Learning Mazes with Aliasing States: An LCS Algorithm with Associative Perception

Learning classifier systems (LCSs) belong to a class of algorithms based on the principle of self-organization and have frequently been applied to the task of solving mazes, an important type of reinforcement learning (RL) problem. Maze problems represent a simplified virtual model of real environments that can be used for developing core algorithms of many real-world applications related to the problem of navigation. However, the best achievements of LCSs in maze problems are still mostly bounded to non-aliasing environments, while LCS complexity seems to obstruct a proper analysis of the reasons of failure. We construct a new LCS agent that has a simpler and more transparent performance mechanism, but that can still solve mazes better than existing algorithms. We use the structure of a predictive LCS model, strip out the evolutionary mechanism, simplify the reinforcement learning procedure and equip the agent with the ability of associative perception, adopted from psychology. To improve our understanding of the nature and structure of maze environments, we analyze mazes used in research for the last two decades, introduce a set of maze complexity characteristics, and develop a set of new maze environments. We then run our new LCS with associative perception through the old and new aliasing mazes, which represent partially observable Markov decision problems (POMDP) and demonstrate that it performs at least as well as, and in some cases better than, other published systems

Improving Strategies via SMT Solving

We consider the problem of computing numerical invariants of programs by abstract interpretation. Our method eschews two traditional sources of imprecision: (i) the use of widening operators for enforcing convergence within a finite number of iterations (ii) the use of merge operations (often, convex hulls) at the merge points of the control flow graph. It instead computes the least inductive invariant expressible in the domain at a restricted set of program points, and analyzes the rest of the code en bloc. We emphasize that we compute this inductive invariant precisely. For that we extend the strategy improvement algorithm of [Gawlitza and Seidl, 2007]. If we applied their method directly, we would have to solve an exponentially sized system of abstract semantic equations, resulting in memory exhaustion. Instead, we keep the system implicit and discover strategy improvements using SAT modulo real linear arithmetic (SMT). For evaluating strategies we use linear programming. Our algorithm has low polynomial space complexity and performs for contrived examples in the worst case exponentially many strategy improvement steps; this is unsurprising, since we show that the associated abstract reachability problem is Pi-p-2-complete

Statistics of Atmospheric Correlations

For a large class of quantum systems the statistical properties of their spectrum show remarkable agreement with random matrix predictions. Recent advances show that the scope of random matrix theory is much wider. In this work, we show that the random matrix approach can be beneficially applied to a completely different classical domain, namely, to the empirical correlation matrices obtained from the analysis of the basic atmospheric parameters that characterise the state of atmosphere. We show that the spectrum of atmospheric correlation matrices satisfy the random matrix prescription. In particular, the eigenmodes of the atmospheric empirical correlation matrices that have physical significance are marked by deviations from the eigenvector distribution.Comment: 8 pages, 9 figs, revtex; To appear in Phys. Rev.

Intestinal fungi contribute to development of alcoholic liver disease

This study was supported in part by NIH grants R01 AA020703, U01 AA021856 and by Award Number I01BX002213 from the Biomedical Laboratory Research & Development Service of the VA Office of Research and Development (to B.S.). K.H. was supported by a DFG (Deutsche Forschungsgemeinschaft) fellowship (HO/ 5690/1-1). S.B. was supported by a grant from the Swiss National Science Foundation (P2SKP3_158649). G.G. received funding from the Yale Liver Center NIH P30 DK34989 and R.B. from NIAAA grant U01 AA021908. A.K. received support from NIH grants RC2 AA019405, R01 AA020216 and R01 AA023417. G.D.B. is supported by funds from the Wellcome Trust. We acknowledge the Human Tissue and Cell Research (HTCR) Foundation for making human tissue available for research and Hepacult GmbH (Munich, Germany) for providing primary human hepatocytes for in vitro analyses. We thank Dr. Chien-Yu Lin Department of Medicine, Fu-Jen Catholic University, Taiwan for statistical analysis.Peer reviewedPublisher PD

Effect of an Electron-phonon Interaction on the One-electron Spectral Weight of a d-wave Superconductor

We analyze the effects of an electron-phonon interaction on the one-electron spectral weight A(k,omega) of a d_{x^2-y^2} superconductor. We study the case of an Einstein phonon mode with various momentum-dependent electron-phonon couplings and compare the structure produced in A(k,omega) with that obtained from coupling to the magnetic pi-resonant mode. We find that if the strength of the interactions are adjusted to give the same renormalization at the nodal point, the differences in A(k,omega) are generally small but possibly observable near k=(pi,0).Comment: 10 pages, 14 figures (color versions of Figs. 2,4,10,11,12 available upon request

