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

Steady-State and Transient Currents in Organic Liquids by Injection from a Tunnel Cathode

Experimental data are presented on the currents induced in organic liquids by injection from a tunnel cathode. The injection level was varied over a wide range resulting in almost no space‐charge limitation to almost complete space‐charge limitation. Results were different from that usually observed in solids, in that at low fields, the steady‐state current was proportional to V², while at high fields the current was proportional to V. By proper choice of electrode spacing and applied voltage, space‐charge‐limited current transients as low as 10⁻¹¹ A∕cm² and 5 sec transit times were observed. A smooth transition between the electrode‐limited and the space‐charge limited regimes was achieved by varying the junction voltage that varied the injection level

The Starburst in the Central Kiloparsec of Markarian 231

We present VLBA observations at 0.33 and 0.61 GHz, and VLA observations between 5 and 22 GHz, of subkiloparsec scale radio emission from Mrk 231. In addition to jet components clearly associated with the AGN, we also find a smooth extended component of size 100 - 1000 pc most probably related to the purported massive star forming disk in Mrk 231. The diffuse radio emission from the disk is found to have a steep spectrum at high frequencies, characteristic of optically thin synchrotron emission. The required relativistic particle density in the disk can be produced by a star formation rate of 220 Msolar/yr in the central kiloparsec. At low frequencies the disk is absorbed, most likely by ionized gas with an emission measure of 8 x 10^5 pc cm-6. We have also identified 4 candidate radio supernovae that, if confirmed, represent direct evidence for ongoing star formation in the central kiloparsec.Comment: in press at ApJ for v. 519 July 1999, 14 page LaTeX document includes 6 postscript figure

Fe XVII X-ray Line Ratios for Accurate Astrophysical Plasma Diagnostics

New laboratory measurements using an Electron Beam Ion Trap (EBIT) and an x-ray microcalorimeter are presented for the n=3 to n=2 Fe XVII emission lines in the 15 {\AA} to 17 {\AA} range, along with new theoretical predictions for a variety of electron energy distributions. This work improves upon our earlier work on these lines by providing measurements at more electron impact energies (seven values from 846 to 1185 eV), performing an in situ determination of the x-ray window transmission, taking steps to minimize the ion impurity concentrations, correcting the electron energies for space charge shifts, and estimating the residual electron energy uncertainties. The results for the 3C/3D and 3s/3C line ratios are generally in agreement with the closest theory to within 10%, and in agreement with previous measurements from an independent group to within 20%. Better consistency between the two experimental groups is obtained at the lowest electron energies by using theory to interpolate, taking into account the significantly different electron energy distributions. Evidence for resonance collision effects in the spectra is discussed. Renormalized values for the absolute cross sections of the 3C and 3D lines are obtained by combining previously published results, and shown to be in agreement with the predictions of converged R-matrix theory. This work establishes consistency between results from independent laboratories and improves the reliability of these lines for astrophysical diagnostics. Factors that should be taken into account for accurate diagnostics are discussed, including electron energy distribution, polarization, absorption/scattering, and line blends.Comment: 29 pages, including 7 figure

Hot electron injection into dense argon, nitrogen, and hydrogen

Hot electrons have been injected into very dense argon, nitrogen, and hydrogen gases and liquids. The current‐voltage characteristics are experimentally determined for densities (N) of argon, nitrogen, and hydrogen ranging from about 10²⁰ to 10²² cm⁻³ and applied fields (E) ranging from about 10 to 10⁴ V cm⁻¹. The argon data show a square root E∕N dependence of the current. The nitrogen and hydrogen data show a complicated dependence of the current on E∕N due to the rapid thermalization in the region of the image potential of the injected electrons through inelastic collision processes not present in argon. A hydrodynamic‐two‐fluid model is developed to analyze the nitrogen and hydrogen data. From the analysis of our data, we obtain the density dependence of the momentum exchange scattering cross section and the energy relaxation time for the injected hot electrons

Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks

Deep neural networks have emerged as a widely used and effective means for tackling complex, real-world problems. However, a major obstacle in applying them to safety-critical systems is the great difficulty in providing formal guarantees about their behavior. We present a novel, scalable, and efficient technique for verifying properties of deep neural networks (or providing counter-examples). The technique is based on the simplex method, extended to handle the non-convex Rectified Linear Unit (ReLU) activation function, which is a crucial ingredient in many modern neural networks. The verification procedure tackles neural networks as a whole, without making any simplifying assumptions. We evaluated our technique on a prototype deep neural network implementation of the next-generation airborne collision avoidance system for unmanned aircraft (ACAS Xu). Results show that our technique can successfully prove properties of networks that are an order of magnitude larger than the largest networks verified using existing methods.Comment: This is the extended version of a paper with the same title that appeared at CAV 201

Frustration induced Raman scattering in CuGeO_3

We present experimental data for the Raman intensity in the spin-Peierls compound CuGeO_3 and theoretical calculations from a one-dimensional frustrated spin model. The theory is based on (a) exact diagonalization and (b) a recently developed solitonic mean field theory. We find good agreement between the 1D-theory in the homogeneous phase and evidence for a novel dimerization of the Raman operator in the spin-Peierls state. Finally we present evidence for a coupling between the interchain exchange, the spin-Peierls order parameter and the magnetic excitations along the chains.Comment: Phys. Rev. B, Rapid Comm, in Pres

An inquiry-based learning approach to teaching information retrieval

The study of information retrieval (IR) has increased in interest and importance with the explosive growth of online information in recent years. Learning about IR within formal courses of study enables users of search engines to use them more knowledgeably and effectively, while providing the starting point for the explorations of new researchers into novel search technologies. Although IR can be taught in a traditional manner of formal classroom instruction with students being led through the details of the subject and expected to reproduce this in assessment, the nature of IR as a topic makes it an ideal subject for inquiry-based learning approaches to teaching. In an inquiry-based learning approach students are introduced to the principles of a subject and then encouraged to develop their understanding by solving structured or open problems. Working through solutions in subsequent class discussions enables students to appreciate the availability of alternative solutions as proposed by their classmates. Following this approach students not only learn the details of IR techniques, but significantly, naturally learn to apply them in solution of problems. In doing this they not only gain an appreciation of alternative solutions to a problem, but also how to assess their relative strengths and weaknesses. Developing confidence and skills in problem solving enables student assessment to be structured around solution of problems. Thus students can be assessed on the basis of their understanding and ability to apply techniques, rather simply their skill at reciting facts. This has the additional benefit of encouraging general problem solving skills which can be of benefit in other subjects. This approach to teaching IR was successfully implemented in an undergraduate module where students were assessed in a written examination exploring their knowledge and understanding of the principles of IR and their ability to apply them to solving problems, and a written assignment based on developing an individual research proposal

Magnon-magnon interactions in the Spin-Peierls compound CuGeO_3

In a magnetic substance the gap in the Raman spectrum, Delta_R, is approximatively twice the value of the neutron scattering gap, Delta_S, if the the magnetic excitations (magnons) are only weakly interacting. But for CuGeO_3 the experimentally observed ratio Delta_R/Delta_S is approximatively 1.49-1.78, indicating attractive magnon-magnon interactions in the quasi-1D Spin-Peierls compound CuGe_3. We present numerical estimates for Delta_R/Delta_S from exact diagonalization studies for finite chains and find agreement with experiment for intermediate values of the frustration parameter alpha. An analysis of the numerical Raman intensity leads us to postulate a continuum of two-magnon bound states in the Spin-Peierls phase. We discuss in detail the numerical method used, the dependence of the results on the model parameters and a novel matrix-element effect due to the dimerization of the Raman-operator in the Spin-Peierls phase.Comment: submitted to PRB, Phys. Rev. B, in pres