This paper is devoted to the eeects of tness noise in EAs (evolutionary algorithms). After a short introduction to the history of this research eld, the performance of GAs (genetic algorithms) and ESs (evolution strategies) on the hyper-sphere test function is evaluated. It will be shown that the main eeects of noise { the decrease of convergence velocity and the residual location error R 1 { a...

The deployment of versatile robot systems in diverse environments requires intuitive approaches for humans to flexibly teach them new skills. In our present work, we investigate different user feedback types a real movement skill. We compare as star ratings on an absolute scale single roll-outs versus preference-based pairwise comparisons with respective optimization algorithms (i.e., variation...

A subset of HIV-1-infected patients known as elite controllers or suppressors (ES) control the virus naturally. We have previously demonstrated sequence discordance between proviral and plasma gag clones in ES, much of which can be attributed to selective pressure from the host (J. R. Bailey, T. M. Williams, R. F. Siliciano, and J. N. Blankson, J. Exp. Med. 203:1357-1369, 2006). However, it is ...

Natural populations inhabiting the same environment often independently evolve the same phenotype. Is this replicated evolution a result of genetic constraints imposed by patterns of genetic covariation? We looked for associations between directions of morphological divergence and the orientation of the genetic variance-covariance matrix (G) by using an experimental system of morphological evol...

In the context of numerical optimization, this paper develops a methodology to analyze the linear convergence of comparison-based step-size adaptive randomized search (CB-SARS), a class of probabilistic derivative-free optimization algorithms where the function is solely used through comparisons of candidate solutions. Various algorithms are included in the class of CB-SARS algorithms. On the o...

Enterprise Systems Implementation Methodology (ESIM) is considered to be a critical factor for successful Enterprise Systems (ES) implementations. In spite of ESIM’s potential and significance for practice, little attention has been paid to this object of study in ES literature. Moreover, current studies reveal contradictory findings and provide a fragmented understanding. The purpose of this p...

Scenario-based optimization is a problem class often occurring in finance, planning and control. While the standard approach is usually based on linear stochastic programming, this paper develops an Evolution Strategy (ES) that can be used to treat nonlinear planning problems arising from Value at Risk (VaR)-constraints and not necessarily proportional transaction costs. Due to the VaR-constrai...

Real-parameter blackbox optimization using evolution strategies (ES) is often applied when the fitness function or its characteristics are not explicitly given. The evaluation of fitness and feasibility might be expensive. In the past, different surrogate model (SM) approaches have been proposed to address this issue. In our previous work, local feasibility SM have been proposed, which are trai...

Biological evolution gives rise to self-organizing phenomena. Inspired by this theory, directed variation is added to the ( , ) evolution strategies (ES) algorithm and it is called directed variation ES (DVES). In DVES, some neighboring individuals in the population mutate correlatively according to the distribution of the whole population. Experimental results showed that, with the same number...

We study the theoretical capacity to statistically learn local landscape information by Evolution Strategies (ESs). Specifically, we investigate the covariance matrix when constructed by ESs operating with the selection operator alone. We model continuous generation of candidate solutions about quadratic basins of attraction, with deterministic selection of the decision vectors that minimize th...