Practical Open-Loop Optimistic Planning

We consider the problem of online planning in a Markov Decision Process when given only access to a generative model, restricted to open-loop policies - i.e. sequences of actions - and under budget constraint. In this setting, the Open-Loop Optimistic Planning (OLOP) algorithm enjoys good theoretical guarantees but is overly conservative in practice, as we show in numerical experiments. We propose a modified version of the algorithm with tighter upper-confidence bounds, KLOLOP, that leads to better practical performances while retaining the sample complexity bound. Finally, we propose an efficient implementation that significantly improves the time complexity of both algorithms

Assessing Importance and Satisfaction Judgments of Intermodal Work Commuters with Electronic Survey Methodology, MTI Report WP 12-01

Recent advances in multivariate methodology provide an opportunity to further the assessment of service offerings in public transportation for work commuting. We offer methodologies that are alternative to direct rating scale and have advantages in the quality and precision of measurement. The alternative of methodology for adaptive conjoint analysis for the measurement of the importance of attributes in service offering is implemented. Rasch scaling methodology is used for the measurement of satisfaction with these attributes. Advantages that these methodologies introduce for assessment of the respective constructs and use of the assessment are discussed. In a first study, the conjoint derived weights were shown to have predictive capabilities in applications to respondent distributions of a fixed total budget to improve overall service offerings. Results with the Rasch model indicate that the attribute measures are reliable and can adequately constitute a composite measure of satisfaction. The Rasch items were also shown to provide a basis to discriminate between privately owned vehicles (POVs) and public transport commuters. Dissatisfaction with uncertainty in travel time and income level of respondents were the best predictors of POV commuting

Spaceflight performance of several types of silicon solar cells on the LIPS 3 satellite

Results from exposure of several types of Solarex silicon cells to a space environment for nearly two years on the LIPS 3 satellite are presented. Experiments include standard thickness (10 mil) cells with and without back surface fields, and ultrathin (2 mil) cells also with and without back surface fields. A comparison between a widely used coverslide adhesive, DC 93-500 and a potential alternate is also presented. The major findings from the data are that the 2 mil cells without a back surface field show the smallest normalized short circuit current degradation and that the 10 mil back surface field cells show the greatest absolute power output for the radiation exposures and temperatures encountered. The new encapsulant (McGhan Nusil CV-2500) exhibits a degradation comparable to DC 93-500. A comparison is made with each of the cell types in this experiment with expectations based on JPL Radiation Handbook data

L0L_0-ARM: Network Sparsification via Stochastic Binary Optimization

We consider network sparsification as an $L_0$-norm regularized binary optimization problem, where each unit of a neural network (e.g., weight, neuron, or channel, etc.) is attached with a stochastic binary gate, whose parameters are jointly optimized with original network parameters. The Augment-Reinforce-Merge (ARM), a recently proposed unbiased gradient estimator, is investigated for this binary optimization problem. Compared to the hard concrete gradient estimator from Louizos et al., ARM demonstrates superior performance of pruning network architectures while retaining almost the same accuracies of baseline methods. Similar to the hard concrete estimator, ARM also enables conditional computation during model training but with improved effectiveness due to the exact binary stochasticity. Thanks to the flexibility of ARM, many smooth or non-smooth parametric functions, such as scaled sigmoid or hard sigmoid, can be used to parameterize this binary optimization problem and the unbiasness of the ARM estimator is retained, while the hard concrete estimator has to rely on the hard sigmoid function to achieve conditional computation and thus accelerated training. Extensive experiments on multiple public datasets demonstrate state-of-the-art pruning rates with almost the same accuracies of baseline methods. The resulting algorithm $L_0$-ARM sparsifies the Wide-ResNet models on CIFAR-10 and CIFAR-100 while the hard concrete estimator cannot. The code is public available at https://github.com/leo-yangli/l0-arm.Comment: Published as a conference paper at ECML 201

Hi-Val: Iterative Learning of Hierarchical Value Functions for Policy Generation

Task decomposition is effective in manifold applications where the global complexity of a problem makes planning and decision-making too demanding. This is true, for example, in high-dimensional robotics domains, where (1) unpredictabilities and modeling limitations typically prevent the manual specification of robust behaviors, and (2) learning an action policy is challenging due to the curse of dimensionality. In this work, we borrow the concept of Hierarchical Task Networks (HTNs) to decompose the learning procedure, and we exploit Upper Confidence Tree (UCT) search to introduce HOP, a novel iterative algorithm for hierarchical optimistic planning with learned value functions. To obtain better generalization and generate policies, HOP simultaneously learns and uses action values. These are used to formalize constraints within the search space and to reduce the dimensionality of the problem. We evaluate our algorithm both on a fetching task using a simulated 7-DOF KUKA light weight arm and, on a pick and delivery task with a Pioneer robot

Cathodoluminescence of nanocrystalline Y2O3:Eu3+ with various Eu3+ concentrations

© The Author(s) 2014. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 License (CC BY, http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse of the work in any medium, provided the original work is properly cited.This article has been made available through the Brunel Open Access Publishing Fund.Herein a study on the preparation and cathodoluminescence of monosized spherical nanoparticles of Y2O3:Eu3+ having a Eu3+ concentration that varies between 0.01 and 10% is described. The luminous efficiency and decay time have been determined at low a current density, whereas cathodoluminescence-microscopy has been carried out at high current density, the latter led to substantial saturation of certain spectral transitions. A novel theory is presented to evaluate the critical distance for energy transfer from Eu3+ ions in S6 to Eu3+ ions in C2 sites. It was found that Y2O3:Eu3+ with 1–2% Eu3+ has the highest luminous efficiency of 16lm/w at 15keV electron energy. Decay times of the emission from 5D0 (C2) and 5D1 (C2) and 5D0 (S6) levels were determined. The difference in decay time from the 5D0 (C2) and 5D1 (C2) levels largely explained the observed phenomena in the cathodoluminescence-micrographs recorded with our field emission scanning electron microscope

Optimization of Design of Space Experiments from the Standpoint of Data Processing Semiannual Report, May 1 - Oct. 31, 1966

Encoding algorithm for processing data from space experiment

Cathodoluminescence of Double Layers of Phosphor Particles

This article has been made available through the Brunel Open Access Publishing Fund.We present radiance measurements of particle layers of ZnO:Zn, Y2O3:Eu and Y2O2S:Eu bombarded with electrons at anode voltages between 1 and 15 kV. The layers described in this work refer to single component layers, double layers and two component mixtures. The phosphor layers are deposited on ITO-coated glass slides by settling; the efficiency of the cathodoluminescence is determined by summing the radiances and luminances in the reflected and transmitted modes respectively. The efficiency of a double layer of Y2O3:Eu on top of ZnO:Zn at high electron energy is significantly larger than the efficiency of a corresponding layer in which the two components are mixed. This result is interpreted in terms of the penetration-model, which predicts a larger efficiency for a high-voltage phosphor on top of a low-voltage phosphor. When a layer of the low-voltage phosphor ZnO:Zn is on top of the high-voltage phosphor Y2O3:Eu, we also observe a higher efficiency than that of the corresponding layer with both components mixed. In this case the efficiency increases due to suppression of charging in the Y2O3:Eu layer. Double layers of ZnO:Zn and Y2O2S:Eu did not show enhanced efficiency, because the size of the Y2O2S:Eu particles was too large to evoke the penetration effect. © The Author(s) 2014. Published by ECS