March 2013 arXiv papers — page 30

Andrea Cipollone, Carlo Barbieri, Petr Navrátil

We extend the formalism of self-consistent Green's function theory to include three-body interactions and apply it to isotopic chains around oxygen for the first time. The third-order algebraic diagrammatic construction [ADC(3)] equations for two-body Hamiltonians can be exploited upon defining system-dependent one- and two-body interactions coming from

Martino Borello, Francesca Dalla Volta, Gabriele Nebe

A computer calculation with Magma shows that there is no extremal self-dual binary code C of length 72, whose automorphism group contains the symmetric group of degree 3, the alternating group of degree 4 or the dihedral group of order 8. Combining this with the known results in the literature one obtains that Aut(C) has order at most 5 or isomorphic to the

Alexi Morin-Duchesne, Paul A. Pearce, Jorgen Rasmussen

A lattice model of critical dense polymers is solved exactly for arbitrary system size on the torus. More generally, an infinite family of lattice loop models is studied on the torus and related to the corresponding Fortuin-Kasteleyn random cluster models. Starting with a cylinder, the commuting periodic single-row transfer matrices are built from the period

Petros Souvatzis, Anders M. N. Niklasson

We present an efficient general approach to first principles molecular dynamics simulations based on extended Lagrangian Born-Oppenheimer molecular dynamics in the limit of vanishing self-consistent field optimization. The reduction of the optimization requirement reduces the computational cost to a minimum, but without causing any significant loss of accura

Marko Horvat, Siniša Popović, Krešimir Ćosić

Multimedia documents such as images, sounds or videos can be used to elicit emotional responses in exposed human subjects. These stimuli are stored in affective multimedia databases and successfully used for a wide variety of research in affective computing, human-computer interaction and cognitive sciences. Affective multimedia databases are simple reposito

L. Dorame, O. G. Miranda, J. W. F. Valle

Gamma-ray bursts (GRBs) are expected to provide a source of ultra high energy cosmic rays, accompanied with potentially detectable neutrinos at neutrino telescopes. Recently, IceCube has set an upper bound on this neutrino flux well below theoretical expectation. We investigate whether this mismatch between expectation and observation can be due to neutrino

Sandy S. C. Law, Kristian L. McDonald

The seesaw mechanism can be generalized to a Type-III variant and a quintuplet variant. We present two models that provide analogous generalizations of the inverse seesaw mechanism. The first model employs a fermion triplet F ~ (1,3,0) and requires no additional multiplets or parameters relative to the standard inverse seesaw. We argue that, from a bottom-up

Li-Bang Wang, Wei-Tou Ni

We propose a theoretical scenario to solve the proton radius puzzle which recently arises from the muonic hydrogen experiment. In this framework, 4 + n dimensional theory is incorporated with modified gravity. The extra gravitational interaction between the proton and muon at very short range provides an energy shift which accounts for the discrepancy betwee

Hang-Hyun Jo, Raj Kumar Pan, Juan I. Perotti, Kimmo Kaski

To understand the origin of bursty dynamics in natural and social processes we provide a general analysis framework, in which the temporal process is decomposed into sub-processes and then the bursts in sub-processes, called contextual bursts, are combined to collective bursts in the original process. For the combination of sub-processes, it is required to c

Denis I. Borisov, Miloslav Znojil

Unavoided crossings of the energy levels due to a variation of a real parameter are studied. It is found that after the quantum system in question passes through one of its energy-crossing points {\it alias} Kato's exceptional points (EP), its physical interpretation may {\em dramatically} change even when the crossing energies themselves do not complexi

Danail Obreschkow, Marc Tinguely, Nicolas Dorsaz, Philippe Kobel

We describe a recently realized experiment producing the most spherical cavitation bubbles today. The bubbles grow inside a liquid from a point-plasma generated by a nanosecond laser pulse. Unlike in previous studies, the laser is focussed by a parabolic mirror, resulting in a plasma of unprecedented symmetry. The ensuing bubbles are sufficiently spherical t

