GPU Based Path Integral Control with Learned Dynamics

We present an algorithm which combines recent advances in model based path integral control with machine learning approaches to learning forward dynamics models. We take advantage of the parallel computing power of a GPU to quickly take a massive number of samples from a learned probabilistic dynamics model, which we use to approximate the path integral form of the optimal control. The resulting algorithm runs in a receding-horizon fashion in realtime, and is subject to no restrictive assumptions about costs, constraints, or dynamics. A simple change to the path integral control formulation allows the algorithm to take model uncertainty into account during planning, and we demonstrate its performance on a quadrotor navigation task. In addition to this novel adaptation of path integral control, this is the first time that a receding-horizon implementation of iterative path integral control has been run on a real system.Comment: 6 pages, NIPS 2014 - Autonomously Learning Robots Worksho

A Dirac Sea and thermodynamic equilibrium for the quantized three-wave interaction

The classical version of the three wave interaction models the creation and destruction of waves; the quantized version models the creation and destruction of particles. The quantum three wave interaction is described and the Bethe Ansatz for the eigenfunctions is given in closed form. The Bethe equations are derived in a rigorous fashion and are shown to have a thermodynamic limit. The Dirac sea of negative energy states is obtained as the infinite density limit. Finite particle/hole excitations are determined and the asymptotic relation of energy and momentum is obtained. The Yang-Yang functional for the relative free energy of finite density excitations is constructed and is shown to be convex and bounded below. The equations of thermal equilibrium are obtained

Sound Source Localization in a Multipath Environment Using Convolutional Neural Networks

The propagation of sound in a shallow water environment is characterized by boundary reflections from the sea surface and sea floor. These reflections result in multiple (indirect) sound propagation paths, which can degrade the performance of passive sound source localization methods. This paper proposes the use of convolutional neural networks (CNNs) for the localization of sources of broadband acoustic radiated noise (such as motor vessels) in shallow water multipath environments. It is shown that CNNs operating on cepstrogram and generalized cross-correlogram inputs are able to more reliably estimate the instantaneous range and bearing of transiting motor vessels when the source localization performance of conventional passive ranging methods is degraded. The ensuing improvement in source localization performance is demonstrated using real data collected during an at-sea experiment.Comment: 5 pages, 5 figures, Final draft of paper submitted to 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 15-20 April 2018 in Calgary, Alberta, Canada. arXiv admin note: text overlap with arXiv:1612.0350

Ship-based nitric acid measurements in the Gulf of Maine during New England Air Quality Study 2002

Gas phase nitric acid (HNO3) was measured at 5-min resolution on board the National Oceanographic and Atmospheric Administration (NOAA) research vessel Ronald H. Brown during the second leg (29 July to 10 August) of the New England Air Quality Study (NEAQS) 2002 cruise. A primary objective of the cruise was to improve understanding of the oxidation of NOx in, and removal of the oxidation products from, the polluted marine boundary layer east of northeastern North America. For the first 9 days of this leg the ship remained north of Cape Cod, and the cruise track did not extend much farther north than the New Hampshire-Maine border. During this period, HNO3 averaged 1.1 ppb and accounted for 19% of total reactive nitrogen oxides (measured NOy). On all days, peak HNO3 mixing ratios were observed in the early afternoon (average 2.3 ppb), at levels twofold to fourfold higher than the minima around sunrise and sunset. In these daytime peaks, HNO3/NOy averaged 28%. There were secondary nighttime peaks of HNO3 (0.9 ppb average), when HNO3 accounted for 16% of total reactive nitrogen oxides. This pronounced diurnal pattern confirms that production, and subsequent deposition, of HNO3 in the polluted marine boundary layer downwind of New England removes a significant fraction of the NOx exported to the atmosphere over the Gulf of Maine. Nitric acid was correlated with O3, particularly during the early afternoon interval when both molecules reached maximum mixing ratios (R2 = 0.66). The ozone production efficiency (OPE) inferred from the slope (10 ppb O3/ppb HNO3) was similar to the OPE of 9 estimated at the Atmospheric Investigation, Regional Modeling, Analysis and Prediction (AIRMAP) Thompson Farm station in coastal New Hampshire during the study period

Curbing Tax Expenditures

Reviews trends in tax expenditures and their effects and examines three options for raising tax revenue by applying limits to large and widely utilized tax preferences: a fixed percentage credit, a cap based on income, and a constant percentage reduction