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Artificial Life

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2016: Artificial Life
Lance R Williams
Object-oriented combinator chemistry (OOCC) is an artificial chemistry with composition devices borrowed from object-oriented and functional programming languages. Actors in OOCC are embedded in space and subject to diffusion; since they are neither created nor destroyed, their mass is conserved. Actors use programs constructed from combinators to asynchronously update their own states and the states of other actors in their neighborhoods. The fact that programs and combinators are themselves reified as actors makes it possible to build programs that build programs from combinators of a few primitive types using asynchronous spatial processes that resemble chemistry as much as computation...
2016: Artificial Life
Thomas LaBar, Arend Hintze, Christoph Adami
The role of historical contingency in the origin of life is one of the great unknowns in modern science. Only one example of life exists-one that proceeded from a single self-replicating organism (or a set of replicating hypercycles) to the vast complexity we see today in Earth's biosphere. We know that emergent life has the potential to evolve great increases in complexity, but it is unknown if evolvability is automatic given any self-replicating organism. At the same time, it is difficult to test such questions in biochemical systems...
2016: Artificial Life
Eran Agmon, Alexander J Gates, Randall D Beer
Emergent individuals are often characterized with respect to their viability: their ability to maintain themselves and persist in variable environments. As such individuals interact with an environment, they undergo sequences of structural changes that correspond to their ontogenies. Ultimately, individuals that adapt to their environment, and increase their chances of survival, persist. This article provides an initial step towards a more formal treatment of these concepts. A network of possible ontogenies is uncovered by subjecting a model protocell to sequential perturbations and mapping the resulting structural configurations...
2016: Artificial Life
Micah Brodsky
How might organisms grow into their desired physical forms in spite of environmental and genetic variation? How do they maintain this form in spite of physical insults? This article presents a case study in simulated morphogenesis, using a physics-based model for embryonic epithelial tissue. The challenges of the underlying physics force the introduction of closed-loop controllers for both spatial patterning and geometric structure. Reliable development is achieved not through elaborate control procedures or exact solutions, but through crude layering of independent, overlapping mechanisms...
2016: Artificial Life
Simon Hickenbotham, Susan Stepney
No abstract text is available yet for this article.
2016: Artificial Life
David H Ackley, Elena S Ackley
Traditional digital computing demands perfectly reliable memory and processing, so programs can build structures once then use them forever-but such deterministic execution is becoming ever more costly in large-scale systems. By contrast, living systems, viewed as computations, naturally tolerate fallible hardware by repairing and rebuilding structures even while in use-and suggest ways to compute using massive amounts of unreliable, merely best-effort hardware. However, we currently know little about programming without deterministic execution, in architectures where traditional models of computation-and deterministic ALife models such as the Game of Life-need not apply...
2016: Artificial Life
Tim Taylor, Mark Bedau, Alastair Channon, David Ackley, Wolfgang Banzhaf, Guillaume Beslon, Emily Dolson, Tom Froese, Simon Hickinbotham, Takashi Ikegami, Barry McMullin, Norman Packard, Steen Rasmussen, Nathaniel Virgo, Eran Agmon, Edward Clark, Simon McGregor, Charles Ofria, Glen Ropella, Lee Spector, Kenneth O Stanley, Adam Stanton, Christopher Timperley, Anya Vostinar, Michael Wiser
We describe the content and outcomes of the First Workshop on Open-Ended Evolution: Recent Progress and Future Milestones (OEE1), held during the ECAL 2015 conference at the University of York, UK, in July 2015. We briefly summarize the content of the workshop's talks, and identify the main themes that emerged from the open discussions. Two important conclusions from the discussions are: (1) the idea of pluralism about OEE-it seems clear that there is more than one interesting and important kind of OEE; and (2) the importance of distinguishing observable behavioral hallmarks of systems undergoing OEE from hypothesized underlying mechanisms that explain why a system exhibits those hallmarks...
2016: Artificial Life
Tim Taylor, Joshua E Auerbach, Josh Bongard, Jeff Clune, Simon Hickinbotham, Charles Ofria, Mizuki Oka, Sebastian Risi, Kenneth O Stanley, Jason Yosinski
We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from 1994-when the first WebAL work appeared-up to the present day, together with a brief discussion of relevant precursors. We examine recent projects, from 2010-2015, in greater detail in order to highlight the current state of the art. We follow the survey with a discussion of common themes and methodologies that can be observed in recent work and identify a number of likely directions for future work in this exciting area...
