, including avoiding predators, foraging, and so forth. A good number of motion detectors have been identified in the insects' visual pathways. Computational modeling of these motion detectors has not only been providing effective solutions to artificial intelligence, but also benefiting the understanding of complicated biological visual systems. Read More

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http://dx.doi.org/10.1162/artl_a_00297DOI Listing

Why Open-Endedness Matters.

Artif Life 2019 ;25(3):232-235

Uber AI Labs.

Rather than acting as a review or analysis of the field, this essay focuses squarely on the motivations for investigating open-endedness and the opportunities it opens up. It begins by contemplating the awesome accomplishments of evolution in nature and the profound implications if such a process could be ignited on a computer. Some of the milestones in our understanding so far are then discussed, finally closing by highlighting the grand challenge of formalizing open-endedness as a computational process that can be encoded as an algorithm. Read More

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http://dx.doi.org/10.1162/artl_a_00294DOI Listing
April 2020
10 Reads

Nanoscale Robots Exhibiting Quorum Sensing.

Artif Life 2019 ;25(3):227-231

Augmanity Nano.

Multi-agent systems demonstrate the ability to collectively perform complex tasks (e.g., construction, search, and locomotion) with greater speed, efficiency, or effectiveness than could a single agent alone. Read More

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http://dx.doi.org/10.1162/artl_a_00293DOI Listing
April 2020
3 Reads

Mapping the Peaks: Fitness Landscapes of the Fittest and the Flattest.

Artif Life 2019 ;25(3):250-262

Michigan State University, Department of Microbiology and Molecular Genetics; Department of Ecology, Evolutionary Biology, and Behavior; BEACON Center for the Study of Evolution in Action.

Populations exposed to a high mutation rate harbor abundant deleterious genetic variation, leading to depressed mean fitness. This reduction in mean fitness presents an opportunity for selection to restore fitness through the evolution of mutational robustness. In extreme cases, selection for mutational robustness can lead to genotypes (with low fitness but high robustness) outcompeting genotypes (with high fitness but low robustness)-a phenomenon known as . Read More

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http://dx.doi.org/10.1162/artl_a_00296DOI Listing
April 2020
1 Read

Exploring Bipedal Hopping through Computational Evolution.

Artif Life 2019 ;25(3):236-249

Michigan State University, Department of Computer Science and Engineering.

Bipedal hopping is an efficient form of locomotion, yet it remains relatively rare in the natural world. Previous research has suggested that the tail balances the angular momentum of the legs to produce steady state bipedal hopping. In this study, we employ a 3D physics simulation engine to optimize gaits for an animat whose control and morphological characteristics are subject to computational evolution, which emulates properties of natural evolution. Read More

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http://dx.doi.org/10.1162/artl_a_00295DOI Listing
April 2020
1 Read

Open-Ended Evolution and a Mechanism of Novelties in Web Services.

Artif Life 2019 ;25(2):168-177

University of Tsukuba, Department of Computer Science.

Web services are analogous to living ecosystems in nature, in that they form an artificial ecosystem consisting of many tags and their associated media, such as photographs, movies, and web pages created by human users. In biological ecosystems, we view a tag as a species and a human as a hidden environmental resource. Our study examines the evolution of web services, in particular social tagging systems, with respect to the self-organization of new tags. Read More

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http://dx.doi.org/10.1162/artl_a_00287DOI Listing
April 2020
1 Read

On the Potential for Open-Endedness in Neural Networks.

Artif Life 2019 ;25(2):145-167

University of Surrey, Centre for Evaluation of Complexity Across the Nexus, Centre for Research in Social Simulation.

Natural evolution gives the impression of leading to an open-ended process of increasing diversity and complexity. If our goal is to produce such open-endedness artificially, this suggests an approach driven by evolutionary metaphor. On the other hand, techniques from machine learning and artificial intelligence are often considered too narrow to provide the sort of exploratory dynamics associated with evolution. Read More

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http://dx.doi.org/10.1162/artl_a_00286DOI Listing
April 2020
2 Reads

Open-Endedness for the Sake of Open-Endedness.

Authors:
Arend Hintze

Artif Life 2019 ;25(2):198-206

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

Natural evolution keeps inventing new complex and intricate forms and behaviors. Digital evolution and genetic algorithms fail to create the same kind of complexity, not just because we still lack the computational resources to rival nature, but because (it has been argued) we have not understood in principle how to create open-ended evolving systems. Much effort has been made to define such open-endedness so as to create forms of increasing complexity indefinitely. Read More

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http://dx.doi.org/10.1162/artl_a_00289DOI Listing
April 2020
1 Read

How to Make Swarms Open-Ended? Evolving Collective Intelligence Through a Constricted Exploration of Adjacent Possibles.

Artif Life 2019 ;25(2):178-197

University of Tokyo.

