208 research outputs found

    Discovering the Elite Hypervolume by Leveraging Interspecies Correlation

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    Evolution has produced an astonishing diversity of species, each filling a different niche. Algorithms like MAP-Elites mimic this divergent evolutionary process to find a set of behaviorally diverse but high-performing solutions, called the elites. Our key insight is that species in nature often share a surprisingly large part of their genome, in spite of occupying very different niches; similarly, the elites are likely to be concentrated in a specific "elite hypervolume" whose shape is defined by their common features. In this paper, we first introduce the elite hypervolume concept and propose two metrics to characterize it: the genotypic spread and the genotypic similarity. We then introduce a new variation operator, called "directional variation", that exploits interspecies (or inter-elites) correlations to accelerate the MAP-Elites algorithm. We demonstrate the effectiveness of this operator in three problems (a toy function, a redundant robotic arm, and a hexapod robot).Comment: In GECCO 201

    Properties of Nucleon Resonances by means of a Genetic Algorithm

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    We present an optimization scheme that employs a Genetic Algorithm (GA) to determine the properties of low-lying nucleon excitations within a realistic photo-pion production model based upon an effective Lagrangian. We show that with this modern optimization technique it is possible to reliably assess the parameters of the resonances and the associated error bars as well as to identify weaknesses in the models. To illustrate the problems the optimization process may encounter, we provide results obtained for the nucleon resonances Δ\Delta(1230) and Δ\Delta(1700). The former can be easily isolated and thus has been studied in depth, while the latter is not as well known experimentally.Comment: 12 pages, 10 figures, 3 tables. Minor correction

    Analysis of objectives relationships in multiobjective problems using trade-off region maps

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    Understanding the relationships between objectives in many-objective optimisation problems is desirable in order to develop more effective algorithms. We propose a techniquefor the analysis and visualisation of complex relationships between many (three or more) objectives. This technique looks at conflicting, harmonious and independent objectives relationships from different perspectives. To do that, it uses correlation, trade-off regions maps and scatter-plots in a four step approach. We apply the proposed technique to a set of instances of the well-known multiobjective multidimensional knapsack problem. The experimental results show that with the proposed technique we can identify local and complex relationships between objectives, trade-offs not derived from pairwise relationships, gaps in the fitness landscape, and regions of interest. Such information can be used to tailor the development of algorithms

    Dominance Based Crossover Operator for Evolutionary Multi-objective Algorithms

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    In spite of the recent quick growth of the Evolutionary Multi-objective Optimization (EMO) research field, there has been few trials to adapt the general variation operators to the particular context of the quest for the Pareto-optimal set. The only exceptions are some mating restrictions that take in account the distance between the potential mates - but contradictory conclusions have been reported. This paper introduces a particular mating restriction for Evolutionary Multi-objective Algorithms, based on the Pareto dominance relation: the partner of a non-dominated individual will be preferably chosen among the individuals of the population that it dominates. Coupled with the BLX crossover operator, two different ways of generating offspring are proposed. This recombination scheme is validated within the well-known NSGA-II framework on three bi-objective benchmark problems and one real-world bi-objective constrained optimization problem. An acceleration of the progress of the population toward the Pareto set is observed on all problems

    Synthesis and Characterization of Cobalt(II) N,N′‑Diphenylazodioxide Complexes

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    Removal of chloride from CoCl2 with TlPF6 in acetonitrile, followed by addition of excess nitrosobenzene, yielded the eight-coordinate cobalt(II) complex salt [Co{Ph(O)NN(O)- Ph}4](PF6)2, shown by single-crystal X-ray analysis to have a distorted tetragonal geometry. The analogous treatment of the bipyridyl complex Co(bpy)Cl2 yielded the mixed-ligand cobalt(II) complex salt [Co(bpy){Ph(O)NN(O)Ph}2](PF6)2, whose singlecrystal X-ray structure displays a trigonal prismatic geometry, similar to that of the iron(II) cation in the previously known complex salt [Fe{Ph(O)NN(O)Ph}3](FeCl4)2. The use of TlPF6 to generate solvated metal complex cations from chloride salts or chlorido complexes, followed by the addition of nitrosobenzene, is shown to be a useful synthetic strategy for the preparation of azodioxide complex cations with the noncoordinating, diamagnetic PF6 − counteranion. Coordination number appears to be more important than d electron count in determining the geometry and metal−ligand bond distances of diphenylazodioxide complexes