"Dark energy" in the Local Void

The unexpected discovery of the accelerated cosmic expansion in 1998 has filled the Universe with the embarrassing presence of an unidentified "dark energy", or cosmological constant, devoid of any physical meaning. While this standard cosmology seems to work well at the global level, improved knowledge of the kinematics and other properties of our extragalactic neighborhood indicates the need for a better theory. We investigate whether the recently suggested repulsive-gravity scenario can account for some of the features that are unexplained by the standard model. Through simple dynamical considerations, we find that the Local Void could host an amount of antimatter ($\sim5\times10^{15}\,M_\odot$) roughly equivalent to the mass of a typical supercluster, thus restoring the matter-antimatter symmetry. The antigravity field produced by this "dark repulsor" can explain the anomalous motion of the Local Sheet away from the Local Void, as well as several other properties of nearby galaxies that seem to require void evacuation and structure formation much faster than expected from the standard model. At the global cosmological level, gravitational repulsion from antimatter hidden in voids can provide more than enough potential energy to drive both the cosmic expansion and its acceleration, with no need for an initial "explosion" and dark energy. Moreover, the discrete distribution of these dark repulsors, in contrast to the uniformly permeating dark energy, can also explain dark flows and other recently observed excessive inhomogeneities and anisotropies of the Universe.Comment: 6 pages, accepted as a Letter to the Editor by Astrophysics and Space Scienc

Development of Novel CO2 Adsorbents for Capture of CO2 from Flue Gas

Capturing CO2 emissions generated from fossil fuel-based power plants has received widespread attention and is considered a vital course of action for CO2 emission abatement. Efforts are underway at the Department of Energy’s National Energy Technology Laboratory to develop viable energy technologies enabling the CO2 capture from large stationary point sources. Solid, immobilized amine sorbents (IAS) formulated by impregnation of liquid amines within porous substrates are reactive towards CO2 and offer an alternative means for cyclic capture of CO2 eliminating, to some degree, inadequacies related to chemical absorption by aqueous alkanolamine solutions. This paper describes synthesis, characterization, and CO2 adsorption properties for IAS materials previously tested to bind and release CO2 and water vapor in a closed loop life support system. Tetraethylenepentamine (TEPA), acrylonitrile-modified tetraethylenepentamine (TEPAN), and a single formulation consisting of TEPAN and N, N’-bis(2-hydroxyethyl)ethylenediamine (BED) were individually supported on a poly (methyl methacrylate) (PMMA) substrate and examined. CO2 adsorption profiles leading to reversible CO2 adsorption capacities were obtained using thermogravimetry. Under 10% CO2 in nitrogen at 25°C and 1 atm, TEPA supported on PMMA over 60 minutes adsorbed ~3.2 mmol/g{sorbent} whereas, TEPAN supported on PMMA along with TEPAN and BED supported on PMMA adsorbed ~1.7 mmol/g{sorbent} and ~2.3 mmol/g{sorbent} respectively. Cyclic experiments with a 1:1 weight ratio of TEPAN and BED supported on poly (methyl methacrylate) beads utilizing a fixed-bed flow system with 9% CO2, 3.5% O2, nitrogen balance with trace gas constituents were studied. CO2 adsorption capacity was ~ 3 mmols CO2/g{sorbent} at 40°C and 1.4 atm. No beneficial effect on IAS performance was found using a moisture-laden flue gas mixture. Tests with 750 ppmv NO in a humidified gas stream revealed negligible NO sorption onto the IAS. A high SO2 concentration resulted in incremental loss in IAS performance and revealed progressive degrees of “staining” upon testing. Adsorption of SO2 by the IAS necessitates upstream removal of SO2 prior to CO2 capture

Prenatal arsenic exposure and DNA methylation in maternal and umbilical cord blood leukocytes

Background: Arsenic is an epigenetic toxicant and could influence fetal developmental programming.Objectives: We evaluated the association between arsenic exposure and DNA methylation in maternal and umbilical cord leukocytes.Methods: Drinking-water and urine samples were collected when women were at 64 28 weeks gestation; the samples were analyzed for arsenic using inductively coupled plasma mass spectrometry. DNA methylation at CpG sites in p16 (n = 7) and p53 (n = 4), and in LINE-1 and Alu repetitive elements (3 CpG sites in each), was quantified using pyrosequencing in 113 pairs of maternal and umbilical blood samples. We used general linear models to evaluate the relationship between DNA methylation and tertiles of arsenic exposure.Results: Mean (\ub1 SD) drinking-water arsenic concentration was 14.8 \ub1 36.2 \u3bcg/L (range: < 1-230 \u3bcg/L). Methylation in LINE-1 increased by 1.36% [95% confidence interval (CI): 0.52, 2.21%] and 1.08% (95% CI: 0.07, 2.10%) in umbilical cord and maternal leukocytes, respectively, in association with the highest versus lowest tertile of total urinary arsenic per gram creatinine. Arsenic exposure was also associated with higher methylation of some of the tested CpG sites in the promoter region of p16 in umbilical cord and maternal leukocytes. No associations were observed for Alu or p53 methylation.Conclusions: Exposure to higher levels of arsenic was positively associated with DNA methylation in LINE-1 repeated elements, and to a lesser degree at CpG sites within the promoter region of the tumor suppressor gene p16. Associations were observed in both maternal and fetal leukocytes. Future research is needed to confirm these results and determine if these small increases in methylation are associated with any health effect

Designing Social Agents with Empathic Understanding

Abstract. This paper addresses the design of an agent model for a social agent capable of understanding other agents in an empathic way. The model describes how the empathic agent deals with another agent’s mental states and the associated feelings, thus not only understanding the other agent’s mental state but at the same time feeling the accompanying emotion of the other agent.