Nobuhiro Nakamura

We introduce a diffeomorphism invariant of $4$-manifolds, the $\mathrm{Pin}^-(2)$-monopole invariant, defined by using the $\mathrm{Pin}^-(2)$-monopole equations. We compute the invariants of several $4$-manifolds, and prove gluing formulae. By using the invariants, we construct exotic smooth structures on the connected sum of an elliptic surface $E(n)$ with

Song-Yon Kim, Mun-Chol Kim

In this paper we studied about the wavelet identification of the thresholds and time delay for more general case without the constraint that the time delay is smaller than the order of the model. Here we composed an empirical wavelet from the SETAR (Self-Exciting Threshold Autoregressive) model and identified the thresholds and time delay in the model using

Zhihai Wang, D. L. Zhou

Within the capacity of current experiments, we design a composite atom-cavity system with a common bath, in which the decay channels of the atom and the cavity mode interfere with each other. When the direct atom-cavity coupling is absent, the system can be trapped in a quasi-dark state (the coherent superposition of excited states for the atom and the cavit

Freddy Delbaen, Ying Hu, Adrien Richou

In [3], the authors proved that uniqueness holds among solutions whose exponentials are $L^p$ with $p$ bigger than a constant $γ$ ($p\textgreater{}γ$). In this paper, we consider the critical case: $p=γ$. We prove that the uniqueness holds among solutions whose exponentials are $L^γ$ under the additional assumption that the generator is strongly convex.

Jong-Phil Lee

Unparticle contributions to the recently measured decay mode $B_s\toμ^+μ^-$ are analyzed. We consider only the scalar unparticles because vector unparticles are expected to provide negligible contributions. Assuming that the relevant coupling constants are real, we present allowed regions of coupling constants and the scaling dimension of the scalar unpartic

Kyong-Hui Kim, Hak-Myong Pak

In this article, we consider flexible seasonal time series models which consist of a common trend function over periods and additive individual trend (seasonal effect) functions. The consistency and asymptotic normality of the local linear estimators were obtained under the $α$-mixing conditions and without specifying the error distribution. We develop these

Evgeny Epelbaum, Hermann Krebs, Timo A. Lähde, Dean Lee

We present an ab initio calculation of the quark mass dependence of the ground state energies of ^4He, ^8Be and ^{12}C, and of the energy of the Hoyle state in ^{12}C. These investigations are performed within the framework of lattice chiral Effective Field Theory. We address the sensitivity of the production rate of carbon and oxygen in red giant stars to t

Wen Yuan, Winfried Sickel, Dachun Yang

In this paper we consider smoothness and decay properties of radial functions belonging to smoothness spaces related to Morrey spaces (Sobolev-Morrey spaces, Besov-type spaces and Besov-Morrey spaces). Within this framework we prove generalizations of the Radial Lemma of Strauss.

Xiao-Gang He, Han Phoon, Yong Tang, German Valencia

The recent discovery of a 126 GeV boson at the LHC will be followed by a detailed examination of its couplings in order to determine whether this particle is the Higgs boson of the standard model or one of many particles of an extended scalar sector. One such extension with a rich phenomenology consists of a color octet electroweak doublet scalar. The most g

Nikolai Dokuchaev

The paper studies estimation of parameters of diffusion market models from historical data. The standard definition of implied volatility for these models presents its value as an implicit function of several parameters, including the risk-free interest rate. In reality, the risk free interest rate is unknown and need to be forecasted, because the option pri

Lihua Cao, Yutian Li

A pair of linearly independent asymptotic solutions are constructed for the second-order linear difference equation {equation*} P_{n+1}(x)-(A_{n}x+B_{n})P_{n}(x)+P_{n-1}(x)=0, {equation*} where $A_n$ and $B_n$ have asymptotic expansions of the form {equation*} A_n\sim n^{-θ}\sum_{s=0}^\infty\frac{α_s}{n^s},\qquad B_n\sim\sum_{s=0}^\infty\frac{β_s}{n^s}, {equ