2016: Artificial Life
Rick Janssen, Stefano Nolfi, Pim Haselager, Ida Sprinkhuizen-Kuyper
Coevolving systems are notoriously difficult to understand. This is largely due to the Red Queen effect that dictates heterospecific fitness interdependence. In simulation studies of coevolving systems, master tournaments are often used to obtain more informed fitness measures by testing evolved individuals against past and future opponents. However, such tournaments still contain certain ambiguities. We introduce the use of a phenotypic cluster analysis to examine the distribution of opponent categories throughout an evolutionary sequence...
2016: Artificial Life
(no author information available yet)
No abstract text is available yet for this article.
2016: Artificial Life
Hiroki Sayama, John Rieffel, Sebastian Risi, René Doursat, Hod Lipson
No abstract text is available yet for this article.
2016: Artificial Life
Randal S Olson, David B Knoester, Christoph Adami
Animal grouping behaviors have been widely studied due to their implications for understanding social intelligence, collective cognition, and potential applications in engineering, artificial intelligence, and robotics. An important biological aspect of these studies is discerning which selection pressures favor the evolution of grouping behavior. In the past decade, researchers have begun using evolutionary computation to study the evolutionary effects of these selection pressures in predator-prey models. The selfish herd hypothesis states that concentrated groups arise because prey selfishly attempt to place their conspecifics between themselves and the predator, thus causing an endless cycle of movement toward the center of the group...
2016: Artificial Life
Michał Joachimczak, Reiji Suzuki, Takaya Arita
We show how the concept of metamorphosis, together with a biologically inspired model of multicellular development, can be used to evolve soft-bodied robots that are adapted to two very different tasks, such as being able to move in an aquatic and in a terrestrial environment. Each evolved solution defines two pairs of morphologies and controllers, together with a process of transforming one pair into the other. Animats develop from a single cell and grow through cellular divisions and deaths until they reach an initial larval form adapted to a first environment...
2016: Artificial Life
David Ripps
In the realm of cellular-automata-based artificial life, configurations that self-reproduce employing signals are a more advanced form than those that reproduce holistically by simple fission. One might view those signals as a very rudimentary genetic code, since they guide the formation of the "child" from its "parent." In principle, the signals could mutate to deliver a child better suited to reproduction in this artificial world. But even the simplest signal-based replicator discovered so far requires 58 specific CA transition rules that have been carefully hand-crafted to exactly meet the requirement of self-replication...
2016: Artificial Life
Andrés C Burgos, Daniel Polani
We consider the problem of the evolution of a code within a structured population of agents. The agents try to maximize their information about their environment by acquiring information from the outputs of other agents in the population. A naive use of information-theoretic methods would assume that every agent knows how to interpret the information offered by other agents. However, this assumes that it knows which other agents it observes, and thus which code they use. In our model, however, we wish to preclude that: It is not clear which other agents an agent is observing, and the resulting usable information is therefore influenced by the universality of the code used and by which agents an agent is listening to...
2016: Artificial Life
Filippo Caschera, Vincent Noireaux
Cell-free expression is a technology used to synthesize minimal biological cells from natural molecular components. We have developed a versatile and powerful all-E. coli cell-free transcription-translation system energized by a robust metabolism, with the far objective of constructing a synthetic cell capable of self-reproduction. Inorganic phosphate (iP), a byproduct of protein synthesis, is recycled through polysugar catabolism to regenerate ATP (adenosine triphosphate) and thus supports long-lived and highly efficient protein synthesis in vitro...
2016: Artificial Life
Drew Blount
It is obviously useful to think of evolved individuals in terms of their adaptations, yet the task of empirically classifying traits as adaptations has been claimed by some to be impossible in principle. I reject that claim by construction, introducing a formal method to empirically test whether a trait is an adaptation. The method presented is general, intuitive, and effective at identifying adaptations while remaining agnostic about their adaptive function. The test follows directly from the notion that adaptations arise from variation, heritability, and differential fitness in an evolving population: I operationalize these three concepts at the trait level, formally defining measures of individual traits...
2016: Artificial Life
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