We propose an approach to open-ended evolution via the simulation of swarm dynamics. In nature, swarms possess remarkable properties, which allow many organisms, from swarming bacteria to ants and flocking birds, to form higher-order structures that enhance their behavior as a group. Swarm simulations highlight three important factors to create novelty and diversity: (a) communication generates combinatorial cooperative dynamics, (b) concurrency allows for separation of time scales, and (c) complexity and size increases push the system towards transitions in innovation. Read More

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http://dx.doi.org/10.1162/artl_a_00288DOI Listing
April 2020
1 Read

Cardinality Leap for Open-Ended Evolution: Theoretical Consideration and Demonstration by Hash Chemistry.

Authors:
Hiroki Sayama

Artif Life 2019 ;25(2):104-116

Binghamton University, Center for Collective Dynamics of Complex Systems.

Open-ended evolution requires unbounded possibilities that evolving entities can explore. The cardinality of a set of those possibilities thus has a significant implication for the open-endedness of evolution. I propose that facilitating formation of higher-order entities is a generalizable, effective way to cause a in the set of possibilities that promotes open-endedness. Read More

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http://dx.doi.org/10.1162/artl_a_00283DOI Listing
April 2020
1 Read

Maximum Individual Complexity is Indefinitely Scalable in Geb.

Authors:
Alastair Channon

Artif Life 2019 ;25(2):134-144

Keele University, School of Computing and Mathematics.

Geb was the first artificial life system to be classified as exhibiting open-ended evolutionary dynamics according to Bedau and Packard's evolutionary activity measures and is the only one to have been classified as such according to the enhanced version of that classification scheme. Its evolution is driven by biotic selection, that is (approximately), by natural selection rather than artificial selection. Whether or not Geb can generate an indefinite increase in maximum individual complexity is evaluated here by scaling two parameters: world length (which bounds population size) and the maximum number of neurons per individual. Read More

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http://dx.doi.org/10.1162/artl_a_00285DOI Listing
April 2020
1 Read

Toward Open-Ended Fraternal Transitions in Individuality.

Artif Life 2019 ;25(2):117-133

Michigan State University.

The emergence of new replicating entities from the union of simpler entities characterizes some of the most profound events in natural evolutionary history. Such transitions in individuality are essential to the evolution of the most complex forms of life. Thus, understanding these transitions is critical to building artificial systems capable of open-ended evolution. Read More

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http://dx.doi.org/10.1162/artl_a_00284DOI Listing
April 2020
9 Reads

Evolutionary Innovations and Where to Find Them: Routes to Open-Ended Evolution in Natural and Artificial Systems.

Authors:
Tim Taylor

Artif Life 2019 ;25(2):207-224

Monash University, Faculty of Information Technology.

This article presents a high-level conceptual framework to help orient the discussion and implementation of open-endedness in evolutionary systems. Drawing upon earlier work by Banzhaf et al. (2016), three different kinds of open-endedness are identified: , , and . Read More

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http://dx.doi.org/10.1162/artl_a_00290DOI Listing
April 2020
1 Read

An Overview of Open-Ended Evolution: Editorial Introduction to the Open-Ended Evolution II Special Issue.

Artif Life 2019 ;25(2):93-103

Monash University.

Nature's spectacular inventiveness, reflected in the enormous diversity of form and function displayed by the biosphere, is a feature of life that distinguishes most strongly from . 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 (OEE) in the field. Read More

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http://dx.doi.org/10.1162/artl_a_00291DOI Listing
April 2020
1 Read

Open-Ended Technological Innovation.

Artif Life 2019 ;25(1):33-49

ProtoLife, Inc.

We detect ongoing innovation in empirical data about human technological innovations. Ongoing technological innovation is a form of open-ended evolution, but it occurs in a nonbiological, cultural population that consists of actual technological innovations that exist in the real world. The change over time of this population of innovations seems to be quite open-ended. Read More

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http://dx.doi.org/10.1162/artl_a_00279DOI Listing
March 2020
28 Reads

Evolved Open-Endedness, Not Open-Ended Evolution.

Artif Life 2019 ;25(1):4-8

Binghamton University-SUNY, Department of Systems Sciences and Industrial Engineering.

Open-endedness is often considered a prerequisite property of the whole evolutionary system and its dynamical behaviors. In the actual history of evolution on Earth, however, there are many examples showing that open-endedness is rather a consequence of evolution. We suggest that this view, which we call evolved open-endedness (EOE), be incorporated more into research on open-ended evolution. Read More

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http://dx.doi.org/10.1162/artl_a_00276DOI Listing
March 2020
1 Read

Escalation of Memory Length in Finite Populations.

Artif Life 2019 ;25(1):22-32

Brandeis University, Department of Computer Science .

The escalation of complexity is a commonly cited benefit of coevolutionary systems, but computational simulations generally fail to demonstrate this capacity to a satisfactory degree. We draw on a macroevolutionary theory of escalation to develop a set of criteria for coevolutionary systems to exhibit escalation of strategic complexity. By expanding on a previously developed model of the evolution of memory length for cooperative strategies by Kristian Lindgren, we resolve previously observed limitations on the escalation of memory length by extending operators of evolutionary variation. Read More

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http://dx.doi.org/10.1162/artl_a_00278DOI Listing
March 2020
1 Read

Two Modes of Evolution: Optimization and Expansion.

