128,846 research outputs found

    A Computational Model of Symbiotic Composition in Evolutionary Transitions

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    Several of the major transitions in evolutionary history, such as the symbiogenic origin of eukaryotes from prokaryotes, share the feature that existing entities became the components of composite entities at a higher level of organisation. This composition of pre-adapted extant entities into a new whole is a fundamentally different source of variation from the gradual accumulation of small random variations, and it has some interesting consequences for issues of evolvability. Intuitively, the pre-adaptation of sets of features in reproductively independent specialists suggests a form of ‘divide and conquer’ decomposition of the adaptive domain. Moreover, the compositions resulting from one level may become the components for compositions at the next level, thus scaling-up the variation mechanism. In this paper, we explore and develop these concepts using a simple abstract model of symbiotic composition to examine its impact on evolvability. To exemplify the adaptive capacity of the composition model, we employ a scale-invariant fitness landscape exhibiting significant ruggedness at all scales. Whilst innovation by mutation and by conventional evolutionary algorithms becomes increasingly more difficult as evolution continues in this landscape, innovation by composition is not impeded as it discovers and assembles component entities through successive hierarchical levels

    Coevolutionary Dynamics in a Minimal Substrate

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    One of the central difficulties of coevolutionary methods arises from 'intransitive superiority' - in a two-player game, for example, the fact that A beats B, and B beats C, does not exclude the possibility that C beats A. Such cyclic superiority in a coevolutionary substrate is hypothesized to cause cycles in the dynamics of the population such that it 'chases its own tail' - traveling through some part of strategy space more than once despite apparent improvement with each step. It is often difficult to know whether an application domain contains such difficulties and to verify this hypothesis in the failure of a given coevolutionary set-up. In this paper we wish to elucidate some of the issues and concepts in an abstract domain where the dynamics of coevolution can be studied simply and directly. We define three simple 'number games' that illustrate intransitive superiority and resultant oscillatory dynamics, as well as some other relevant concepts. These include the distinction between a player's perceived performance and performance with respect to an external metric, and the significance of strategies with a multi-dimensional nature. These features alone can also cause oscillatory behavior and coevolutionary failure

    Embodied Evolution: Distributing an evolutionary algorithm in a population of robots

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    We introduce Embodied Evolution (EE) as a new methodology for evolutionary robotics (ER). EE uses a population of physical robots that autonomously reproduce with one another while situated in their task environment. This constitutes a fully distributed evolutionary algorithm embodied in physical robots. Several issues identified by researchers in the evolutionary robotics community as problematic for the development of ER are alleviated by the use of a large number of robots being evaluated in parallel. Particularly, EE avoids the pitfalls of the simulate-and-transfer method and allows the speed-up of evaluation time by utilizing parallelism. The more novel features of EE are that the evolutionary algorithm is entirely decentralized, which makes it inherently scalable to large numbers of robots, and that it uses many robots in a shared task environment, which makes it an interesting platform for future work in collective robotics and Artificial Life. We have built a population of eight robots and successfully implemented the first example of Embodied Evolution by designing a fully decentralized, asynchronous evolutionary algorithm. Controllers evolved by EE outperform a hand-designed controller in a simple application. We introduce our approach and its motivations, detail our implementation and initial results, and discuss the advantages and limitations of EE

    Circus, Pollack Brothers (B)

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    Pollack Brothers Circus clown directing a group of boys and girls to the penny stage entrance

    Symbiotic Composition and Evolvability

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    Several of the Major Transitions in natural evolution, such as the symbiogenic origin of eukaryotes from prokaryotes, share the feature that existing entities became the components of composite entities at a higher level of organisation. This composition of pre-adapted extant entities into a new whole is a fundamentally different source of variation from the gradual accumulation of small random variations, and it has some interesting consequences for issues of evolvability. In this paper we present a very abstract model of 'symbiotic composition' to explore its possible impact on evolvability. A particular adaptive landscape is used to exemplify a class where symbiotic composition has an adaptive advantage with respect to evolution under mutation and sexual recombination. Whilst innovation using conventional evolutionary algorithms becomes increasingly more difficult as evolution continues in this problem, innovation via symbiotic composition continues through successive hierarchical levels unimpeded. <br/

    1966-69 -- Correspondence, Hebrew University AFHU -- letter, 1969-04-28

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    Letter from Pollack, Eileen to Sabin, Albert B. dated 1969-04-28.Sabin Collection Fair Use Policy</a

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    How Symbiosis Can Guide Evolution

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    Hinton and Nowlan have demonstrated a model of how lifetime plasticity can guide evolution. They show how acquired traits change the shape of the reward landscape in which subsequent genetic variation takes place, and in so doing encourage the discovery of equivalent heritable traits. This enables the seemingly Lamarkian inheritance of acquired characteristics without the direct transfer of information from the phenotype to the genotype. This paper draws direct inspiration from their work to illustrate a different phenomenon. We demonstrate how the formation of symbiotic relationships in an ecosystem can guide the course of subsequent genetic variation. This phenomenon can be described as two phases: First, symbiotic groups find solutions where individual organisms cannot, simply because lifetime interaction produces new combinations of abilities more rapidly than the relatively slow genetic variation of individuals. Second, these symbiotic groups subsequently change the shape of the reward landscape for evolution, providing a gradient that guides genetic variation to the same solution. Ultimately, an individual organism exhibits the capabilities formerly exhibited by the group. This process enables the combination of characteristics from organisms of distinct species without direct transfer of genetic information
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