Learning Markov Decision Processes for Model Checking

Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system. The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation is performed by analyzing the probabilistic linear temporal logic properties of the system as well as by analyzing the schedulers, in particular the optimal schedulers, induced by the learned models.Comment: In Proceedings QFM 2012, arXiv:1212.345

Introduction to the new usability

This paper introduces the motivation for and concept of the "new usability" and positions it against existing approaches to usability. It is argued that the contexts of emerging products and systems mean that traditional approaches to usability engineering and evaluation are likely to prove inappropriate to the needs of "digital consumers." The paper briefly reviews the contributions to this special issue in terms of their relation to the idea of the "new usability" and their individual approaches to dealing with contemporary usability issues. This helps provide a background to the "new usability" research agenda, and the paper ends by posing what are argued to be the central challenges facing the area and those which lie at the heart of the proposed research agenda

Model Independent Tests of Skyrmions and Their Holographic Cousins

We describe a new exact relation for large $N_c$ QCD for the long-distance behavior of baryon form factors in the chiral limit. This model-independent relation is used to test the consistency of the structure of several baryon models. All 4D semiclassical chiral soliton models satisfy the relation, as does the Pomarol-Wulzer holographic model of baryons as 5D Skyrmions. However, remarkably, we find that the holographic model treating baryons as instantons in the Sakai-Sugimoto model does not satisfy the relation.Comment: v2. Added references, corrected typo

Just How Strange? Loops, Poles and the Strangeness Radius of the Nucleon

We consider a simple model for the strangeness radius of the nucleon. The model is based on vector meson dominance (VMD) and $\omega - \phi$ mixing in addition to a kaon cloud contribution. We find that the VMD contribution is similar in magnitude and of the same sign as the kaon contribution to the Sachs strangeness radius and is significantly larger than the kaon contribution to the Dirac radius. Two figures (not included) can be obtained through the authors ([email protected]).Comment: 12 pages, DOE/ER/40762--011, U. of MD PP \#93--21

Hybrid Bayesian Networks Using Mixtures of Truncated Basis Functions

This paper introduces MoTBFs, an R package for manipulating mixtures of truncated basis functions. This class of functions allows the representation of joint probability distributions involving discrete and continuous variables simultaneously, and includes mixtures of truncated exponentials and mixtures of polynomials as special cases. The package implements functions for learning the parameters of univariate, multivariate, and conditional distributions, and provides support for parameter learning in Bayesian networks with both discrete and continuous variables. Probabilistic inference using forward sampling is also implemented. Part of the functionality of the MoTBFs package relies on the bnlearn package, which includes functions for learning the structure of a Bayesian network from a data set. Leveraging this functionality, the MoTBFs package supports learning of MoTBF-based Bayesian networks over hybrid domains. We give a brief introduction to the methodological context and algorithms implemented in the package. An extensive illustrative example is used to describe the package, its functionality, and its usage

How to observe the Efimov effect

We propose to observe the Efimov effect experimentally by applying an external electric field on atomic three-body systems. We first derive the lowest order effective two-body interaction for two spin zero atoms in the field. Then we solve the three-body problem and search for the extreme spatially extended Efimov states. We use helium trimers as an illustrative numerical example and estimate the necessary field strength to be less than 2.7 V/angstrom.Comment: 4 pages, 2 postscript figures, psfig.sty, revte

Dramatiske refleksioner: Dramatiske refleksioner

Forlaget DRAMA udgiver hvert år 35-40 dramaer af både etablerede og debuterende danske dramatikere. Vi har kigget på 37 af de stykker, der er udgivet mellem 2006 - 2008. 17 af disse dramaer reklamerer med et engagement i aktuelle samfundsmæssige problemstillinger

Fidelity of Quantum Interferometers

For a generic interferometer, the conditional probability density distribution, $p(\phi|m)$, for the phase $\phi$ given measurement outcome $m$, will generally have multiple peaks. Therefore, the phase sensitivity of an interferometer cannot be adequately characterized by the standard deviation, such as $\Delta\phi\sim 1/\sqrt{N}$ (the standard limit), or $\Delta\phi\sim 1/N$ (the Heisenberg limit). We propose an alternative measure of phase sensitivity--the fidelity of an interferometer--defined as the Shannon mutual information between the phase shift $\phi$\ and the measurement outcomes $m$. As an example application of interferometer fidelity, we consider a generic optical Mach-Zehnder interferometer, used as a sensor of a classical field. We find the surprising result that an entangled {\it N00N} state input leads to a lower fidelity than a Fock state input, for the same photon number.Comment: 4 pages, 3 figure

Simulating Hamiltonians in Quantum Networks: Efficient Schemes and Complexity Bounds

We address the problem of simulating pair-interaction Hamiltonians in n node quantum networks where the subsystems have arbitrary, possibly different, dimensions. We show that any pair-interaction can be used to simulate any other by applying sequences of appropriate local control sequences. Efficient schemes for decoupling and time reversal can be constructed from orthogonal arrays. Conditions on time optimal simulation are formulated in terms of spectral majorization of matrices characterizing the coupling parameters. Moreover, we consider a specific system of n harmonic oscillators with bilinear interaction. In this case, decoupling can efficiently be achieved using the combinatorial concept of difference schemes. For this type of interactions we present optimal schemes for inversion.Comment: 19 pages, LaTeX2