    Observation of the Dynamic Beta Effect at CESR with CLEO

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    Using the silicon strip detector of the CLEO experiment operating at the Cornell Electron-positron Storage Ring (CESR), we have observed that the horizontal size of the luminous region decreases in the presence of the beam-beam interaction from what is expected without the beam-beam interaction. The dependence on the bunch current agrees with the prediction of the dynamic beta effect. This is the first direct observation of the effect.Comment: 9 page uuencoded postscript file, postscritp file also available through http://w4.lns.cornell.edu/public/CLNS, submitted to Phys. Rev.

    Mathematical Identification of Critical Reactions in the Interlocked Feedback Model

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    Dynamic simulations are necessary for understanding the mechanism of how biochemical networks generate robust properties to environmental stresses or genetic changes. Sensitivity analysis allows the linking of robustness to network structure. However, it yields only local properties regarding a particular choice of plausible parameter values, because it is hard to know the exact parameter values in vivo. Global and firm results are needed that do not depend on particular parameter values. We propose mathematical analysis for robustness (MAR) that consists of the novel evolutionary search that explores all possible solution vectors of kinetic parameters satisfying the target dynamics and robustness analysis. New criteria, parameter spectrum width and the variability of solution vectors for parameters, are introduced to determine whether the search is exhaustive. In robustness analysis, in addition to single parameter sensitivity analysis, robustness to multiple parameter perturbation is defined. Combining the sensitivity analysis and the robustness analysis to multiple parameter perturbation enables identifying critical reactions. Use of MAR clearly identified the critical reactions responsible for determining the circadian cycle in the Drosophila interlocked circadian clock model. In highly robust models, while the parameter vectors are greatly varied, the critical reactions with a high sensitivity are uniquely determined. Interestingly, not only the per-tim loop but also the dclk-cyc loop strongly affect the period of PER, although the dclk-cyc loop hardly changes its amplitude and it is not potentially influential. In conclusion, MAR is a powerful method to explore wide parameter space without human-biases and to link a robust property to network architectures without knowing the exact parameter values. MAR identifies the reactions critically responsible for determining the period and amplitude in the interlocked feedback model and suggests that the circadian clock intensively evolves or designs the kinetic parameters so that it creates a highly robust cycle

    Facilitating Next-Generation Pre-Exposure Prophylaxis Clinical Trials Using HIV Recent Infection Assays: A Consensus Statement from the Forum HIV Prevention Trial Design Project

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    Standard-of-care HIV pre-exposure prophylaxis (PrEP) is highly efficacious, but uptake of and persistence on a daily oral pill is low in many settings. Evaluation of alternate PrEP products will require innovation to avoid the unpractically large sample sizes in noninferiority trials. We propose estimating HIV incidence in people not on PrEP as an external counterfactual to which on-PrEP incidence in trial subjects can be compared. HIV recent infection testing algorithms (RITAs), such as the limiting antigen avidity assay plus viral load used on specimens from untreated HIV positive people identified during screening, is one possible approach. Its feasibility is partly dependent on the sample size needed to ensure adequate power, which is impacted by RITA performance, the number of recent infections identified, the expected efficacy of the intervention, and other factors. Screening sample sizes to support detection of an 80% reduction in incidence for 3 key populations are more modest, and comparable to the number of participants in recent phase III PrEP trials. Sample sizes would be significantly larger in populations with lower incidence, where the false recency rate is higher or if PrEP efficacy is expected to be lower. Our proposed counterfactual approach appears to be feasible, offers high statistical power, and is nearly contemporaneous with the on-PrEP population. It will be important to monitor the performance of this approach during new product development for HIV prevention. If successful, it could be a model for preventive HIV vaccines and prevention of other infectious diseases
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