Artif Life 2019 ;25(1):9-21

University of Southern Denmark, Center for Fundamental Living Technology (FLinT), Department for Physics, Chemistry, and Pharmacy.

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. Read More

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http://dx.doi.org/10.1162/artl_a_00277DOI Listing
March 2020
1 Read

Open-Ended Evolution and Open-Endedness: Editorial Introduction to the Open-Ended Evolution I Special Issue.

Artif Life 2019 ;25(1):1-3

Monash University.

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. Read More

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http://dx.doi.org/10.1162/artl_e_00282DOI Listing
March 2020
2 Reads

Evolving Complexity in Prediction Games.

Artif Life 2019 ;25(1):74-91

Brandeis University DEMO Lab.

To study open-ended coevolution, we define a complexity metric over interacting finite state machines playing formal language prediction games, and study the dynamics of populations under competitive and cooperative interactions. In the past purely competitive and purely cooperative interactions have been studied extensively, but neither can successfully and continuously drive an arms race. We present quantitative results using this complexity metric and analyze the causes of varying rates of complexity growth across different types of interactions. Read More

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http://dx.doi.org/10.1162/artl_a_00281DOI Listing
March 2020
15 Reads

The MODES Toolbox: Measurements of Open-Ended Dynamics in Evolving Systems.

Artif Life 2019 ;25(1):50-73

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

Building more open-ended evolutionary systems can simultaneously advance our understanding of biology, artificial life, and evolutionary computation. In order to do so, however, we need a way to determine when we are moving closer to this goal. We propose a set of metrics that allow us to measure a system's ability to produce commonly-agreed-upon hallmarks of open-ended evolution: change potential, novelty potential, complexity potential, and ecological potential. Read More

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http://dx.doi.org/10.1162/artl_a_00280DOI Listing
March 2020
3 Reads

Artificial Gene Regulatory Networks-A Review.

Artif Life 2018 25;24(4):296-328. Epub 2019 Jan 25.

Michigan State University, BEACON Center for the Study of Evolution in Action, Department of Computer Science and Engineering.

In nature, gene regulatory networks are a key mediator between the information stored in the DNA of living organisms (their genotype) and the structural and behavioral expression this finds in their bodies, surviving in the world (their phenotype). They integrate environmental signals, steer development, buffer stochasticity, and allow evolution to proceed. In engineering, modeling and implementations of artificial gene regulatory networks have been an expanding field of research and development over the past few decades. Read More

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http://dx.doi.org/10.1162/artl_a_00267DOI Listing
September 2019
1 Read

Examining Community Stability in the Face of Mass Extinction in Communities of Digital Organisms.

Artif Life 2018 25;24(4):250-276. Epub 2019 Jan 25.

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

Digital evolution is a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve. It is an excellent platform for addressing topics in long-term evolution and paleobiology, such as mass extinction and recovery, with experimental evolutionary approaches. 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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https://www.mitpressjournals.org/doi/abs/10.1162/artl_a_0027
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http://dx.doi.org/10.1162/artl_a_00272DOI Listing
September 2019
5 Reads
1.386 Impact Factor

Moderate Environmental Variation Across Generations Promotes the Evolution of Robust Solutions.

Artif Life 2018 25;24(4):277-295. Epub 2019 Jan 25.

Institute of Cognitive Sciences and Technologies, National Research Council.

Previous evolutionary studies demonstrated how robust solutions can be obtained by evaluating agents multiple times in variable environmental conditions. Here we demonstrate how agents evolved in environments that vary across generations outperform agents evolved in environments that remain fixed. Moreover, we demonstrate that best performance is obtained when the environment varies at a moderate rate across generations, that is, when the environment does not vary every generation but every N generations. Read More

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http://dx.doi.org/10.1162/artl_a_00274DOI Listing
September 2019
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Spatial Structure Can Decrease Symbiotic Cooperation.

Artif Life 2018 25;24(4):229-249. Epub 2019 Jan 25.

Michigan State University.

Mutualisms occur when at least two species provide a net fitness benefit to each other. These types of interactions are ubiquitous in nature, with more being discovered regularly. Mutualisms are vital to humankind: Pollinators and soil microbes are critical in agriculture, bacterial microbiomes regulate our health, and domesticated animals provide us with food and companionship. Read More

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http://dx.doi.org/10.1162/artl_a_00273DOI Listing
September 2019
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Measuring Fitness Effects of Agent-Environment Interactions.

Artif Life 2018 ;24(3):199-217

Imperial College London.

One important sense of the term "adaptation" is the process by which an agent changes appropriately in response to new information provided by environmental stimuli. We propose a novel quantitative measure of this phenomenon, which extends a little-known definition of adaptation as "increased robustness to repeated perturbation" proposed by Klyubin (2002). Our proposed definition essentially corresponds to the average value (relative to some fitness function) of state changes that are caused by the environment (in some statistical ensemble of environments). Read More

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http://dx.doi.org/10.1162/artl_a_00269DOI Listing
September 2019
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