Myong-Song Ho, Gwang-Hui Ju, Yong-Bom O, Gwang-Ho Jong

We proposed an algorithm for solving Hamilton-Jacobi equation associated to an optimal trajectory problem for a vehicle moving inside the pre-specified domain with the speed depending upon the direction of the motion and current position of the vehicle. The dynamics of the vehicle is defined by an ordinary differential equation, the right hand of which is gi

Huy Nguyên Lê, Yu Cai, Xingyao Wu, Valerio Scarani

Complexity is often invoked alongside size and mass as a characteristic of macroscopic quantum objects. In 2004, Aaronson introduced the \textit{tree size} (TS) as a computable measure of complexity and studied its basic properties. In this paper, we improve and expand on those initial results. In particular, we give explicit characterizations of a family of

Richard L. Bishop

These notes on Riemannian geometry use the bases bundle and frame bundle, as in Geometry of Manifolds, to express the geometric structures. It has more problems and omits the background material. It starts with the definition of Riemannian and semi-Riemannian structures on manifolds. Affine connections, geodesics, torsion and curvature, the exponential map,

Lixin Dai, Andres Escala, Paolo Coppi

We have carried out general relativistic particle simulations of stars tidally disrupted by massive black holes. When a star is disrupted in a bound orbit with moderate eccentricity instead of a parabolic orbit, the temporal behavior of the resulting stellar debris changes qualitatively. The debris is initially all bound, returning to pericenter in a short t

Abhishek Majhi

Energy of a black hole is usually quantized by invoking some area quantization scheme after expressing the energy in terms of the horizon area. However, in this approach one has to quantize the local and asymptotic energy of the black hole separately and the two results do not manifest any physical correspondence with each other. Here, as opposed to this pra

Abhishek Majhi

Following a recent proposal, we consider the most general structure possible for the Hamiltonian operator associated with the Quantum Isolated Horizon(QIH) with explanations of the underlying physical motivations. An extensive thermodynamic analysis with this model Hamiltonian is presented. Considering {\it fixed} number of punctures, the canonical partition

Rong-Gen Cai, Li Li, Li-Fang Li, Ru-Keng Su

We continue our study of entanglement entropy in the holographic superconducting phase transitions. In this paper we consider the holographic p-wave superconductor/insulator model, where as the back reaction increases, the transition is changed from second order to first order. We find that unlike the s-wave case, there is no additional first order transitio

Hauke Worpel, Duncan K. Galloway, Daniel J. Price

The standard approach for time-resolved X-ray spectral analysis of thermonuclear bursts involves subtraction of the pre-burst emission as background. This approach implicitly assumes that the persistent flux remains constant throughout the burst. We reanalyzed 332 photospheric radius expansion bursts observed from 40 sources by the Rossi X-ray Timing Explore

Alberto Compagno, Mauro Conti, Paolo Gasti, Gene Tsudik

Content-Centric Networking (CCN) is an emerging networking paradigm being considered as a possible replacement for the current IP-based host-centric Internet infrastructure. In CCN, named content becomes a first-class entity. CCN focuses on content distribution, which dominates current Internet traffic and is arguably not well served by IP. Named-Data Networ

Erik Woodhead

We introduce a quantum cloning bound which we apply to a straightforward and relatively direct security proof of the prepare-and-measure Bennett-Brassard 1984 (BB84) quantum key distribution (QKD) protocol against collective attacks. The approach we propose is able to handle the practical problem of source and detector alignment imprecisions in a simple way.

Yongkun Li, Patrick P. C. Lee, John C. S. Lui

Solid state drives (SSDs) have seen wide deployment in mobiles, desktops, and data centers due to their high I/O performance and low energy consumption. As SSDs write data out-of-place, garbage collection (GC) is required to erase and reclaim space with invalid data. However, GC poses additional writes that hinder the I/O performance, while SSD blocks can on

Jaydip Sen

Cloud computing transforms the way information technology (IT) is consumed and managed, promising improved cost efficiencies, accelerated innovation, faster time-to-market, and the ability to scale applications on demand (Leighton, 2009). According to Gartner, while the hype grew exponentially during 2008 and continued since, it is clear that there is a majo

Brian Simanek

We discuss the relationship between ratio asymptotics for general orthogonal polynomials and the asymptotics of the associated Bergman shift operator. More specifically, we consider the case in which a measure is supported on an infinite compact subset of the complex plane. We show that there is a straightforward connection between the corresponding orthonor

Omid Amini, Matthew Baker, Erwan Brugallé, Joseph Rabinoff

Let K be an algebraically closed, complete non-Archimedean field. The purpose of this paper is to carefully study the extent to which finite morphisms of algebraic K-curves are controlled by certain combinatorial objects, called skeleta. A skeleton is a metric graph embedded in the Berkovich analytification of X. A skeleton has the natural structure of a met

CMS Collaboration

Invariant mass spectra for jets reconstructed using the anti-kt and Cambridge-Aachen algorithms are studied for different jet "grooming" techniques in data corresponding to an integrated luminosity of 5 inverse femtobarns, recorded with the CMS detector in proton-proton collisions at the LHC at a center-of-mass energy of 7 TeV. Leading-order QCD pred

Raul Jimenez, Tsvi Piran

While there are numerous indications that GRBs arise from the death of massive stars, the GRB rate does not follow the global cosmic star formation rate and, within their hosts, GRBs are more concentrated in regions of very high star formation. We explain both puzzles here. Using the publicly available VESPA database of SDSS Data Release 7 spectra, we explor

Jeroen Ooms

The increasing availability of cloud computing and scientific super computers brings great potential for making R accessible through public or shared resources. This allows us to efficiently run code requiring lots of cycles and memory, or embed R functionality into, e.g., systems and web services. However some important security concerns need to be addresse

Jabed H. Tomal, William J. Welch, Ruben H. Zamar

Statistical detection of a rare class of objects in a two-class classification problem can pose several challenges. Because the class of interest is rare in the training data, there is relatively little information in the known class response labels for model building. At the same time the available explanatory variables are often moderately high dimensional

Jorge Soto-Andrade, M. Francisca Yáñez

We show that the Gelfand character $ \chi_G$ of a finite group $G $ (i.e. the sum of all irreducible complex characters of $G$ ) may be realized as a `` twisted trace'' $ g \mapsto Tr( \rho_g \circ T) $ for a suitable involutive linear automorphism $T$ of $L^2(G)$, where $(L^2(G), \rho)$ is the right regular representation of $G$. Moreover, we prove that und

Masoumeh Dashti, Kody J. H. Law, Andrew M. Stuart, Jochen Voss

We consider the inverse problem of estimating an unknown function $u$ from noisy measurements $y$ of a known, possibly nonlinear, map $\mathcal{G}$ applied to $u$. We adopt a Bayesian approach to the problem and work in a setting where the prior measure is specified as a Gaussian random field $μ_0$. We work under a natural set of conditions on the likelihood

Antonio Pasqua, Surajit Chattopadhyay, Iuliia Khomenko

In this paper, we consider a recently proposed model of Dark Energy (DE) know as Modified Holographic Ricci DE (MHRDE) (which is function of the Hubble parameter and its first derivative with respect to the cosmic time $t$) in the light of the $f(R,T)$ model of modified gravity, considering the particular model $f(R,T) = μR + νT$, with $μ$ and $ν$ constants.

Mikhail M. Labushev

The concepts of alpha- and beta-packets of the periodic table of chemical elements and chemical compounds are defined. The first of the 47 minerals alpha-packets is composed. In it all minerals are arranged in increasing Iav index of proportionality of atomic weights of composing chemical elements, the same way as chemical elements are located in increasing

Vladimir Vovk

The game-theoretic version of Kolmogorov's strong law of large numbers says that Skeptic has a strategy forcing the statement of the law in a game of prediction involving Reality, Forecaster, and Skeptic. This note describes a simple matching strategy for Reality.

Bent Flyvbjerg, Mette Skamris Holm, Søren L. Buhl

This article presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth US$59 billion. The study shows with very high statistical significance that forecasters generally do a poor job of estimating the dem

Martin C. Weisskopf

I summarize the excitement of my role primarily in the early years of X-ray Astronomy. As a "second-generation" X-ray astronomer, I was privileged to participate in the enormous advance of the field, both technically and astrophysically, that occurred in the late 1960's and 1970's. The remainder of my career has concentrated on the design, co

Bent Flyvbjerg

The article first describes characteristics of major infrastructure projects. Second, it documents a much neglected topic in economics: that ex ante estimates of costs and benefits are often very different from actual ex post costs and benefits. For large infrastructure projects the consequence is cost overruns, benefit shortfalls, and the systematic underes

Bent Flyvbjerg, Nils Bruzelius, Bert van Wee

Because of the prominent position of urban rail in reducing urban transport-related problems, such as congestion and air pollution, insights into the costs of possible new urban rail projects is very relevant for those involved with cost estimations, policy makers, cost-benefit analysts, and other target groups. Knowledge of the differences in costs per kilo

Aran Nayebi

A prefixed polynomial equation is an equation of the form $P(t_1,\ldots,t_n) = 0$, where $P$ is a polynomial whose variables $t_1,\ldots,t_n$ range over the natural numbers, preceded by quantifiers over some, or all, of its variables. Here, we consider exponential prefixed polynomial equations (EPPEs), where variables can also occur as exponents. We obtain a

Henry E. Kyburg

Surely we want solid foundations. What kind of castle can we build on sand? What is the point of devoting effort to balconies and minarets, if the foundation may be so weak as to allow the structure to collapse of its own weight? We want our foundations set on bedrock, designed to last for generations. Who would want an architect who cannot certify the sound

Ronald R. Yager

We describe a technique that can be used for the fusion of multiple sources of information as well as for the evaluation and selection of alternatives under multi-criteria. Three important properties contribute to the uniqueness of the technique introduced. The first is the ability to do all necessary operations and aggregations with information that is of a

Hong Xu

The local computation technique (Shafer et al. 1987, Shafer and Shenoy 1988, Shenoy and Shafer 1986) is used for propagating belief functions in so called a Markov Tree. In this paper, we describe an efficient implementation of belief function propagation on the basis of the local computation technique. The presented method avoids all the redundant computati

Michael S. K. M. Wong, Y. Y. Yao, P. Lingras

The compatibility of quantitative and qualitative representations of beliefs was studied extensively in probability theory. It is only recently that this important topic is considered in the context of belief functions. In this paper, the compatibility of various quantitative belief measures and qualitative belief structures is investigated. Four classes of

Nic Wilson

A very computationally-efficient Monte-Carlo algorithm for the calculation of Dempster-Shafer belief is described. If Bel is the combination using Dempster's Rule of belief functions Bel, ..., Bel,7, then, for subset b of the frame C), Bel(b) can be calculated in time linear in 1(31 and m (given that the weight of conflict is bounded). The algorithm can

Wilson X. Wen

The relationship between belief networks and relational databases is examined. Based on this analysis, a method to construct belief networks automatically from statistical relational data is proposed. A comparison between our method and other methods shows that our method has several advantages when generalization or prediction is deeded.

Deborah L. Thurston, Yun Qi Tian

In mechanical design, there is often unavoidable uncertainty in estimates of design performance. Evaluation of design alternatives requires consideration of the impact of this uncertainty. Expert heuristics embody assumptions regarding the designer's attitude towards risk and uncertainty that might be reasonable in most cases but inaccurate in others. We

Peter L. Spirtes

The presence of latent variables can greatly complicate inferences about causal relations between measured variables from statistical data. In many cases, the presence of latent variables makes it impossible to determine for two measured variables A and B, whether A causes B, B causes A, or there is some common cause. In this paper I present several theorems

Paul Snow

In probabilistic logic entailments, even moderate size problems can yield linear constraint systems with so many variables that exact methods are impractical. This difficulty can be remedied in many cases of interest by introducing a three valued logic (true, false, and "don't care"). The three-valued approach allows the construction of "comp

Philippe Smets

Survey of several forms of updating, with a practical illustrative example. We study several updating (conditioning) schemes that emerge naturally from a common scenarion to provide some insights into their meaning. Updating is a subtle operation and there is no single method, no single 'good' rule. The choice of the appropriate rule must always be g

