Open-Ended Evolutionary Robotics: an Information Theoretic Approach

This paper is concerned with designing self-driven fitness functions for Embedded Evolutionary Robotics. The proposed approach considers the entropy of the sensori-motor stream generated by the robot controller. This entropy is computed using unsupervised learning; its maximization, achieved by an on-board evolutionary algorithm, implements a "curiosity instinct", favouring controllers visiting many diverse sensori-motor states (sms). Further, the set of sms discovered by an individual can be transmitted to its offspring, making a cultural evolution mode possible. Cumulative entropy (computed from ancestors and current individual visits to the sms) defines another self-driven fitness; its optimization implements a "discovery instinct", as it favours controllers visiting new or rare sensori-motor states. Empirical results on the benchmark problems proposed by Lehman and Stanley (2008) comparatively demonstrate the merits of the approach

First principles calculations of oxygen adsorption on the UN (001) surface

Fabrication, handling and disposal of nuclear fuel materials require comprehensive knowledge of their surface morphology and reactivity. Due to unavoidable contact with air components (even at low partial pressures), UN samples contain considerable amount of oxygen impurities affecting fuel properties. The basic properties of O atoms adsorbed on the UN(001) surface are simulated here combining the two first principles calculation methods based on the plane wave basis set and that of the localized atomic orbitals.Comment: 9 page

Locating and Quantifying Broadband Fan Sources Using In-Duct Microphones

In-duct beamforming techniques have been developed for locating broadband noise sources on a low-speed fan and quantifying the acoustic power in the inlet and aft fan ducts. The NASA Glenn Research Center's Advanced Noise Control Fan was used as a test bed. Several of the blades were modified to provide a broadband source to evaluate the efficacy of the in-duct beamforming technique. Phased arrays consisting of rings and line arrays of microphones were employed. For the imaging, the data were mathematically resampled in the frame of reference of the rotating fan. For both the imaging and power measurement steps, array steering vectors were computed using annular duct modal expansions, selected subsets of the cross spectral matrix elements were used, and the DAMAS and CLEAN-SC deconvolution algorithms were applied

The movement advantage in famous and unfamiliar faces: a comparison of point-light displays and shape-normalised avatar stimuli.

Facial movement may provide cues to identity, by supporting the extraction of face shape information via structure-from-motion, or via characteristic patterns of movement. Currently, it is unclear whether familiar and unfamiliar faces derive the same benefit from these mechanisms. This study examined the movement advantage by asking participants to match moving and static images of famous and unfamiliar faces to facial point-light displays (PLDs) or shape-normalised avatars in a same/different task (experiment 1). In experiment 2 we also used a same/different task, but participants matched from PLD to PLD or from avatar to avatar. In both experiments, unfamiliar face matching was more accurate for PLDs than for avatars, but there was no effect of stimulus type on famous faces. In experiment 1, there was no movement advantage, but in experiment 2, there was a significant movement advantage for famous and unfamiliar faces. There was no evidence that familiarity increased the movement advantage. For unfamiliar faces, results suggest that participants were relying on characteristic movement patterns to match the faces, and did not derive any extra benefit from the structure-from-motion cues in the PLDs. The results indicate that participants may use static and movement-based cues in a flexible manner when matching famous and unfamiliar faces

Representing some non-representable matroids

We extend the notion of representation of a matroid to algebraic structures that we call skew partial fields. Our definition of such representations extends Tutte's definition, using chain groups. We show how such representations behave under duality and minors, we extend Tutte's representability criterion to this new class, and we study the generator matrices of the chain groups. An example shows that the class of matroids representable over a skew partial field properly contains the class of matroids representable over a skew field. Next, we show that every multilinear representation of a matroid can be seen as a representation over a skew partial field. Finally we study a class of matroids called quaternionic unimodular. We prove a generalization of the Matrix Tree theorem for this class.Comment: 29 pages, 2 figure

Phylogeny of Geomydoecus and Thomomydoecus pocket gopher lice (phthiraptera, trichodectidae) inferred from cladistic analysis of adult and first instar morphology

The phylogeny for all 122 species and subspecies of chewing lice of the genera Geomydoecus and Thomomydoecus (Phthiraptera: Trichodectidae) hosted by pocket gophers (Rodentia: Geomyidae) is estimated by a cladistic analysis of fifty-eight morphological characters obtained from adults and first instars. The data set has considerable homoplasy, but still contains phylogenetic information. The phylogeny obtained is moderately resolved and, with some notable exceptions, supports the species complexes proposed by Hellenthal and Price over the the last two decades. The subgenera G. (Thaelerius) and T. (Thomomydoecus) are both shown to be monophyletic, but the monophly of subgenus T. (Jamespattonius) could not be confirmed, perhaps due to the lack of first-instar data for one of its component species. The nominate subgenus of Geomydoecus may be monophyletic, but our cladogram was insufficiently resolved to corroborate this. Mapping the pocket gopher hosts onto the phylogeny reveals a consistent pattern of louse clades being restricted to particular genera or subgenera of gophers, but the history of the host-parasite association appears complex and will require considerable effort to resolve

Segurança Na Mudança Direta De Natalizumabe Para Fingolimode Em Um Grupo De Pacientes Com Esclerose Múltipla E Positivos Para Jcv

To assess safety of the switch between natalizumab and fingolimod without a washout period. Methods: Prospective data on 25 JCV positive patients who underwent this medication switch were collected and analyzed. Results: After a median period of nine months from the medication switch, there were no safety issues to report. The patients had good disease control and no adverse events were reported. Conclusion: Washout may not be necessary in daily practice when switching from natalizumab to fingolimod. Expertise on multiple sclerosis management, however, is essential for drug switching. © 2016, Associacao Arquivos de Neuro-Psiquiatria. All Rights Reserved.74865065

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio