title:
Constraining Sub-Grid Physics with High-Redshift Spatially-Resolved
  Metallicity Distributions

abstract:
  We examine the role of energy feedback in shaping the distribution of metals
within cosmological hydrodynamical simulations of L* disc galaxies. While
negative abundance gradients today provide a boundary condition for galaxy
evolution models, in support of inside-out disc growth, empirical evidence as
to whether abundance gradients steepen or flatten with time remains highly
contradictory. We made use of a suite of L* discs, realised with and without
`enhanced' feedback. All the simulations were produced using the smoothed
particle hydrodynamics code Gasoline, and their in situ gas-phase metallicity
gradients traced from redshift z~2 to the present-day. Present-day
age-metallicity relations and metallicity distribution functions were derived
for each system. The `enhanced' feedback models, which have been shown to be in
agreement with a broad range of empirical scaling relations, distribute energy
and re-cycled ISM material over large scales and predict the existence of
relatively `flat' and temporally invariant abundance gradients. Enhanced
feedback schemes reduce significantly the scatter in the local stellar
age-metallicity relation and, especially, the [O/Fe]-[Fe/H] relation. The local
[O/Fe] distribution functions for our L* discs show clear bimodality, with
peaks at [O/Fe]=-0.05 and +0.05 (for stars with [Fe/H]>-1), consistent with our
earlier work on dwarf discs. Our results with `enhanced' feedback are
inconsistent with our earlier generation of simulations realised with
`conservative' feedback. We conclude that spatially-resolved metallicity
distributions, particularly at high-redshift, offer a unique and under-utilised
constraint on the uncertain nature of stellar feedback processes.


title: The parsec-scale structure of radio-loud broad absorption line quasars

abstract:
  Broad absorption line quasars (BAL QSOs) belong to a class of objects not
well-understood as yet. Their UV spectra show BALs in the blue wings of the UV
resonance lines, owing to ionized gas with outflow velocities up to 0.2 c. They
can have radio emission that is difficult to characterize and that needs to be
studied at various wavelengths and resolutions. We aim to study the pc-scale
properties of their synchrotron emission and, in particular, to determine their
core properties. We performed observations in the Very Long Baseline
Interferometry (VLBI) technique, using both the European VLBI Network (EVN) at
5 GHz, and the Very Long Baseline Array (VLBA) at 5 and 8.4 GHz to map the
pc-scale structure of the brightest radio-loud objects of our sample, allowing
a proper morphological interpretation. A variety of morphologies have been
found: 9 BAL QSOs on a total of 11 observed sources have a resolved structure.
Core-jet, double, and symmetric objects are present, suggesting different
orientations. In some cases the sources can be young GPS or CSS. The projected
linear size of the sources, also considering observations from our previous
work for the same objects, can vary from tens of pc to hundreds of kpc. In some
cases, a diffuse emission can be supposed from the missing flux-density with
respect to previous lower resolution observations. Finally, the magnetic field
strength does not significantly differ from the values found in the literature
for radio sources with similar sizes. These results are not easily interpreted
with the youth scenario for BAL QSOs, in which they are generally compact
objects still expelling a dust cocoon. The variety of orientations,
morphologies, and extensions found are presumably related to different possible
angles for the BAL producing outflows, with respect to the jet axis. Moreover,
the phenomenon could be present in various phases of the QSO evolution.


title:
Revisiting some physics issues related to the new mass limit for
  magnetized white dwarfs

abstract:
  We clarify important physics issues related to the recently established new
mass limit for magnetized white dwarfs which is significantly
super-Chandrasekhar. The issues include, justification of high magnetic field
and the corresponding formation of stable white dwarfs, contribution of the
magnetic field to the total density and pressure, flux freezing, variation of
magnetic field and related currents therein. We also attempt to address the
observational connection of such highly magnetized white dwarfs.


title: Plasmons do not go that quantum

abstract:
  We develop a theoretical model of the surface plasmon resonance of metallic
nanospheres in the size range down to the single nanometer size. Within this
model we explicitly show how different microscopic mechanisms, namely
quantization due to size (QSE) and electron spill-out, affect the energy of the
surface plasmon. We demonstrate, that electron spill-out effects, which can
move the surface plasma energy both toward the red or the blue, can be
comparable to or even stronger than QSE. Thus, depending on circumstances, QSE
may only be observed for ultrasmall metal nanoparticles much closer to 1 nm in
size than to 10 nm. Results presented herein are in quantitative agreement with
recent published experimental results for Ag and Au.


title: Active Galactic Nuclei under the scrutiny of CTA

abstract:
  Active Galactic Nuclei (hereafter AGN) produce powerful outflows which offer
excellent conditions for efficient particle acceleration in internal and
external shocks, turbulence, and magnetic reconnection events. The jets as well
as particle accelerating regions close to the supermassive black holes
(hereafter SMBH) at the intersection of plasma inflows and outflows, can
produce readily detectable very high energy gamma-ray emission. As of now, more
than 45 AGN including 41 blazars and 4 radiogalaxies have been detected by the
present ground-based gamma-ray telescopes, which represents more than one third
of the cosmic sources detected so far in the VHE gamma-ray regime. The future
Cherenkov Telescope Array (CTA) should boost the sample of AGN detected in the
VHE range by about one order of magnitude, shedding new light on AGN population
studies, and AGN classification and unification schemes. CTA will be a unique
tool to scrutinize the extreme high-energy tail of accelerated particles in
SMBH environments, to revisit the central engines and their associated
relativistic jets, and to study the particle acceleration and emission
mechanisms, particularly exploring the missing link between accretion physics,
SMBH magnetospheres and jet formation. Monitoring of distant AGN will be an
extremely rewarding observing program which will inform us about the inner
workings and evolution of AGN. Furthermore these AGN are bright beacons of
gamma-rays which will allow us to constrain the extragalactic infrared and
optical backgrounds as well as the intergalactic magnetic field, and will
enable tests of quantum gravity and other "exotic" phenomena.


title: The Wald entropy formula and loop quantum gravity

abstract:
  We outline how the Wald entropy formula naturally arises in loop quantum
gravity based on recently introduced dimension-independent connection
variables. The key observation is that in a loop quantization of a generalized
gravity theory, the analog of the area operator turns out to measure, morally
speaking, the Wald entropy rather than the area. We discuss the explicit
example of (higher-dimensional) Lanczos-Lovelock gravity and comment on recent
work on finding the correct numerical prefactor of the entropy by comparing it
to a semiclassical effective action.


title:
Charge Kondo Effect in Thermoelectric Properties of Lead Telluride doped
  with Thallium Impurities

abstract:
  We investigate the thermoelectric properties of PbTe doped with a small
concentration $x$ of Tl impurities acting as acceptors and described by
Anderson impurities with negative on-site (effective) interaction. The
resulting charge Kondo effect naturally accounts for a number of the low
temperature anomalies in this system, including the unusual doping dependence
of the carrier concentration, the Fermi level pinning and the self-compensation
effect. The Kondo anomalies in the low temperature resistivity at temperatures
$T\leq 10\, {\rm K}$ and the $x$-dependence of the residual resistivity are
also in good agreement with experiment. Our model also captures the qualitative
aspects of the thermopower at higher temperatures $T>300\, {\rm K}$ for high
dopings ($x>0.6%$) where transport is expected to be largely dominated by
carriers in the heavy hole band of PbTe.


title:
Asymptotic preserving schemes on distorted meshes for Friedrichs systems
  with sti relaxation: application to angular models in linear transport

abstract:
  In this paper we propose an asymptotic preserving scheme for a family of
Friedrichs systems on unstructured meshes based on a decomposition between the
hyperbolic heat equation and a linear hyperbolic which not involved in the di
usive regime. For the hyperbolic heat equation we use asymptotic preserving
schemes recently designed previously. To discretize the second part we use
classical Rusanov or upwind schemes. To nish we apply this method for the
discretization of the PN and SN models which are widely used in transport
codes.


title: Commuting matrices and the Hilbert scheme of points on affine spaces

abstract:
  We give a linear algebraic and a monadic descriptions of the Hilbert scheme
of points on the affine space of dimension $n$ which naturally extends
Nakajima's representation of the Hilbert scheme of points on the plane. As an
application of our ideas and recent results from the literature on commuting
matrices, we show that the Hilbert scheme of $c$ points on $(\C^3)$ is
irreducible for $c\le 10$.


title: Classifying terminal weighted projective space

abstract:
  We present a classification of all weighted projective spaces with at worst
terminal or canonical singularities in dimension four. As a corollary we also
classify all four-dimensional one-point lattice simplices up to equivalence.
Finally, we classify the terminal Gorenstein weighted projective spaces up to
dimension ten.


title:
Projection: A Unified Approach to Semi-Infinite Linear Programs and
  Duality in Convex Programming

abstract:
  Fourier-Motzkin elimination is a projection algorithm for solving finite
linear programs. We extend Fourier-Motzkin elimination to semi-infinite linear
programs which are linear programs with finitely many variables and infinitely
many constraints. Applying projection leads to new characterizations of
important properties for primal-dual pairs of semi-infinite programs such as
zero duality gap, feasibility, boundedness, and solvability. Extending the
Fourier-Motzkin elimination procedure to semi-infinite linear programs yields a
new classification of variables that is used to determine the existence of
duality gaps. In particular, the existence of what the authors term dirty
variables can lead to duality gaps. Our approach has interesting applications
in finite-dimensional convex optimization. For example, sufficient conditions
for a zero duality gap, such as existence of a Slater point, are reduced to
guaranteeing that there are no dirty variables. This leads to completely new
proofs of such sufficient conditions for zero duality.


title: A universal formula for the volume of compact Lie groups

abstract:
  We provide a closed formula for the volume of a simple compact Lie group in
terms of the universal Vogel parameters. For the unitary groups SU_n this
reduces to the integral representation of the classical Barnes G-function.


title:
Directed harmonic currents for laminations on certain compact complex
  surfaces

abstract:
  Let $\mathcal{L}$ be a Lipschitz lamination by Riemann surfaces embedded in
$M$. If $M$ is a complex torus, $\mathbb{CP}^1\times\mathbb{CP}^1$ or
$\mathbb{T}^1\times\mathbb{CP}^1$ and there is no directed closed current then
there exists a unique directed harmonic current of mass one. Moreover if
$\mathcal{L}$ is embedded in $M=\mathbb{CP}^1\times\mathbb{CP}^1$ and has no
compact leaves, then there is no directed closed current. If $\mathcal{L}$ is
not Lipschitz, then slightly weaker results are obtained.


title: Some remarks on multicategories and additive categories

abstract:
  Categories are coreflectively embedded in multicategories via the "discrete
cocone" construction, the right adjoint being given by the monoid construction.
Furthermore, the adjunction lifts to the "cartesian level": preadditive
categories are coreflectively embedded (as theories for many-sorted modules) in
cartesian multicategories (general algebraic theories). In particular, one gets
a direct link between two ways of considering modules over a rig, namely as
additive functors valued in commutative monoids or as models of the theory
generated by the rig itself.


title: Accelerating Solitons in Gas-Filled Hollow-Core Photonic Crystal Fibers

abstract:
  We found the self-similar solitary solutions of a recently proposed model for
propagation of pulses in gas filled hollow-core photonic crystal fibers that
includes a plasma induced nonlinearity. As anticipated for a simpler model and
using a perturbation analysis, there are indeed stationary solitary waves that
accelerate and self-shift to higher frequencies. However, if the plasma
nonlinearity strength is large or the pulse amplitudes are small, the solutions
have distinguished long tails and decay as they propagate.


title:
Measurement of the $B^0 \rightarrow K^{*0}e^+e^-$ branching fraction at
  low dilepton mass

abstract:
  The branching fraction of the rate decay $B^0 \rightarrow K^{*0}e^+e^-$ in
the dilepton mass region from 30 to 1000 MeV$/c^2$ has been measured by the
LHCb experiment, using $pp$ collision data, corresponding to an integrated
luminosity of 1.0 fb$^{-1}$, at a centre-of-mass energy of 7 TeV. The decay
mode $B^0 \rightarrow J/\psi(e^+e^-) K^{*0}$ is utilized as a normalization
channel. The branching fraction $B^0 \rightarrow K^{*0}e^+e^-$ is measured to
be $$ B(B^0 \rightarrow K^{*0}e^+e^-)^{30-1000 MeV/c^2}= (3.1\, ^{+0.9\mbox{}
+0.2}_{-0.8\mbox{}-0.3} \pm 0.2)\times 10^{-7}, $$ where the first error is
statistical, the second is systematic, and the third comes from the
uncertainties on the B^0 \rightarrow J/\psi K^{*0}$ and $J/\psi \rightarrow
e^+e^- $ branching fractions.


title:
Observation of the Charged Hadron $Z_c^{\pm}(3900)$ and Evidence for the
  Neutral $Z_c^0(3900)$ in $e^+e^-\to \pi\pi J/\psi$ at $\sqrt{s}=4170$ MeV

abstract:
  Using 586 pb$^{-1}$ of $e^+e^-$ annihilation data taken with the CLEO-c
detector at $\sqrt{s}=4170$ MeV, the peak of the charmonium resonance
$\psi(4160)$, we analyze the decay $\psi(4160)\to \pi^+\pi^- J/\psi$, and
report observation of the charged state $Z_c^\pm(3900)$ decaying into $\pi^\pm
J/\psi$ at a significance level of $>5 \sigma$. We obtain
$M(Z_c^\pm)=3886\pm4(\text{stat})\pm 2(\text{syst})$ MeV and
$\Gamma(Z_c^\pm)=37\pm4(\text{stat})\pm 8(\text{syst})$ MeV, which are in good
agreement with the results for this resonance obtained by the BES III and Belle
Collaborations in the decay of the resonance Y(4260). We also present first
evidence for the production of the neutral member of this isospin triplet,
$Z_c^0(3900)$ decaying into $\pi^0J/\psi$ at a $3.5\sigma$ significance level.


title:
On the internal dynamics of starless cores: stability of starless cores
  with internal motions and collapse dynamics

abstract:
  In order to understand the collapse dynamics of observed low-mass starless
cores, we revise the conventional stability condition of hydrostatic
Bonnor-Ebert spheres to take internal motions into account. Because observed
starless cores resemble Bonnor-Ebert density structures, the stability and
dynamics of the starless cores are frequently analyzed by comparing to the
conventional stability condition of a hydrostatic Bonnor-Ebert sphere. However,
starless cores are not hydrostatic but have observed internal motions. In this
study, we take gaseous spheres with a homologous internal velocity field and
derive stability conditions of the spheres utilizing a virial analysis. We
propose two limiting models of spontaneous gravitational collapse: the collapse
of critical Bonnor-Ebert spheres and uniform density spheres. The collapse of
these two limiting models are intended to provide the lower and the upper
limits, respectively, of the infall speeds for a given density structure. The
results of our study suggest that the stability condition sensitively depends
on internal motions. A homologous inward motion with a transonic speed can
reduce the critical size compared to the static Bonnor-Ebert sphere by more
than a factor of two. As an application of the two limiting models of
spontaneous gravitational collapse, we compare the density structures and
infall speeds of the observed starless cores L63, L1544, L1689B, and L694-2 to
the two limiting models. L1689B and L694-2 seem to have been perturbed to
result in faster infall motions than for spontaneous gravitational collapse.


title: Carnegie Supernova Project: Observations of Type IIn supernovae

abstract:
  The observational diversity displayed by various Type IIn supernovae (SNe
IIn) is explored and quantified. In doing so, a more coherent picture ascribing
the variety of observed SNe IIn types to particular progenitor scenarios is
sought. Carnegie Supernova Project (CSP) optical and near-infrared light curves
and visual-wavelength spectroscopy of the Type IIn SNe 2005kj, 2006aa, 2006bo,
2006qq, and 2008fq are presented. Combined with previously published
observations of the Type IIn SNe 2005ip and 2006jd, the full CSP sample is used
to derive physical parameters that describe the nature of the interaction
between the expanding SN ejecta and the circumstellar material (CSM). For each
SN of our sample, we find counterparts, identifying objects similar to SNe
1994W (SN 2006bo), 1998S (SN 2008fq), and 1988Z (SN 2006qq). We present the
unprecedented initial $u$-band plateau of SN 2006aa, and its peculiar late-time
luminosity and temperature evolution. For each SN, mass-loss rates of
10$^{-4}-10^{-2}$ $M_{\odot}$ yr$^{-1}$ are derived, assuming the CSM was
formed by steady winds. Typically wind velocities of a few hundred km s$^{-1}$
are also computed. The CSP SN IIn sample seems to be divided into subcategories
rather than to have exhibited a continuum of observational properties. The wind
and mass-loss parameters would favor a luminous blue variable progenitor
scenario. However the assumptions made to derive those parameters strongly
influence the results, and therefore, other progenitor channels behind SNe IIn
cannot be excluded at this time.


title: Finite temperature and pressure molecular dynamics for BaFe2As2

abstract:
  We study the temperature and pressure dependence of the structural and
electronic properties of the iron pnictide superconductor BaFe2As2. We use
density functional theory based Born-Oppenheimer molecular dynamics simulations
to investigate the system at temperatures from T=5 K to 150 K and pressures
from P=0 GPa to 30 GPa. When increasing the pressure at low temperature, we
find the two transitions from an orthorhombic to a tetragonal and to a
collapsed tetragonal structure that are also observed in zero temperature
structure relaxations and in experiment. However, these transitions are
considerably smeared out at finite temperature, whereas the critical pressure
for the first transition increases with temperature. We also analyze the
electronic structure of BaFe2As2 at finite temperature and work out differences
between the time averaged band structure and Fermi surface at finite
temperature compared to the known zero temperature results. Our results should
be helpful for resolving some open issues in experimental reports for BaFe2As2
under high pressure.


title:
Homotopies of Curves on the 2-Sphere with Geodesic Curvature in a
  Prescribed Interval

abstract:
  Let $C_{k_1}^{k_2}$ denote the set of all closed curves of class $C^r$ on the
sphere $S^2$ whose geodesic curvatures are restricted to lie in $(k_1,k_2)$,
furnished with the $C^r$ topology (for some $r >= 2$ and possibly infinite $k_1
< k_2$). In 1970, J. Little proved that the space $C_0^{+\infty}$ of closed
curves having positive geodesic curvature has three connected components. Let
$r_i = arccot k_i$ (i = 1, 2). We show that $C_{k_1}^{k_2}$ has n connected
components $C_1, ..., C_n$, where n is the greatest integer smaller than or
equal to $\pi/(r_1-r_2) + 1$, and $C_j$ contains circles traversed j times ($1
<= j <= n$). The component $C_{n-1}$ also contains circles traversed $(n-1) +
2m$ times, and $C_n$ also contains circles traversed $n + 2m$ times, for any
natural number m. In addition, each of $C_1, ..., C_{n-2}$ is homotopy
equivalent to $SO_3$ ($n >= 3$). A simple characterization of the components in
terms of the properties of a curve and a proof that $C_{k_1}^{k_2}$ is
homeomorphic to $C_{k'_1}^{k'_2}$ whenever $r_1 - r_2 = r'_1 - r'_2$ ($r'_i =
arccot k'_i$) are also presented.


title:
Lie algebras of infinitesimal CR-automorphisms of finite type,
  holomorphically nondegenerate, weighted homogeneous CR-generic submanifolds
  of C^N

abstract:
  We consider the significant class of holomorphically nondegenerate CR
manifolds of finite type that are represented by some weighted homogeneous
polynomials and we derive some useful features which enable us to set up a fast
effective algorithm to compute their Lie algebras of infinitesimal
CR-automorphisms. This algorithm mainly relies upon a natural gradation of the
sought Lie algebras, and it also consists in treating separately the related
graded components. While some other methods are based on constructing and
solving an associated pde systems which become time consuming as soon as the
number of variables increases, the new method presented here is based on plain
techniques of linear algebra. Furthermore, it benefits from a
divide-and-conquer strategy to break down the computations into some simpler
sub-computations. Moreover, we consider the new and effective concept of
comprehensive Gr\"obner systems which provides us some powerful tools to treat
the computations in the parametric cases. The designed algorithm is also
implemented in the Maple software.


title: Discrete integrals based on comonotonic modularity

abstract:
  It is known that several discrete integrals, including the Choquet and Sugeno
integrals as well as some of their generalizations, are comonotonically modular
functions. Based on a recent description of the class of comonotonically
modular functions, we axiomatically identify more general families of discrete
integrals that are comonotonically modular, including signed Choquet integrals
and symmetric signed Choquet integrals as well as natural extensions of Sugeno
integrals.


title: Modularity of certain mod $p^n$ Galois representations

abstract:
  For a rational prime $p \geq 3$ and an integer $n \geq 2$, we study the
modularity of continuous 2-dimensional mod $p^n$ Galois representations of
$\Gal(\bar{\Q}/\Q)$ whose residual representations are odd and absolutely
irreducible. Under suitable hypotheses on the local structure of these
representations and the size of their images we use deformation theory to
construct characteristic 0 lifts. We then invoke modularity lifting results to
prove that these lifts are modular. As an application, we show that certain
unramified mod $p^n$ Galois representations arise from modular forms of weight
$p^{n-1}(p-1)+1$.


title: Collective dynamics of the high-energy proton-nucleus collisions

abstract:
  We analyze the proton-lead collisions at the LHC energy of 5.02TeV in the
three-stage approach, previously used to successfully describe the relativistic
A-A collisions. The approach consists of the early phase, modeled with the
Glauber model, the event-by-event viscous 3+1 dimensional (3+1 D) relativistic
hydrodynamics, and the statistical hadronization at freeze-out. We show that
features typical of collective dynamics, such as the harmonic flow and the
ridge structures in the two-particle correlations in relative azimuth and
pseudorapidity, may be naturally explained in our framework. In the
proton-nucleus system the harmonic flow is generated from an initially
event-by-event deformed system and is entirely due to these initial
fluctuations. Notably, fluctuations of strength of the initial Glauber sources
which yield the observed distribution of hadron multiplicities and, at the same
time, lead to correct values of the elliptic flow coefficients both from the
two- and four-particle cumulant method, as measured by the ATLAS collaboration.
The azimuthally asymmetric flow is not modified significantly when changing the
viscosity coefficient, the initial time for the collective expansion, or the
initial size of the fireball. The results present an estimate of the collective
component in the two-particle correlations measured experimentally. We
demonstrate that the harmonic flow coefficients can be experimentally measured
with methods based on large rapidity gaps which reduce some of the other
sources of correlations.


title: Comment on "Dynamics of transfer ionization in fast ion-atom collisions"

abstract:
  We inspect the first-order electron-electron capture scenario for transfer
ionization that has been recently formulated by Voitkiv et al. (Phys. Rev. A
86, 012709 (2012) and references therein). Using the multichannel scattering
theory for many-body systems with Coulomb interactions, we show that this
scenario is just a part of the well-studied Oppenheimer-Brinkmann-Kramers
approximation. Accurate numerical calculations in this approximation for the
proton-helium transfer ionization reaction exhibit no appreciable manifestation
of the claimed mechanism.


title: Lattice dynamics of coesite

abstract:
  The lattice dynamics of coesite has been studied by a combination of diffuse
x-ray scattering, inelastic x-ray scattering and an ab initio lattice dynamics
calculation. The combined technique gives access to the full lattice dynamics
in harmonic description and thus eventually provides detailed information on
the elastic properties, the stability and metastability of crystalline systems.
The experimentally validated calculation was used for the investigation of
eigenvectors, mode character and their influence on the density of vibrational
states. High symmetry sections of the reciprocal space distribution of diffuse
scattering and inelastic x-ray scattering spectra as well as the density of
vibrational states and the dispersion relation are reported and compared to the
calculation. A critical point at the zone boundary is found to contribute
strongly to the main peak of the low energy part in the density of vibrational
states. Comparison with the most abundant SiO2 polymorph - alpha-quartz -
reveals similarities and distinct differences in the low-energy vibrational
properties.


title:
Time reversal for radiative transport with applications to inverse and
  control problems

abstract:
  In this paper we develop a time reversal method for the radiative transport
equation to solve two problems: an inverse problem for the recovery of an
initial condition from boundary measurements, and the exact boundary
controllability of the transport field with finite steering time. Absorbing and
scattering effects, modeled by coefficients with low regularity, are
incorporated in the formulation of these problems. This time reversal approach
leads to a convergent iterative procedure to reconstruct the initial condition
provided that the scattering coefficient is sufficiently small in the
$L^{\infty}$ norm. Then, using duality arguments, we show that the solvability
of the inverse problem leads to exact controllability of the transport field
with minimum-norm control obtained constructively. The solution approach to
both of these problems may have medical applications in areas such as optical
imaging and optimization of radiation delivery for cancer therapy.


title: Tree-level Amplitudes in the Nonlinear Sigma Model

abstract:
  We study in detail the general structure and further properties of the
tree-level amplitudes in the SU(N) nonlinear sigma model. We construct the
flavor-ordered Feynman rules for various parameterizations of the SU(N) fields
U(x), write down the Berends-Giele relations for the semi-on-shell currents and
discuss their efficiency for the amplitude calculation in comparison with those
of renormalizable theories. We also present an explicit form of the partial
amplitudes up to ten external particles. It is well known that the standard
BCFW recursive relations cannot be used for reconstruction of the the on-shell
amplitudes of effective theories like the SU(N) nonlinear sigma model because
of the inappropriate behavior of the deformed on-shell amplitudes at infinity.
We discuss possible generalization of the BCFW approach introducing "BCFW
formula with subtractions" and with help of Berends-Giele relations we prove
particular scaling properties of the semi-on-shell amplitudes of the SU(N)
nonlinear sigma model under specific shifts of the external momenta. These
results allow us to define alternative deformation of the semi-on-shell
amplitudes and derive BCFW-like recursion relations. These provide a systematic
and effective tool for calculation of Goldstone bosons scattering amplitudes
and it also shows the possible applicability of on-shell methods to effective
field theories. We also use these BCFW-like relations for the investigation of
the Adler zeroes and double soft limit of the semi-on-shell amplitudes.


title:
Fast-moving finite and infinite trains of solitons for nonlinear
  Schr\"odinger equations

abstract:
  We study *infinite soliton trains* solutions of nonlinear Schr\"odinger
equations (NLS), i.e. solutions behaving at large time as the sum of infinitely
many solitary waves. Assuming the composing solitons have sufficiently large
relative speeds, we prove the existence and uniqueness of such a soliton train.
We also give a new construction of multi-solitons (i.e. finite trains) and
prove uniqueness in an exponentially small neighborhood, and we consider the
case of solutions composed of several solitons and kinks (i.e. solutions with a
non-zero background at infinity).


title:
Generic diffusion for a class of non-convex Hamiltonians with two
  degrees of freedom

abstract:
  In this paper, we study small perturbations of a class of non-convex
integrable Hamiltonians with two degrees of freedom, and we prove a result of
diffusion for an open and dense set of perturbations, with an optimal time of
diffusion which grows linearly with respect to the inverse of the size of the
perturbation.


title: On the matching method and the Goldstone theorem in holography

abstract:
  We study the transition of a scalar field in a fixed $AdS_{d+1}$ background
between an extremum and a minimum of a potential. We compute analytically the
solution to the perturbation equation for the vev deformation case by
generalizing the usual matching method to higher orders and find the propagator
of the boundary theory operator defined through the AdS-CFT correspondence. We
show that, contrary to what happens at the leading order of the matching
method, the next-to-leading order presents a simple pole at $q^2=0$ in
accordance with the Goldstone theorem applied to a spontaneously broken
dilatation invariance.


title: Some Arithmetic Dynamics of Diagonally Split Polynomial Maps

abstract:
  Let $n\geq 2$, and let $f$ be a polynomial of degree at least 2 with
coefficients in a number field or a characteristic 0 function field $K$. We
present two arithmetic applications of a recent theorem of Medvedev-Scanlon to
the dynamics of the map $(f,...,f):\ (\bP^1_{K})^n\longrightarrow (\bP^1_K)^n$,
namely the dynamical analogues of the Hasse principle and the
Bombieri-Masser-Zannier height bound theorem. In particular, we prove that the
Hasse principle holds when we intersect an orbit and a preperiodic subvariety,
and that points in the intersection of a curve with the union of all periodic
hypersurfaces have bounded heights unless that curve is vertical or contained
in a periodic hypersurface.


title:
Signal-background interference effects for $gg \to H \to W^+ W^-$ beyond
  leading order

abstract:
  We study the effect of QCD corrections to the $gg\to H\to W^+ W^-$
signal-background interference at the LHC for a heavy Higgs boson. We construct
a soft-collinear approximation to the NLO and NNLO corrections for the
background process, which is exactly known only at LO. We estimate its accuracy
by constructing and comparing the same approximation to the exact result for
the signal process, which is known up to NNLO, and we conclude that we can
describe the signal-background interference to better than ten percent
accuracy. We show that our result implies that, in practice, a fairly good
approximation to higher-order QCD corrections to the interference may also be
obtained by rescaling the known LO result by a K-factor computed using the
signal process.


title: Friedmann equations from emergence of cosmic space

abstract:
  Padmanabhan [arXiv:1206.4916] argues that the cosmic acceleration can be
understood from the perspective that spacetime dynamics is an emergence
phenomena. By calculating the difference between the surface degrees of freedom
and the bulk degrees of freedom in a region of space, he also arrives at the
Friedmann equation in a flat universe. In this paper, by modification of his
proposal, we are able to derive the Friedmann equation of the
Friedmann-Robertson-Walker universewith any spatial curvature.We also extend
the study to higher-dimensional spacetime and derive successfully the Friedmann
equations not only in Einstein gravity but also in Gauss-Bonnet and more
general Lovelock gravity with any spatial curvature. This is the first
derivation of Friedmann equations in these gravity theories in a nonflat
Friedmann-Robertson-Walker universe by using the novel idea proposed by
Padmanabhan. Our study indicates that the approach presented here is powerful
enough and further supports the viability of Padmanabhan's perspective of
emergence gravity.


title: The pulsating low-mass He-core white dwarfs

abstract:
  Recent years have witnessed the discovery of many low-mass ($\lesssim 0.45
M_{\odot}$) white dwarf (WD) stars --- expected to harbor He cores--- in the
field of the Milky Way and in several galactic globular and open clusters.
Recently, three pulsating objects of this kind have been discovered: SDSS
J1840+6423, SDSS J1112+1117, and SDSS J1518+0658. Motivated by these very
exciting findings, and in view of the valuable asteroseismological potential of
these objects, we present here the main outcomes of a detailed theoretical
study on the seismic properties of low-mass He-core WDs based on fully
evolutionary models representative of these objects. This study is aimed to
provide a theoretical basis from which to interpret present and future
observations of variable low-mass WDs.


title:
Anticipatory Buffer Control and Resource Allocation for Wireless Video
  Streaming

abstract:
  This paper describes a new approach for allocating resources to video
streaming traffic. Assuming that the future channel state can be predicted for
a certain time, we minimize the fraction of the bandwidth consumed for smooth
streaming by jointly allocating wireless channel resources and play-out buffer
size. To formalize this idea, we introduce a new model to capture the dynamic
of a video streaming buffer and the allocated spectrum in an optimization
problem. The result is a Linear Program that allows to trade off buffer size
and allocated bandwidth. Based on this tractable model, our simulation results
show that anticipating poor channel states and pre-loading the buffer
accordingly allows to serve more users at perfect video quality.


title: Rotating black strings in $f(R)$-Maxwell theory

abstract:
  In general, the field equations of $f(R)$ theory coupled to a matter field
are very complicated and hence it is not easy to find exact analytical
solutions. However, if one considers traceless energy-momentum tensor for the
matter source as well as constant scalar curvature, one can derive some exact
analytical solutions from $f(R)$ theory coupled to a matter field. In this
paper, by assuming constant curvature scalar, we construct a class of charged
rotating black string solutions in $f(R)$-Maxwell theory. We study the physical
properties and obtain the conserved quantities of the solutions. The conserved
and thermodynamic quantities computed here depend on function $f'(R_{0})$ and
differ completely from those of Einstein theory in AdS spaces. Besides, unlike
Einstein gravity, the entropy does not obey the area law. We also investigate
the validity of the first law of thermodynamics as well as the stability
analysis in the canonical ensemble, and show that the black string solutions
are always thermodynamically stable in $f(R)$-Maxwell theory with constant
curvature scalar. Finally, we extend the study to the case where the Ricci
scalar is not a constant and in particular $R=R(r)$. In this case, by using the
Lagrangian multipliers method, we derive an analytical black string solution
from $f(R)$ gravity and reconstructed the function $R(r)$. We find that this
class of solutions has an additional logaritmic term in the metric function
which incorporates the effect of the $f(R)$ theory in the solutions.


title: An X-ray study of the supernova remnant G20.0-0.2 and its surroundings

abstract:
  Aims: We study the supernova remnant G20.0-0.2 and its surroundings in order
to look for the high energy counterpart of the radio nebula and to find
evidence of interaction between the shock front and the interstellar medium.
Methods: We used Chandra archival observations to analyze the X-ray emission
from the supernova remnant. The surrounding gas was investigated using data
extracted from the Galactic Ring Survey, the VLA Galactic Plane Survey, the
Galactic Legacy Infrared Midplane Survey Extraordinaire, and the Bolocam
Galactic Plane Survey. Results: G20.0-0.2 shows diffuse X-ray emission from the
central region of the radio remnant. Although the current data do not allow us
to distinguish between a thermal or non-thermal origin for the X-ray diffuse
emission, based on the radio properties we suggest a synchrotron origin as the
most favorable. The hard X-ray point source CXO J182807.4-113516 appears
located at the geometrical center of the remnant and is a potential candidate
to be the pulsar powering the nebula. We found a molecular cloud adjacent to
the flattest border of G20.0-0.2, indicating a probable interaction between the
shock front of the remnant and the molecular gas. Several young stellar object
candidates are found located in the brightest region of the molecular emission,
and over a millimeter continuum source and a dark cloud. This distribution is
an indication of an active star forming region around the supernova remnant.


title:
Simple and Generic Simulator Algorithm for Inhomogeneous Random Spatial
  Deployment

abstract:
  We conceptualized a straightforward and flexible approach for random spatial
inhomogeneity by proposing the area-specific deployment (ASD) algorithm, which
takes into account the clustering tendency of users. In fact, the ASD method
has the advantage of achieving a more realistic heterogeneous deployment based
on limited planning inputs, while still preserving the stochastic character of
users position. We then applied this technique to different circumstances, and
developed spatial-level network algorithms for controlled and uncontrolled
cellular network deployments. Overall, the derived simulator tools will
effectively and easily be useful for designers and deployment planners modeling
a host of multi-coverage and multi-scale wireless network situations.


title:
Increasing the Efficiency of a Thermionic Engine Using a Negative
  Electron Affinity Collector

abstract:
  Most attention to improving vacuum thermionic energy conversion device (TEC)
technology has been on improving electron emission with little attention to
collector optimization. A model was developed to characterize the output
characteristics of a TEC where the collector features negative electron
affinity (NEA). According to the model, there are certain conditions for which
the space charge limitation can be reduced or eliminated. The model is applied
to devices comprised of materials reported in the literature, and predictions
of output power and efficiency are made, targeting the sub-1000K hot-side
regime. By slightly lowering the collector barrier height, an output power of
around $1kW$, at $\geq 20%$ efficiency for a reasonably sized device ($\sim
0.1m^{2}$ emission area) can be achieved.


title: A variational eigenvalue solver on a quantum processor

abstract:
  Quantum computers promise to efficiently solve important problems that are
intractable on a conventional computer. For quantum systems, where the
dimension of the problem space grows exponentially, finding the eigenvalues of
certain operators is one such intractable problem and remains a fundamental
challenge. The quantum phase estimation algorithm can efficiently find the
eigenvalue of a given eigenvector but requires fully coherent evolution. We
present an alternative approach that greatly reduces the requirements for
coherent evolution and we combine this method with a new approach to state
preparation based on ans\"atze and classical optimization. We have implemented
the algorithm by combining a small-scale photonic quantum processor with a
conventional computer. We experimentally demonstrate the feasibility of this
approach with an example from quantum chemistry: calculating the ground state
molecular energy for He-H+, to within chemical accuracy. The proposed approach,
by drastically reducing the coherence time requirements, enhances the potential
of the quantum resources available today and in the near future.


title: Inhomogeneous magnetism in the doped kagome lattice of LaCuO2.66

abstract:
  The hole-doped kagome lattice of Cu2+ ions in LaCuO2.66 was investigated by
nuclear quadrupole resonance (NQR), electron spin resonance (ESR), electrical
resistivity, bulk magnetization and specific heat measurements. For
temperatures above ~180 K, the spin and charge properties show an activated
behavior suggestive of a narrow-gap semiconductor. At lower temperatures, the
results indicate an insulating ground state which may or may not be charge
ordered. While the frustrated spins in remaining patches of the original kagome
lattice might not be directly detected here, the observation of coexisting
non-magnetic sites, free spins and frozen moments reveals an intrinsically
inhomogeneous magnetism. Numerical simulations of a 1/3-diluted kagome lattice
rationalize this magnetic state in terms of a heterogeneous distribution of
cluster sizes and morphologies near the site-percolation threshold.


title:
A Faithful Distributed Implementation of Dual Decomposition and Average
  Consensus Algorithms

abstract:
  We consider large scale cost allocation problems and consensus seeking
problems for multiple agents, in which agents are suggested to collaborate in a
distributed algorithm to find a solution. If agents are strategic to minimize
their own individual cost rather than the global social cost, they are endowed
with an incentive not to follow the intended algorithm, unless the tax/subsidy
mechanism is carefully designed. Inspired by the classical
Vickrey-Clarke-Groves mechanism and more recent algorithmic mechanism design
theory, we propose a tax mechanism that incentivises agents to faithfully
implement the intended algorithm. In particular, a new notion of asymptotic
incentive compatibility is introduced to characterize a desirable property of
such class of mechanisms. The proposed class of tax mechanisms provides a
sequence of mechanisms that gives agents a diminishing incentive to deviate
from suggested algorithm.


title: The Quantum Harmonic Oscillator in the ESR Model

abstract:
  The ESR model proposes a new theoretical perspective which incorporates the
mathematical formalism of standard (Hilbert space) quantum mechanics (QM) in a
noncontextual framework, reinterpreting quantum probabilities as conditional on
detection instead of absolute. We have provided in some previous papers
mathematical representations of the physical entities introduced by the ESR
model, namely observables, properties, pure states, proper and improper
mixtures, together with rules for calculating conditional and overall
probabilities, and for describing transformations of states induced by
measurements. We study in this paper the relevant physical case of the quantum
harmonic oscillator in our mathematical formalism. We reinterpret the standard
quantum rules for probabilities, provide new expressions for absolute
probabilities, and show how the standard state transformations must be modified
according to the ESR model.


title: Symplectic embeddings of polydisks

abstract:
  In this note, we obtain new obstructions to symplectic embeddings of a
product of disks (a polydisk) into a 4-dimensional ball. The polydisk P(r,s) is
the product of the disk of area r with the disk of area s. The ball of capacity
a, denoted B(a), is the ball with \pi r^2 \le a.
  We show P(1,2) embeds in B^4(a) if and only if a is at least 3. This shows
the inclusion of P(1,2) in B^4(3) is optimal. The necessity of a \ge 3 implies
that for this particular embedding problem neither the Ekeland-Hofer nor ECH
capacities give a sharp obstruction. We contrast this with the case of
ellipsoid embeddings into a ball when the ECH capacities give a complete list
of obstructions [McDuff 2011]. Our obstruction does not come from a symplectic
capacity, but instead from pseudoholomorphic foliations, thus the techniques
seem to be special to dimension 4.


title:
Continuum of solutions for an elliptic problem with critical growth in
  the gradient

abstract:
  We consider the boundary value problem \begin{equation*} - \Delta u = \lambda
c(x)u+ \mu(x) |\nabla u|^2 + h(x), \quad u \in H^1_0(\Omega) \cap
L^{\infty}(\Omega) \eqno{(P_{\lambda})} \end{equation*} where $\Omega \subset
\R^N, N \geq 3$ is a bounded domain with smooth boundary. It is assumed that
$c\gneqq 0$, $c,h$ belong to $L^p(\Omega)$ for some $p > N/2$ and that $\mu \in
L^{\infty}(\Omega).$ We explicit a condition which guarantees the existence of
a unique solution of $(P_{\lambda})$ when $\lambda <0$ and we show that these
solutions belong to a continuum. The behaviour of the continuum depends in an
essential way on the existence of a solution of $(P_0)$. It crosses the axis
$\lambda =0$ if $(P_0)$ has a solution, otherwise if bifurcates from infinity
at the left of the axis $\lambda =0$. Assuming that $(P_0)$ has a solution and
strenghtening our assumptions to $\mu(x)\geq \mu_1>0$ and $h\gneqq 0$, we show
that the continuum bifurcates from infinity on the right of the axis $\lambda
=0$ and this implies, in particular, the existence of two solutions for any
$\lambda >0$ sufficiently small.


title:
Precession-tracking coordinates for simulations of
  compact-object-binaries

abstract:
  Binary black hole simulations with black hole excision using spectral methods
require a coordinate transformation into a co-rotating coordinate system where
the black holes are essentially at rest. This paper presents and discusses two
coordinate transformations that are applicable to precessing binary systems,
one based on Euler angles, the other on quaternions. Both approaches are found
to work well for binaries with moderate precession, i.e. for cases where the
orientation of the orbital plane changes by much less than 90 degrees. For
strong precession, performance of the Euler-angle parameterization
deteriorates, eventually failing for a 90 degree change in orientation because
of singularities in the parameterization ("gimbal lock"). In contrast, the
quaternion representation is invariant under an overall rotation, and handles
any orientation of the orbital plane as well as the Euler-angle technique
handles non-precessing binaries.


title: Mixing stops at the LHC

abstract:
  We study the phenomenology of a light stop NLSP in the presence of large
mixing with either the first or the second generation. R-symmetric models
provide a prime setting for this scenario, but our discussion also applies to
the MSSM when a significant amount of mixing can be accommodated. In our
framework the dominant stop decay is through the flavor violating mode into a
light jet and the LSP in an extended region of parameter space. There are
currently no limits from ATLAS and CMS in this region. We emulate shape-based
hadronic SUSY searches for this topology, and find that they have potential
sensitivity. If the extension of these analyses to this region is robust, we
find that these searches can set strong exclusion limits on light stops. If
not, then the flavor violating decay mode is challenging and may represent a
blind spot in stop searches even at 13 TeV. Thus, an experimental investigation
of this scenario is well motivated.


title: Graviweak Unification, Invisible Universe and Dark Energy

abstract:
  We consider a Graviweak Unification model with the assumption of the
existence of the hidden (invisible) sector of our Universe parallel to the
visible world. This Hidden World (HW) is assumed to be a Mirror World (MW) with
broken mirror parity. We start with a diffeomorphism invariant theory of a
gauge field valued in a Lie algebra g, which is broken spontaneously to the
direct sum of the spacetime Lorentz algebra and the Yang-Mills algebra: $\tilde
{\mathfrak g} = {\mathfrak su}(2)^{(grav)}_L \oplus {\mathfrak su}(2)_L$ -- in
the ordinary world, and $\tilde {\mathfrak g}' = {{\mathfrak
su}(2)'}^{(grav)}_R \oplus {\mathfrak su}(2)'_R$ -- in the hidden world. Using
an extension of the Plebanski action for general relativity, we recover the
actions for gravity, SU(2) Yang-Mills and Higgs fields in both (visible and
invisible) sectors of the Universe, and also the total action. After symmetry
breaking, all physical constants, including the Newton's constants,
cosmological constants, Yang-Mills couplings, and other parameters, are
determined by a single parameter $g$ presented in the initial action, and by
the Higgs VEVs. The Dark Energy problem of this model predicts a too large
supersymmetric breaking scale ($\sim 10^{10}-10^{12}$ GeV), which is not within
the reach of the LHC experiments.


title: Lescop's Invariant and Gauge Theory

abstract:
  Taubes proved that the Casson invariant of an integral homology 3-sphere
equals half the Euler characteristic of its instanton Floer homology. We extend
this result to all closed oriented 3-manifolds with positive first Betti number
by establishing a similar relationship between the Lescop invariant of the
manifold and its instanton Floer homology. The proof uses surgery techniques.


title: Minimal Controllability Problems

abstract:
  Given a linear system, we consider the problem of finding a small set of
variables to affect with an input so that the resulting system is controllable.
We show that this problem is NP-hard; indeed, we show that even approximating
the minimum number of variables that need to be affected within a
multiplicative factor of $c \log n$ is NP-hard for some positive $c$. On the
positive side, we show it is possible to find sets of variables matching this
inapproximability barrier in polynomial time. This can be done by a simple
greedy heuristic which sequentially picks variables to maximize the rank
increase of the controllability matrix. Experiments on Erdos-Renyi random
graphs demonstrate this heuristic almost always succeeds at findings the
minimum number of variables.


title: Quasi-static evolution and congested crowd transport

abstract:
  We consider the relationship between Hele-Shaw evolution with drift, the
porous medium equation with superharmonic drift, and a congested crowd motion
model originally proposed by [MRS]- [MRSV]. We first use viscosity solutions to
show that the porous medium equation solutions converge to the Hele- Shaw
solution as the exponent tends to infinity. Next, using of the gradient flow
structure of both the porous medium equation and the crowd motion model, we
prove that the porous medium equation solutions also converge to the congested
crowd motion. Combining these results lets us deduce that in the case where the
initial data to the crowd motion model is given by a patch, or characteristic
function, the solution evolves as a patch that is the unique solution to the
Hele-Shaw problem. While proving our main results we also obtain a comparison
principle for solutions to the minimizing movement scheme based on the
Wasserstein metric, of independent interest.


title: R-Estimation for Asymmetric Independent Component Analysis

abstract:
  Independent Component Analysis (ICA) recently has attracted attention in the
statistical literature as an alternative to elliptical models. Whereas
k-dimensional elliptical densities depend on one single unspecified radial
density, however, k-dimensional independent component distributions involve k
unspecified component densities that for given sample size n and dimension k
making statistical analysis harder. We focus here on estimating the model's
mixing matrix. Traditional methods (FOBI, Kernel-ICA, FastICA) originating from
the engineering literature have consistency that requires moment conditions
without achieving any type of asymptotic efficiency. When based on robust
scatter matrices, the two-scatter methods developed by Oja, et al. (2006) and
Nordhausen, et al. (2008) enjoy better robustness features but have unclear
optimality properties. The semiparametric approach by Chen and Bickel (2006)
achieves semiparametric efficiency but requires estimating the k unobserved
independent component densities. As a reaction, an efficient
(signed-)rank-based approach has been proposed by Ilmonen and Paindaveine
(2011) for the case of symmetric component densities that fail to be root-n
consistent as soon as one of the component densities is asymmetric. In this
paper, using ranks rather than signed ranks, we extend their approach to the
asymmetric case and propose a one-step R-estimator for ICA mixing matrices. The
finite-sample performances of those estimators are investigated and compared to
those of existing methods under moderately large sample sizes. Particularly
good performances are obtained when using data-driven scores taking into
account the skewness and kurtosis of residuals. Finally, we show, by an
empirical exercise, that our methods also may provide excellent results in a
context such as image analysis, where the basic assumptions of ICA are quite
unlikely to hold.


title:
Time (in)consistency of multistage distributionally robust inventory
  models with moment constraints

abstract:
  Recently, there has been a growing interest in developing inventory control
policies which are robust to model misspecification. One approach is to posit
that nature selects a worst-case distribution for any stochastic primitives
from some pre-specified family. Several communities have observed that a subtle
phenomena known as time inconsistency can arise in this framework. In
particular, it becomes possible that a policy which is optimal at time zero may
not be optimal for the associated optimization problem in which the
decision-maker recomputes her policy at each point in time, which has
implications for implementability. If there exists a policy which is optimal
for both formulations, we say that the policy is time consistent, and the
problem is weakly time consistent. If every optimal policy is time consistent,
we say that the problem is strongly time consistent. We study these phenomena
in the context of managing an inventory over time, when only the mean,
variance, and support are known for the demand at each stage. We provide
several illustrative examples showing that here the question of time
consistency can be quite subtle, and complement these observations by providing
simple sufficient conditions for weak and strong time consistency.
Interestingly, our results show that time consistency may hold even when
rectangularity does not. Although a similar phenomena was previously identified
by Shapiro for the setting in which only the mean and support of the demand are
known, there the problem was always weakly time consistent, with both
formulations having the same optimal value. Here our model is rich enough to
exhibit a variety of interesting behaviors, including lack of weak time
consistency, strong time consistency even when both formulations have different
optimal values, and non-existence of even a single optimal base-stock policy
under the static formulation.


title: Application of Evidential Reasoning to Helicopter Flight Path Control

abstract:
  This paper presents a methodology for research and development of the
inferencing and knowledge representation aspects of an Expert System approach
for performing reasoning under uncertainty in support of a real time vehicle
guidance and navigation system. Such a system could be of major benefit for
non-terrain following low altitude flight systems operating in foreign hostile
environments such as might be experienced by NOE helicopter or similar mission
craft. An innovative extension of the evidential reasoning methodology, termed
the Sum-and-Lattice-Points Method, has been developed. The research and
development effort presented in this paper consists of a formal mathematical
development of the Sum-and-Lattice-Points Method, its formulation and
representation in a parallel environment, prototype software development of the
method within an expert system, and initial testing of the system within the
confines of the vehicle guidance system.


title: Knowledge Engineering Within A Generalized Bayesian Framework

abstract:
  During the ongoing debate over the representation of uncertainty in
Artificial Intelligence, Cheeseman, Lemmer, Pearl, and others have argued that
probability theory, and in particular the Bayesian theory, should be used as
the basis for the inference mechanisms of Expert Systems dealing with
uncertainty. In order to pursue the issue in a practical setting, sophisticated
tools for knowledge engineering are needed that allow flexible and
understandable interaction with the underlying knowledge representation
schemes. This paper describes a Generalized Bayesian framework for building
expert systems which function in uncertain domains, using algorithms proposed
by Lemmer. It is neither rule-based nor frame-based, and requires a new system
of knowledge engineering tools. The framework we describe provides a
knowledge-based system architecture with an inference engine, explanation
capability, and a unique aid for building consistent knowledge bases.


title: Taxonomy, Structure, and Implementation of Evidential Reasoning

abstract:
  The fundamental elements of evidential reasoning problems are described,
followed by a discussion of the structure of various types of problems.
Bayesian inference networks and state space formalism are used as the tool for
problem representation.
  A human-oriented decision making cycle for solving evidential reasoning
problems is described and illustrated for a military situation assessment
problem. The implementation of this cycle may serve as the basis for an expert
system shell for evidential reasoning; i.e. a situation assessment processor.


title: Probabilistic Reasoning About Ship Images

abstract:
  One of the most important aspects of current expert systems technology is the
ability to make causal inferences about the impact of new evidence. When the
domain knowledge and problem knowledge are uncertain and incomplete Bayesian
reasoning has proven to be an effective way of forming such inferences [3,4,8].
While several reasoning schemes have been developed based on Bayes Rule, there
has been very little work examining the comparative effectiveness of these
schemes in a real application. This paper describes a knowledge based system
for ship classification [1], originally developed using the PROSPECTOR updating
method [2], that has been reimplemented to use the inference procedure
developed by Pearl and Kim [4,5]. We discuss our reasons for making this
change, the implementation of the new inference engine, and the comparative
performance of the two versions of the system.


title: Towards The Inductive Acquisition of Temporal Knowledge

abstract:
  The ability to predict the future in a given domain can be acquired by
discovering empirically from experience certain temporal patterns that tend to
repeat unerringly. Previous works in time series analysis allow one to make
quantitative predictions on the likely values of certain linear variables.
Since certain types of knowledge are better expressed in symbolic forms, making
qualitative predictions based on symbolic representations require a different
approach. A domain independent methodology called TIM (Time based Inductive
Machine) for discovering potentially uncertain temporal patterns from real time
observations using the technique of inductive inference is described here.


title: Some Extensions of Probabilistic Logic

abstract:
  In [12], Nilsson proposed the probabilistic logic in which the truth values
of logical propositions are probability values between 0 and 1. It is
applicable to any logical system for which the consistency of a finite set of
propositions can be established. The probabilistic inference scheme reduces to
the ordinary logical inference when the probabilities of all propositions are
either 0 or 1. This logic has the same limitations of other probabilistic
reasoning systems of the Bayesian approach. For common sense reasoning,
consistency is not a very natural assumption. We have some well known examples:
{Dick is a Quaker, Quakers are pacifists, Republicans are not pacifists, Dick
is a Republican}and {Tweety is a bird, birds can fly, Tweety is a penguin}. In
this paper, we shall propose some extensions of the probabilistic logic. In the
second section, we shall consider the space of all interpretations, consistent
or not. In terms of frames of discernment, the basic probability assignment
(bpa) and belief function can be defined. Dempster's combination rule is
applicable. This extension of probabilistic logic is called the evidential
logic in [ 1]. For each proposition s, its belief function is represented by an
interval [Spt(s), Pls(s)]. When all such intervals collapse to single points,
the evidential logic reduces to probabilistic logic (in the generalized version
of not necessarily consistent interpretations). Certainly, we get Nilsson's
probabilistic logic by further restricting to consistent interpretations. In
the third section, we shall give a probabilistic interpretation of
probabilistic logic in terms of multi-dimensional random variables. This
interpretation brings the probabilistic logic into the framework of probability
theory. Let us consider a finite set S = {sl, s2, ..., Sn) of logical
propositions. Each proposition may have true or false values; and may be
considered as a random variable. We have a probability distribution for each
proposition. The e-dimensional random variable (sl,..., Sn) may take values in
the space of all interpretations of 2n binary vectors. We may compute absolute
(marginal), conditional and joint probability distributions. It turns out that
the permissible probabilistic interpretation vector of Nilsson [12] consists of
the joint probabilities of S. Inconsistent interpretations will not appear, by
setting their joint probabilities to be zeros. By summing appropriate joint
probabilities, we get probabilities of individual propositions or subsets of
propositions. Since the Bayes formula and other techniques are valid for
e-dimensional random variables, the probabilistic logic is actually very close
to the Bayesian inference schemes. In the last section, we shall consider a
relaxation scheme for probabilistic logic. In this system, not only new
evidences will update the belief measures of a collection of propositions, but
also constraint satisfaction among these propositions in the relational network
will revise these measures. This mechanism is similar to human reasoning which
is an evaluative process converging to the most satisfactory result. The main
idea arises from the consistent labeling problem in computer vision. This
method is originally applied to scene analysis of line drawings. Later, it is
applied to matching, constraint satisfaction and multi sensor fusion by several
authors [8], [16] (and see references cited there). Recently, this method is
used in knowledge aggregation by Landy and Hummel [9].


title: Predicting The Performance of Minimax and Product in Game-Tree

abstract:
  The discovery that the minimax decision rule performs poorly in some games
has sparked interest in possible alternatives to minimax. Until recently, the
only games in which minimax was known to perform poorly were games which were
mainly of theoretical interest. However, this paper reports results showing
poor performance of minimax in a more common game called kalah. For the kalah
games tested, a non-minimax decision rule called the product rule performs
significantly better than minimax.
  This paper also discusses a possible way to predict whether or not minimax
will perform well in a game when compared to product. A parameter called the
rate of heuristic flaw (rhf) has been found to correlate positively with the.
performance of product against minimax. Both analytical and experimental
results are given that appear to support the predictive power of rhf.


title: Reasoning With Uncertain Knowledge

abstract:
  A model of knowledge representation is described in which propositional facts
and the relationships among them can be supported by other facts. The set of
knowledge which can be supported is called the set of cognitive units, each
having associated descriptions of their explicit and implicit support
structures, summarizing belief and reliability of belief. This summary is
precise enough to be useful in a computational model while remaining
descriptive of the underlying symbolic support structure. When a fact supports
another supportive relationship between facts we call this meta-support. This
facilitates reasoning about both the propositional knowledge. and the support
structures underlying it.


title: Models vs. Inductive Inference for Dealing With Probabilistic Knowledge

abstract:
  Two different approaches to dealing with probabilistic knowledge are examined
-models and inductive inference. Examples of the first are: influence diagrams
[1], Bayesian networks [2], log-linear models [3, 4]. Examples of the second
are: games-against nature [5, 6] varieties of maximum-entropy methods [7, 8,
9], and the author's min-score induction [10]. In the modeling approach, the
basic issue is manageability, with respect to data elicitation and computation.
Thus, it is assumed that the pertinent set of users in some sense knows the
relevant probabilities, and the problem is to format that knowledge in a way
that is convenient to input and store and that allows computation of the
answers to current questions in an expeditious fashion. The basic issue for the
inductive approach appears at first sight to be very different. In this
approach it is presumed that the relevant probabilities are only partially
known, and the problem is to extend that incomplete information in a reasonable
way to answer current questions. Clearly, this approach requires that some form
of induction be invoked. Of course, manageability is an important additional
concern. Despite their seeming differences, the two approaches have a fair
amount in common, especially with respect to the structural framework they
employ. Roughly speaking, this framework involves identifying clusters of
variables which strongly interact, establishing marginal probability
distributions on the clusters, and extending the subdistributions to a more
complete distribution, usually via a product formalism. The product extension
is justified on the modeling approach in terms of assumed conditional
independence; in the inductive approach the product form arises from an
inductive rule.


title: Towards a General-Purpose Belief Maintenance System

abstract:
  There currently exists a gap between the theories proposed by the probability
and uncertainty and the needs of Artificial Intelligence research. These
theories primarily address the needs of expert systems, using knowledge
structures which must be pre-compiled and remain static in structure during
runtime. Many Al systems require the ability to dynamically add and remove
parts of the current knowledge structure (e.g., in order to examine what the
world would be like for different causal theories). This requires more
flexibility than existing uncertainty systems display. In addition, many Al
researchers are only interested in using "probabilities" as a means of
obtaining an ordering, rather than attempting to derive an accurate
probabilistic account of a situation. This indicates the need for systems which
stress ease of use and don't require extensive probability information when one
cannot (or doesn't wish to) provide such information. This paper attempts to
help reconcile the gap between approaches to uncertainty and the needs of many
AI systems by examining the control issues which arise, independent of a
particular uncertainty calculus. when one tries to satisfy these needs. Truth
Maintenance Systems have been used extensively in problem solving tasks to help
organize a set of facts and detect inconsistencies in the believed state of the
world. These systems maintain a set of true/false propositions and their
associated dependencies. However, situations often arise in which we are unsure
of certain facts or in which the conclusions we can draw from available
information are somewhat uncertain. The non-monotonic TMS 12] was an attempt at
reasoning when all the facts are not known, but it fails to take into account
degrees of belief and how available evidence can combine to strengthen a
particular belief. This paper addresses the problem of probabilistic reasoning
as it applies to Truth Maintenance Systems. It describes a belief Maintenance
System that manages a current set of beliefs in much the same way that a TMS
manages a set of true/false propositions. If the system knows that belief in
fact is dependent in some way upon belief in fact2, then it automatically
modifies its belief in facts when new information causes a change in belief of
fact2. It models the behavior of a TMS, replacing its 3-valued logic (true,
false, unknown) with an infinite valued logic, in such a way as to reduce to a
standard TMS if all statements are given in absolute true/false terms. Belief
Maintenance Systems can, therefore, be thought of as a generalization of Truth
Maintenance Systems, whose possible reasoning tasks are a superset of those for
a TMS.


title: Planning, Scheduling, and Uncertainty in the Sequence of Future Events

abstract:
  Scheduling in the factory setting is compounded by computational complexity
and temporal uncertainty. Together, these two factors guarantee that the
process of constructing an optimal schedule will be costly and the chances of
executing that schedule will be slight. Temporal uncertainty in the task
execution time can be offset by several methods: eliminate uncertainty by
careful engineering, restore certainty whenever it is lost, reduce the
uncertainty by using more accurate sensors, and quantify and circumscribe the
remaining uncertainty. Unfortunately, these methods focus exclusively on the
sources of uncertainty and fail to apply knowledge of the tasks which are to be
scheduled. A complete solution must adapt the schedule of activities to be
performed according to the evolving state of the production world. The example
of vision-directed assembly is presented to illustrate that the principle of
least commitment, in the creation of a plan, in the representation of a
schedule, and in the execution of a schedule, enables a robot to operate
intelligently and efficiently, even in the presence of considerable uncertainty
in the sequence of future events.


title:
Deriving And Combining Continuous Possibility Functions in the Framework
  of Evidential Reasoning

abstract:
  To develop an approach to utilizing continuous statistical information within
the Dempster- Shafer framework, we combine methods proposed by Strat and by
Shafero We first derive continuous possibility and mass functions from
probability-density functions. Then we propose a rule for combining such
evidence that is simpler and more efficiently computed than Dempster's rule. We
discuss the relationship between Dempster's rule and our proposed rule for
combining evidence over continuous frames.


title: Non-Monotonicity in Probabilistic Reasoning

abstract:
  We start by defining an approach to non-monotonic probabilistic reasoning in
terms of non-monotonic categorical (true-false) reasoning. We identify a type
of non-monotonic probabilistic reasoning, akin to default inheritance, that is
commonly found in practice, especially in "evidential" and "Bayesian"
reasoning. We formulate this in terms of the Maximization of Conditional
Independence (MCI), and identify a variety of applications for this sort of
default. We propose a formalization using Pointwise Circumscription. We compare
MCI to Maximum Entropy, another kind of non-monotonic principle, and conclude
by raising a number of open questions


title: Information and Multi-Sensor Coordination

abstract:
  The control and integration of distributed, multi-sensor perceptual systems
is a complex and challenging problem. The observations or opinions of different
sensors are often disparate incomparable and are usually only partial views.
Sensor information is inherently uncertain and in addition the individual
sensors may themselves be in error with respect to the system as a whole. The
successful operation of a multi-sensor system must account for this uncertainty
and provide for the aggregation of disparate information in an intelligent and
robust manner. We consider the sensors of a multi-sensor system to be members
or agents of a team, able to offer opinions and bargain in group decisions. We
will analyze the coordination and control of this structure using a theory of
team decision-making. We present some new analytic results on multi-sensor
aggregation and detail a simulation which we use to investigate our ideas. This
simulation provides a basis for the analysis of complex agent structures
cooperating in the presence of uncertainty. The results of this study are
discussed with reference to multi-sensor robot systems, distributed Al and
decision making under uncertainty.


title:
Flexible Interpretations: A Computational Model for Dynamic Uncertainty
  Assessment

abstract:
  The investigations reported in this paper center on the process of dynamic
uncertainty assessment during interpretation tasks in real domain. In
particular, we are interested here in the nature of the control structure of
computer programs that can support multiple interpretation and smooth
transitions between them, in real time. Each step of the processing involves
the interpretation of one input item and the appropriate re-establishment of
the system's confidence of the correctness of its interpretation(s).


title: The Myth of Modularity in Rule-Based Systems

abstract:
  In this paper, we examine the concept of modularity, an often cited advantage
of the ruled-based representation methodology. We argue that the notion of
modularity consists of two distinct concepts which we call syntactic modularity
and semantic modularity. We argue that when reasoning under certainty, it is
reasonable to regard the rule-based approach as both syntactically and
semantically modular. However, we argue that in the case of plausible
reasoning, rules are syntactically modular but are rarely semantically modular.
To illustrate this point, we examine a particular approach for managing
uncertainty in rule-based systems called the MYCIN certainty factor model. We
formally define the concept of semantic modularity with respect to the
certainty factor model and discuss logical consequences of the definition. We
show that the assumption of semantic modularity imposes strong restrictions on
rules in a knowledge base. We argue that such restrictions are rarely valid in
practical applications. Finally, we suggest how the concept of semantic
modularity can be relaxed in a manner that makes it appropriate for plausible
reasoning.


title: An Axiomatic Framework for Belief Updates

abstract:
  In the 1940's, a physicist named Cox provided the first formal justification
for the axioms of probability based on the subjective or Bayesian
interpretation. He showed that if a measure of belief satisfies several
fundamental properties, then the measure must be some monotonic transformation
of a probability. In this paper, measures of change in belief or belief updates
are examined. In the spirit of Cox, properties for a measure of change in
belief are enumerated. It is shown that if a measure satisfies these
properties, it must satisfy other restrictive conditions. For example, it is
shown that belief updates in a probabilistic context must be equal to some
monotonic transformation of a likelihood ratio. It is hoped that this formal
explication of the belief update paradigm will facilitate critical discussion
and useful extensions of the approach.


title:
Imprecise Meanings as a Cause of Uncertainty in Medical Knowledge-Based
  Systems

abstract:
  There has been a considerable amount of work on uncertainty in
knowledge-based systems. This work has generally been concerned with
uncertainty arising from the strength of inferences and the weight of evidence.
In this paper we discuss another type of uncertainty: that which is due to
imprecision in the underlying primitives used to represent the knowledge of the
system. In particular, a given word may denote many similar but not identical
entities. Such words are said to be lexically imprecise. Lexical imprecision
has caused widespread problems in many areas. Unless this phenomenon is
recognized and appropriately handled, it can degrade the performance of
knowledge-based systems. In particular, it can lead to difficulties with the
user interface, and with the inferencing processes of these systems. Some
techniques are suggested for coping with this phenomenon.


title: Evidence as Opinions of Experts

abstract:
  We describe a viewpoint on the Dempster/Shafer 'Theory of Evidence', and
provide an interpretation which regards the combination formulas as statistics
of the opinions of "experts". This is done by introducing spaces with binary
operations that are simpler to interpret or simpler to implement than the
standard combination formula, and showing that these spaces can be mapped
homomorphically onto the Dempster/Shafer theory of evidence space. The experts
in the space of "opinions of experts" combine information in a Bayesian
fashion. We present alternative spaces for the combination of evidence
suggested by this viewpoint.


title: Decision Under Uncertainty in Diagnosis

abstract:
  This paper describes the incorporation of uncertainty in diagnostic reasoning
based on the set covering model of Reggia et. al. extended to what in the
Artificial Intelligence dichotomy between deep and compiled (shallow, surface)
knowledge based diagnosis may be viewed as the generic form at the compiled end
of the spectrum. A major undercurrent in this is advocating the need for a
strong underlying model and an integrated set of support tools for carrying
such a model in order to deal with uncertainty.


title: Knowledge and Uncertainty

abstract:
  One purpose -- quite a few thinkers would say the main purpose -- of seeking
knowledge about the world is to enhance our ability to make good decisions. An
item of knowledge that can make no conceivable difference with regard to
anything we might do would strike many as frivolous. Whether or not we want to
be philosophical pragmatists in this strong sense with regard to everything we
might want to enquire about, it seems a perfectly appropriate attitude to adopt
toward artificial knowledge systems. If is granted that we are ultimately
concerned with decisions, then some constraints are imposed on our measures of
uncertainty at the level of decision making. If our measure of uncertainty is
real-valued, then it isn't hard to show that it must satisfy the classical
probability axioms. For example, if an act has a real-valued utility U(E) if
the event E obtains, and the same real-valued utility if the denial of E
obtains, so that U(E) = U(-E), then the expected utility of that act must be
U(E), and that must be the same as the uncertainty-weighted average of the
returns of the act, p-U(E) + q-U('E), where p and q represent the uncertainty
of E and-E respectively. But then we must have p + q = 1.


title:
An Application of Non-Monotonic Probabilistic Reasoning to Air Force
  Threat Correlation

abstract:
  Current approaches to expert systems' reasoning under uncertainty fail to
capture the iterative revision process characteristic of intelligent human
reasoning. This paper reports on a system, called the Non-monotonic
Probabilist, or NMP (Cohen, et al., 1985). When its inferences result in
substantial conflict, NMP examines and revises the assumptions underlying the
inferences until conflict is reduced to acceptable levels. NMP has been
implemented in a demonstration computer-based system, described below, which
supports threat correlation and in-flight route replanning by Air Force pilots.


title: Bayesian Inference for Radar Imagery Based Surveillance

abstract:
  We are interested in creating an automated or semi-automated system with the
capability of taking a set of radar imagery, collection parameters and a priori
map and other tactical data, and producing likely interpretations of the
possible military situations given the available evidence. This paper is
concerned with the problem of the interpretation and computation of certainty
or belief in the conclusions reached by such a system.


title: Evidential Reasoning in Parallel Hierarchical Vision Programs

abstract:
  This paper presents an efficient adaptation and application of the
Dempster-Shafer theory of evidence, one that can be used effectively in a
massively parallel hierarchical system for visual pattern perception. It
describes the techniques used, and shows in an extended example how they serve
to improve the system's performance as it applies a multiple-level set of
processes.


title: Computing Reference Classes

abstract:
  For any system with limited statistical knowledge, the combination of
evidence and the interpretation of sampling information require the
determination of the right reference class (or of an adequate one). The present
note (1) discusses the use of reference classes in evidential reasoning, and
(2) discusses implementations of Kyburg's rules for reference classes. This
paper contributes the first frank discussion of how much of Kyburg's system is
needed to be powerful, how much can be computed effectively, and how much is
philosophical fat.


title:
An Uncertainty Management Calculus for Ordering Searches in Distributed
  Dynamic Databases

abstract:
  MINDS is a distributed system of cooperating query engines that customize,
document retrieval for each user in a dynamic environment. It improves its
performance and adapts to changing patterns of document distribution by
observing system-user interactions and modifying the appropriate certainty
factors, which act as search control parameters. It argued here that the
uncertainty management calculus must account for temporal precedence,
reliability of evidence, degree of support for a proposition, and saturation
effects. The calculus presented here possesses these features. Some results
obtained with this scheme are discussed.


title: An Explanation Mechanism for Bayesian Inferencing Systems

abstract:
  Explanation facilities are a particularly important feature of expert system
frameworks. It is an area in which traditional rule-based expert system
frameworks have had mixed results. While explanations about control are well
handled, facilities are needed for generating better explanations concerning
knowledge base content. This paper approaches the explanation problem by
examining the effect an event has on a variable of interest within a symmetric
Bayesian inferencing system. We argue that any effect measure operating in this
context must satisfy certain properties. Such a measure is proposed. It forms
the basis for an explanation facility which allows the user of the Generalized
Bayesian Inferencing System to question the meaning of the knowledge base. That
facility is described in detail.


title:
Distributed Revision of Belief Commitment in Multi-Hypothesis
  Interpretations

abstract:
  This paper extends the applications of belief-networks to include the
revision of belief commitments, i.e., the categorical acceptance of a subset of
hypotheses which, together, constitute the most satisfactory explanation of the
evidence at hand. A coherent model of non-monotonic reasoning is established
and distributed algorithms for belief revision are presented. We show that, in
singly connected networks, the most satisfactory explanation can be found in
linear time by a message-passing algorithm similar to the one used in belief
updating. In multiply-connected networks, the problem may be exponentially hard
but, if the network is sparse, topological considerations can be used to render
the interpretation task tractable. In general, finding the most probable
combination of hypotheses is no more complex than computing the degree of
belief for any individual hypothesis. Applications to medical diagnosis are
illustrated.


title: Learning Link-Probabilities in Causal Trees

abstract:
  A learning algorithm is presented which given the structure of a causal tree,
will estimate its link probabilities by sequential measurements on the leaves
only. Internal nodes of the tree represent conceptual (hidden) variables
inaccessible to observation. The method described is incremental, local,
efficient, and remains robust to measurement imprecisions.


title: Approximate Deduction in Single Evidential Bodies

abstract:
  Results on approximate deduction in the context of the calculus of evidence
of Dempster-Shafer and the theory of interval probabilities are reported.
Approximate conditional knowledge about the truth of conditional propositions
was assumed available and expressed as sets of possible values (actually
numeric intervals) of conditional probabilities. Under different
interpretations of this conditional knowledge, several formulas were produced
to integrate unconditioned estimates (assumed given as sets of possible values
of unconditioned probabilities) with conditional estimates. These formulas are
discussed together with the computational characteristics of the methods
derived from them. Of particular importance is one such evidence integration
formulation, produced under a belief oriented interpretation, which
incorporates both modus ponens and modus tollens inferential mechanisms, allows
integration of conditioned and unconditioned knowledge without resorting to
iterative or sequential approximations, and produces elementary mass
distributions as outputs using similar distributions as inputs.


title:
The Rational and Computational Scope of Probabilistic Rule-Based Expert
  Systems

abstract:
  Belief updating schemes in artificial intelligence may be viewed as three
dimensional languages, consisting of a syntax (e.g. probabilities or certainty
factors), a calculus (e.g. Bayesian or CF combination rules), and a semantics
(i.e. cognitive interpretations of competing formalisms). This paper studies
the rational scope of those languages on the syntax and calculus grounds. In
particular, the paper presents an endomorphism theorem which highlights the
limitations imposed by the conditional independence assumptions implicit in the
CF calculus. Implications of the theorem to the relationship between the CF and
the Bayesian languages and the Dempster-Shafer theory of evidence are
presented. The paper concludes with a discussion of some implications on
rule-based knowledge engineering in uncertain domains.


title: A Causal Bayesian Model for the Diagnosis of Appendicitis

abstract:
  The causal Bayesian approach is based on the assumption that effects (e.g.,
symptoms) that are not conditionally independent with respect to some causal
agent (e.g., a disease) are conditionally independent with respect to some
intermediate state caused by the agent, (e.g., a pathological condition). This
paper describes the development of a causal Bayesian model for the diagnosis of
appendicitis. The paper begins with a description of the standard Bayesian
approach to reasoning about uncertainty and the major critiques it faces. The
paper then lays the theoretical groundwork for the causal extension of the
Bayesian approach, and details specific improvements we have developed. The
paper then goes on to describe our knowledge engineering and implementation and
the results of a test of the system. The paper concludes with a discussion of
how the causal Bayesian approach deals with the criticisms of the standard
Bayesian model and why it is superior to alternative approaches to reasoning
about uncertainty popular in the Al community.


title: A Backwards View for Assessment

abstract:
  Much artificial intelligence research focuses on the problem of deducing the
validity of unobservable propositions or hypotheses from observable evidence.!
Many of the knowledge representation techniques designed for this problem
encode the relationship between evidence and hypothesis in a directed manner.
Moreover, the direction in which evidence is stored is typically from evidence
to hypothesis.


title: DAVID: Influence Diagram Processing System for the Macintosh

abstract:
  Influence diagrams are a directed graph representation for uncertainties as
probabilities. The graph distinguishes between those variables which are under
the control of a decision maker (decisions, shown as rectangles) and those
which are not (chances, shown as ovals), as well as explicitly denoting a goal
for solution (value, shown as a rounded rectangle.


title: Propagation of Belief Functions: A Distributed Approach

abstract:
  In this paper, we describe a scheme for propagating belief functions in
certain kinds of trees using only local computations. This scheme generalizes
the computational scheme proposed by Shafer and Logan1 for diagnostic trees of
the type studied by Gordon and Shortliffe, and the slightly more general scheme
given by Shafer for hierarchical evidence. It also generalizes the scheme
proposed by Pearl for Bayesian causal trees (see Shenoy and Shafer). Pearl's
causal trees and Gordon and Shortliffe's diagnostic trees are both ways of
breaking the evidence that bears on a large problem down into smaller items of
evidence that bear on smaller parts of the problem so that these smaller
problems can be dealt with one at a time. This localization of effort is often
essential in order to make the process of probability judgment feasible, both
for the person who is making probability judgments and for the machine that is
combining them. The basic structure for our scheme is a type of tree that
generalizes both Pearl's and Gordon and Shortliffe's trees. Trees of this
general type permit localized computation in Pearl's sense. They are based on
qualitative judgments of conditional independence. We believe that the scheme
we describe here will prove useful in expert systems. It is now clear that the
successful propagation of probabilities or certainty factors in expert systems
requires much more structure than can be provided in a pure production-system
framework. Bayesian schemes, on the other hand, often make unrealistic demands
for structure. The propagation of belief functions in trees and more general
networks stands on a middle ground where some sensible and useful things can be
done. We would like to emphasize that the basic idea of local computation for
propagating probabilities is due to Judea Pearl. It is a very innovative idea;
we do not believe that it can be found in the Bayesian literature prior to
Pearl's work. We see our contribution as extending the usefulness of Pearl's
idea by generalizing it from Bayesian probabilities to belief functions. In the
next section, we give a brief introduction to belief functions. The notions of
qualitative independence for partitions and a qualitative Markov tree are
introduced in Section III. Finally, in Section IV, we describe a scheme for
propagating belief functions in qualitative Markov trees.


title: Appropriate and Inappropriate Estimation Techniques

abstract:
  Mode {also called MAP} estimation, mean estimation and median estimation are
examined here to determine when they can be safely used to derive {posterior)
cost minimizing estimates. (These are all Bayes procedures, using the mode.
mean. or median of the posterior distribution). It is found that modal
estimation only returns cost minimizing estimates when the cost function is
0-t. If the cost function is a function of distance then mean estimation only
returns cost minimizing estimates when the cost function is squared distance
from the true value and median estimation only returns cost minimizing
estimates when the cost function ts the distance from the true value. Results
are presented on the goodness or modal estimation with non 0-t cost functions


title: Estimating Uncertain Spatial Relationships in Robotics

abstract:
  In this paper, we describe a representation for spatial information, called
the stochastic map, and associated procedures for building it, reading
information from it, and revising it incrementally as new information is
obtained. The map contains the estimates of relationships among objects in the
map, and their uncertainties, given all the available information. The
procedures provide a general solution to the problem of estimating uncertain
relative spatial relationships. The estimates are probabilistic in nature, an
advance over the previous, very conservative, worst-case approaches to the
problem. Finally, the procedures are developed in the context of
state-estimation and filtering theory, which provides a solid basis for
numerous extensions.


title: A VLSI Design and Implementation for a Real-Time Approximate Reasoning

abstract:
  The role of inferencing with uncertainty is becoming more important in
rule-based expert systems (ES), since knowledge given by a human expert is
often uncertain or imprecise. We have succeeded in designing a VLSI chip which
can perform an entire inference process based on fuzzy logic. The design of the
VLSI fuzzy inference engine emphasizes simplicity, extensibility, and
efficiency (operational speed and layout area). It is fabricated in 2.5 um CMOS
technology. The inference engine consists of three major components; a rule set
memory, an inference processor, and a controller. In this implementation, a
rule set memory is realized by a read only memory (ROM). The controller
consists of two counters. In the inference processor, one data path is laid out
for each rule. The number of the inference rule can be increased adding more
data paths to the inference processor. All rules are executed in parallel, but
each rule is processed serially. The logical structure of fuzzy inference
proposed in the current paper maps nicely onto the VLSI structure. A two-phase
nonoverlapping clocking scheme is used. Timing tests indicate that the
inference engine can operate at approximately 20.8 MHz. This translates to an
execution speed of approximately 80,000 Fuzzy Logical Inferences Per Second
(FLIPS), and indicates that the inference engine is suitable for a demanding
real-time application. The potential applications include decision-making in
the area of command and control for intelligent robot systems, process control,
missile and aircraft guidance, and other high performance machines.


title: A General Purpose Inference Engine for Evidential Reasoning Research

abstract:
  The purpose of this paper is to report on the most recent developments in our
ongoing investigation of the representation and manipulation of uncertainty in
automated reasoning systems. In our earlier studies (Tong and Shapiro, 1985) we
described a series of experiments with RUBRIC (Tong et al., 1985), a system for
full-text document retrieval, that generated some interesting insights into the
effects of choosing among a class of scalar valued uncertainty calculi. [n
order to extend these results we have begun a new series of experiments with a
larger class of representations and calculi, and to help perform these
experiments we have developed a general purpose inference engine.


title: Generalizing Fuzzy Logic Probabilistic Inferences

abstract:
  Linear representations for a subclass of boolean symmetric functions selected
by a parity condition are shown to constitute a generalization of the linear
constraints on probabilities introduced by Boole. These linear constraints are
necessary to compute probabilities of events with relations between the.
arbitrarily specified with propositional calculus boolean formulas.


title: Qualitative Probabilistic Networks for Planning Under Uncertainty

abstract:
  Bayesian networks provide a probabilistic semantics for qualitative
assertions about likelihood. A qualitative reasoner based on an algebra over
these assertions can derive further conclusions about the influence of actions.
While the conclusions are much weaker than those computed from complete
probability distributions, they are still valuable for suggesting potential
actions, eliminating obviously inferior plans, identifying important tradeoffs,
and explaining probabilistic models.


title: Experimentally Comparing Uncertain Inference Systems to Probability

abstract:
  This paper examines the biases and performance of several uncertain inference
systems: Mycin, a variant of Mycin. and a simplified version of probability
using conditional independence assumptions. We present axiomatic arguments for
using Minimum Cross Entropy inference as the best way to do uncertain
inference. For Mycin and its variant we found special situations where its
performance was very good, but also situations where performance was worse than
random guessing, or where data was interpreted as having the opposite of its
true import We have found that all three of these systems usually gave accurate
results, and that the conditional independence assumptions gave the most robust
results. We illustrate how the Importance of biases may be quantitatively
assessed and ranked. Considerations of robustness might be a critical factor is
selecting UlS's for a given application.