Solomon Eyal Shimony

Irrelevance-based partial MAPs are useful constructs for domain-independent explanation using belief networks. We look at two definitions for such partial MAPs, and prove important properties that are useful in designing algorithms for computing them effectively. We make use of these properties in modifying our standard MAP best-first algorithm, so as to han

Prakash P. Shenoy

This paper proposes a new method for solving Bayesian decision problems. The method consists of representing a Bayesian decision problem as a valuation-based system and applying a fusion algorithm for solving it. The fusion algorithm is a hybrid of local computational methods for computation of marginals of joint probability distributions and the local compu

Ross D. Shachter

The graphoid axioms for conditional independence, originally described by Dawid [1979], are fundamental to probabilistic reasoning [Pearl, 19881. Such axioms provide a mechanism for manipulating conditional independence assertions without resorting to their numerical definition. This paper explores a representation for independence statements using multiple

Kerstin Schill, Ernst Poppel, Christoph Zetzsche

A control strategy for expert systems is presented which is based on Shafer's Belief theory and the combination rule of Dempster. In contrast to well known strategies it is not sequentially and hypotheses-driven, but parallel and self organizing, determined by the concept of information gain. The information gain, calculated as the maximal difference bet

Eugene Santos

In general, the best explanation for a given observation makes no promises on how good it is with respect to other alternative explanations. A major deficiency of message-passing schemes for belief revision in Bayesian networks is their inability to generate alternatives beyond the second best. In this paper, we present a general approach based on linear con

Sandra Sandri

In this article we present two ways of structuring bodies of evidence, which allow us to reduce the complexity of the operations usually performed in the framework of evidence theory. The first structure just partitions the focal elements in a body of evidence by their cardinality. With this structure we are able to reduce the complexity on the calculation o

Alessandro Saffiotti, Elisabeth Umkehrer

We present PULCinella and its use in comparing uncertainty theories. PULCinella is a general tool for Propagating Uncertainty based on the Local Computation technique of Shafer and Shenoy. It may be specialized to different uncertainty theories: at the moment, Pulcinella can propagate probabilities, belief functions, Boolean values, and possibilities. Moreov

Enrique H. Ruspini

This paper introduces conceptual relations that synthesize utilitarian and logical concepts, extending the logics of preference of Rescher. We define first, in the context of a possible worlds model, constraint-dependent measures that quantify the relative quality of alternative solutions of reasoning problems or the relative desirability of various policies

Bhavani Raskutti, Ingrid Zukerman

During interactions with human consultants, people are used to providing partial and/or inaccurate information, and still be understood and assisted. We attempt to emulate this capability of human consultants; in computer consultation systems. In this paper, we present a mechanism for handling uncertainty in plan recognition during task-oriented consultation

Anand S. Rao, Michael P. Georgeff

Deliberation plays an important role in the design of rational agents embedded in the real-world. In particular, deliberation leads to the formation of intentions, i.e., plans of action that the agent is committed to achieving. In this paper, we present a branching time possible-worlds model for representing and reasoning about, beliefs, goals, intentions, t

Arthur Ramer

Given a universe of discourse X-a domain of possible outcomes-an experiment may consist of selecting one of its elements, subject to the operation of chance, or of observing the elements, subject to imprecision. A priori uncertainty about the actual result of the experiment may be quantified, representing either the likelihood of the choice of :r_X or the de

Runping Qi, David L. Poole

For high level path planning, environments are usually modeled as distance graphs, and path planning problems are reduced to computing the shortest path in distance graphs. One major drawback of this modeling is the inability to model uncertainties, which are often encountered in practice. In this paper, a new tool, called U-yraph, is proposed for environmen

Gregory M. Provan

A new probabilistic network construction system, DYNASTY, is proposed for diagnostic reasoning given variables whose probabilities change over time. Diagnostic reasoning is formulated as a sequential stochastic process, and is modeled using influence diagrams. Given a set O of observations, DYNASTY creates an influence diagram in order to devise the best act

David L. Poole

This paper presents a simple framework for Horn clause abduction, with probabilities associated with hypotheses. It is shown how this representation can represent any probabilistic knowledge representable in a Bayesian belief network. The main contributions are in finding a relationship between logical and probabilistic notions of evidential reasoning. This

Gerhard Paass

The EM-algorithm is a general procedure to get maximum likelihood estimates if part of the observations on the variables of a network are missing. In this paper a stochastic version of the algorithm is adapted to probabilistic neural networks describing the associative dependency of variables. These networks have a probability distribution, which is a specia

Robert K. Paasch, Alice M. Agogino

We present a general architecture for the monitoring and diagnosis of large scale sensor-based systems with real time diagnostic constraints. This architecture is multileveled, combining a single monitoring level based on statistical methods with two model based diagnostic levels. At each level, sources of uncertainty are identified, and integrated methodolo

Raymond T. Ng, V. S. Subrahmanian

In this paper we study the uses and the semantics of non-monotonic negation in probabilistic deductive data bases. Based on the stable semantics for classical logic programming, we introduce the notion of stable formula, functions. We show that stable formula, functions are minimal fixpoints of operators associated with probabilistic deductive databases with

Keung-Chi Ng, Bruce Abramson

At last year?s Uncertainty in AI Conference, we reported the results of a sensitivity analysis study of Pathfinder. Our findings were quite unexpected-slight variations to Pathfinder?s parameters appeared to lead to substantial degradations in system performance. A careful look at our first analysis, together with the valuable feedback provided by the partic

Richard E. Neapolitan, James Kenevan

The belief network is a well-known graphical structure for representing independences in a joint probability distribution. The methods, which perform probabilistic inference in belief networks, often treat the conditional probabilities which are stored in the network as certain values. However, if one takes either a subjectivistic or a limiting frequency app

Bülent Murtezaoğlu, Henry E. Kyburg

Selecting the right reference class and the right interval when faced with conflicting candidates and no possibility of establishing subset style dominance has been a problem for Kyburg's Evidential Probability system. Various methods have been proposed by Loui and Kyburg to solve this problem in a way that is both intuitively appealing and justifiable w

Nathaniel G. Martin, James F. Allen

When a planner must decide whether it has enough evidence to make a decision based on probability, it faces the sample size problem. Current planners using probabilities need not deal with this problem because they do not generate their probabilities from observations. This paper presents an event based language in which the planner's probabilities are c

Tze-Yun Leong

This paper outlines a methodology for analyzing the representational support for knowledge-based decision-modeling in a broad domain. A relevant set of inference patterns and knowledge types are identified. By comparing the analysis results to existing representations, some insights are gained into a design approach for integrating categorical and uncertain

Paul E. Lehner, Azar Sadigh

A series of monte carlo studies were performed to compare the behavior of some alternative procedures for reasoning under uncertainty. The behavior of several Bayesian, linear model and default reasoning procedures were examined in the context of increasing levels of calibration error. The most interesting result is that Bayesian procedures tended to output

Kathryn Blackmond Laskey

Any probabilistic model of a problem is based on assumptions which, if violated, invalidate the model. Users of probability based decision aids need to be alerted when cases arise that are not covered by the aid's model. Diagnosis of model failure is also necessary to control dynamic model construction and revision. This paper presents a set of decision

Jerome Lang, Didier Dubois, Henri Prade

A semantics is given to possibilistic logic, a logic that handles weighted classical logic formulae, and where weights are interpreted as lower bounds on degrees of certainty or possibility, in the sense of Zadeh's possibility theory. The proposed semantics is based on fuzzy sets of interpretations. It is tolerant to partial inconsistency. Satisfiability

Rudolf Kruse, Detlef Nauck, Frank Klawonn

The concept of movable evidence masses that flow from supersets to subsets as specified by experts represents a suitable framework for reasoning under uncertainty. The mass flow is controlled by specialization matrices. New evidence is integrated into the frame of discernment by conditioning or revision (Dempster's rule of conditioning), for which specia

