3,954 research outputs found
Online Meta-learning by Parallel Algorithm Competition
The efficiency of reinforcement learning algorithms depends critically on a
few meta-parameters that modulates the learning updates and the trade-off
between exploration and exploitation. The adaptation of the meta-parameters is
an open question in reinforcement learning, which arguably has become more of
an issue recently with the success of deep reinforcement learning in
high-dimensional state spaces. The long learning times in domains such as Atari
2600 video games makes it not feasible to perform comprehensive searches of
appropriate meta-parameter values. We propose the Online Meta-learning by
Parallel Algorithm Competition (OMPAC) method. In the OMPAC method, several
instances of a reinforcement learning algorithm are run in parallel with small
differences in the initial values of the meta-parameters. After a fixed number
of episodes, the instances are selected based on their performance in the task
at hand. Before continuing the learning, Gaussian noise is added to the
meta-parameters with a predefined probability. We validate the OMPAC method by
improving the state-of-the-art results in stochastic SZ-Tetris and in standard
Tetris with a smaller, 1010, board, by 31% and 84%, respectively, and
by improving the results for deep Sarsa() agents in three Atari 2600
games by 62% or more. The experiments also show the ability of the OMPAC method
to adapt the meta-parameters according to the learning progress in different
tasks.Comment: 15 pages, 10 figures. arXiv admin note: text overlap with
arXiv:1702.0311
Electrostatics in wind-blown sand
Wind-blown sand, or "saltation," is an important geological process, and the
primary source of atmospheric dust aerosols. Significant discrepancies exist
between classical saltation theory and measurements. We show here that these
discrepancies can be resolved by the inclusion of sand electrification in a
physically based saltation model. Indeed, we find that electric forces enhance
the concentration of saltating particles and cause them to travel closer to the
surface, in agreement with measurements. Our results thus indicate that sand
electrification plays an important role in saltation.Comment: 4 journal pages, 5 figures, and supplementary material. Article is in
press at PR
High spin polarization in the ferromagnetic filled skutterudites KFe4Sb12 and NaFe4Sb12
The spin polarization of ferromagnetic alkali-metal iron antimonides KFe4Sb12
and NaFe4Sb12 is studied by point-contact Andreev reflection using
superconducting Nb and Pb tips. From these measurements an intrinsic transport
spin polarization Pt of 67% and 60% for the K and Na compound, respectively, is
inferred which establishes these materials as a new class of highly spin
polarized ferromagnets. The results are in accord with band structure
calculations within the local spin density approximation (LSDA) that predict
nearly 100% spin polarization in the density of states. We discuss the impact
of calculated Fermi velocities and spin fluctuations on Pt.Comment: Pdf file with fi
The 'Paris-end' of town? Urban typology through machine learning
The confluence of recent advances in availability of geospatial information,
computing power, and artificial intelligence offers new opportunities to
understand how and where our cities differ or are alike. Departing from a
traditional `top-down' analysis of urban design features, this project analyses
millions of images of urban form (consisting of street view, satellite imagery,
and street maps) to find shared characteristics. A (novel) neural network-based
framework is trained with imagery from the largest 1692 cities in the world and
the resulting models are used to compare within-city locations from Melbourne
and Sydney to determine the closest connections between these areas and their
international comparators. This work demonstrates a new, consistent, and
objective method to begin to understand the relationship between cities and
their health, transport, and environmental consequences of their design. The
results show specific advantages and disadvantages using each type of imagery.
Neural networks trained with map imagery will be highly influenced by the mix
of roads, public transport, and green and blue space as well as the structure
of these elements. The colours of natural and built features stand out as
dominant characteristics in satellite imagery. The use of street view imagery
will emphasise the features of a human scaled visual geography of streetscapes.
Finally, and perhaps most importantly, this research also answers the age-old
question, ``Is there really a `Paris-end' to your city?''
Efeito de herbicidas sobre a taxa de transporte de elétrons e o acúmulo de matéria seca em tomateiro.
Objetivou-se com este trabalho avaliar o efeito dos herbicidas metribuzin e carfentrazone sobre a taxa de transporte de elétrons (ETR) do fotossistema II (FSII) e o acúmulo de matéria seca em tomateiro.CD-ROM. Suplemento. Trabalho apresentado no 51. Congresso Brasileiro de Olericultura, Viçosa, MG
कोवलम, तमीलनाडु के तटीय क्षेत्रों में उपलब्ध सुरमई मछली के मत्सयन स्थल का जिओस्पेशियल नक्शा
कृपया पूरा लेखा पढ
Vibrational Spectra of a Mechanosensitive Channel
We report the simulated vibrational spectra of a mechanosensitive membrane channel in different gating states. Our results show that while linear absorption is insensitive to structural differences, linear dichroism and sum-frequency generation spectroscopies are sensitive to the orientation of the transmembrane helices, which is changing during the opening process. Linear dichroism cannot distinguish an intermediate structure from the closed structure, but sum-frequency generation can. In addition, we find that two-dimensional infrared spectroscopy can be used to distinguish all three investigated gating states of the mechanosensitive membrane channel.
Impact demagnetization of the Martian crust: Current knowledge and future directions
The paleomagnetism of the Martian crust has important implications for the history of the dynamo, the intensity of the ancient magnetic field, and the composition of the crust. Modification of crustal magnetization by impact cratering is evident from the observed lack of a measurable crustal field (at spacecraft altitude) within the youngest large impact basins (e.g., Hellas, Argyre and Isidis). It is hoped that comparisons of the magnetic intensity over impact structures, forward modeling of subsurface magnetization, and experimental results of pressure-induced demagnetization of rocks and minerals will provide constraints on the primary magnetic mineralogy in the Martian crust. Such an effort requires: (i) accurate knowledge of the spatial distribution of the shock pressures around impact basins, (ii) crustal magnetic intensity maps of adequate resolution over impact structures, and (iii) determination of demagnetization properties for individual rocks and minerals under compression. In this work, we evaluate the current understanding of these three conditions and compile the available experimental pressure demagnetization data on samples bearing (titano-) magnetite, (titano-) hematite, and pyrrhotite. We find that all samples demagnetize substantially at pressures of a few GPa and that the available data support significant modification of the crustal magnetic field from both large and small impact events. However, the amount of demagnetization with applied pressure does not vary significantly among the possible carrier phases. Therefore, the presence of individual mineral phases on Mars cannot be determined from azimuthally averaged demagnetization profiles over impact basins at present. The identification of magnetic mineralogy on Mars will require more data on pressure demagnetization of thermoremanent magnetization and forward modeling of the crustal field subject to a range of plausible initial field and demagnetization patterns.United States. National Aeronautics and Space Administration (NNG04GD17G)United States. National Aeronautics and Space Administration (NNX07AQ69G)United States. National Aeronautics and Space Administration (NNX06AD14G
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