Robert Kennes

The categorial approach to evidential reasoning can be seen as a combination of the probability kinematics approach of Richard Jeffrey (1965) and the maximum (cross-) entropy inference approach of E. T. Jaynes (1957). As a consequence of that viewpoint, it is well known that category theory provides natural definitions for logical connectives. In particular,

Yen-Teh Hsia

We motivate and describe a theory of belief in this paper. This theory is developed with the following view of human belief in mind. Consider the belief that an event E will occur (or has occurred or is occurring). An agent either entertains this belief or does not entertain this belief (i.e., there is no "grade" in entertaining the belief). If the a

Daniel Hunter

Traditional approaches to non-monotonic reasoning fail to satisfy a number of plausible axioms for belief revision and suffer from conceptual difficulties as well. Recent work on ranked preferential models (RPMs) promises to overcome some of these difficulties. Here we show that RPMs are not adequate to handle iterated belief change. Specifically, we show th

Eric J. Horvitz, Geoffrey Rutledge

We discuss representing and reasoning with knowledge about the time-dependent utility of an agent's actions. Time-dependent utility plays a crucial role in the interaction between computation and action under bounded resources. We present a semantics for time-dependent utility and describe the use of time-dependent information in decision contexts. We il

Max Henrion

Since exact probabilistic inference is intractable in general for large multiply connected belief nets, approximate methods are required. A promising approach is to use heuristic search among hypotheses (instantiations of the network) to find the most probable ones, as in the TopN algorithm. Search is based on the relative probabilities of hypotheses which a

Adam J. Grove, Daphne Koller

In this paper, we consider one aspect of the problem of applying decision theory to the design of agents that learn how to make decisions under uncertainty. This aspect concerns how an agent can estimate probabilities for the possible states of the world, given that it only makes limited observations before committing to a decision. We show that the naive ap

B. Fringuelli, S. Marcugini, A. Milani, S. Rivoira

A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described. It supports a problem solver in situations affected by incomplete information and vague data, by allowing nonmonotonic inferences and the revision of previous conclusions when contradictions are detected.

John Fox, Paul J. Krause

The ability to reason under uncertainty and with incomplete information is a fundamental requirement of decision support technology. In this paper we argue that the concentration on theoretical techniques for the evaluation and selection of decision options has distracted attention from many of the wider issues in decision making. Although numerical methods

Bruce D'Ambrosio

We present a generalization of the local expression language used in the Symbolic Probabilistic Inference (SPI) approach to inference in belief nets [1l, [8]. The local expression language in SPI is the language in which the dependence of a node on its antecedents is described. The original language represented the dependence as a single monolithic condition

Gregory F. Cooper, Edward H. Herskovits

This paper presents a Bayesian method for constructing Bayesian belief networks from a database of cases. Potential applications include computer-assisted hypothesis testing, automated scientific discovery, and automated construction of probabilistic expert systems. Results are presented of a preliminary evaluation of an algorithm for constructing a belief n

Kuo-Chu Chang, Robert Fung

Recent research on the Symbolic Probabilistic Inference (SPI) algorithm[2] has focused attention on the importance of resolving general queries in Bayesian networks. SPI applies the concept of dependency-directed backward search to probabilistic inference, and is incremental with respect to both queries and observations. In response to this research we have

Kuo-Chu Chang, Robert Fung

Research on Symbolic Probabilistic Inference (SPI) [2, 3] has provided an algorithm for resolving general queries in Bayesian networks. SPI applies the concept of dependency directed backward search to probabilistic inference, and is incremental with respect to both queries and observations. Unlike traditional Bayesian network inferencing algorithms, SPI alg

Glenn Carroll, Eugene Charniak

Useless paths are a chronic problem for marker-passing techniques. We use a probabilistic analysis to justify a method for quickly identifying and rejecting useless paths. Using the same analysis, we identify key conditions and assumptions necessary for marker-passing to perform well.

Jose E. Cano, Serafin Moral, Juan F. Verdegay-Lopez

In this paper, we consider several types of information and methods of combination associated with incomplete probabilistic systems. We discriminate between 'a priori' and evidential information. The former one is a description of the whole population, the latest is a restriction based on observations for a particular case. Then, we propose different