Propositional Abduction via Only-Knowing: A Non-Monotonic Approach

Conditional Objects as Nonmonotonic Consequence Relations

This paper investigates the relationship between conditional objects obtained as a qualitative counterpart to conditional probabilities, and nonmonotonic reasoning. Viewed as an inference rule expressing a contextual belief, the conditional object is shown to possess all properties of a well-behaved nonmonotonic consequence relation when a suitable choice of connectives and deduction operation is made. Using previous results from Adams' conditional probabilistic logic, a logic of conditional objects is proposed. Its axioms and inference rules are those of preferential reasoning logic of Lehmann and colleagues. But the semantics relies on a three-valued truth valuation first suggested by De Finetti. It is more elementary and intuitive than the preferential semantics of Lehmann and colleagues and does not require probabilistic semantics. The analysis of a notion of consistency of a set of conditional objects is studied in the light of such a three-valued semantics and higher level counterparts of deduction theorem, modus ponens, resolution and refutation are suggested. Limitations of this logic are discussed. >

A NYONE GIVING A COURSE in general biology faces the discouraging prospect of teaching Mendelian genetics problems competently. This latter task is part of the larger problem of instructing students in the use of a scientific approach to problem solving and biological investigation in general. We at Project SABLE are interested in increasing students' abilities to formulate and test hypotheses and to analyze experimental results. We have been producing instructional materials for use in many types of colleges and universities that instruct students in some basic skills needed to become involved in scientific investigations. This article is a description of a new trial set of materials in Mendelian genetics, which consists of a written tutorial teaching the basic concepts of Mendelian genetics, a computer-simulated providing practice in solving problems, and an independent investigation in genetics giving students the chance to apply their knowledge in a real setting. During an earlier phase of the project, we emphasized the as the best place for students to acquire scientific problem solving skills because we believed concrete manipulation is an important ingredient in acquiring these skills. Our preliminary hypothesis was that if we produced materials that ensured that students could make observations, master the biological concepts, and use scientific equipment and techniques, then they would be prepared to solve interesting problems of their own choosing in the laboratory. We designed a series of selfinstructional tutorials (using some of the elements of programmed instruction) and other materials to meet these criteria. As a result we were successful in establishing an open laboratory setting where students learned in an independent, self-paced manner how to make specific observations and use scientific techniques and procedures (Von Blum 1975). Interviews with students and close analysis of reports of students' independent field investigations, however, showed that, even though students could successfully handle techniques and make observations, they could not develop, identify or test hypotheses nor adequately interpret data. Therefore, we had to revise our hypothesis: before students are ready to undertake independent investigations they need specific instruction in hypothesis formulation, testing, and data analysis. This must be combined with an understanding of basic biological concepts, skill in making observations, and the ability to perform manipulations. We wanted students to recognize the way in which good scientists work, so that they could follow the process themselves when they are faced with a new problem. Consequently, we designed our materials to demonstrate how scientists go about constructing explanations of their observations and using these explanations in predicting further observations. Also, we wanted to provide practice in carrying out this process in a real biological context. After testing and discarding several alternatives, we decided to use a written text to present biological concepts, combined with a computer simulated to provide practice in applying these concepts to solving problems, followed by an independent investigation in the (fig.1). The first materials testing this approach deal with Mendelian genetics. The tutorial, Heredity: Developing an Explanation, presents the major concepts

Abductive inference derives explanations for encountered anomalies and thus embodies a natural approach for diagnostic reasoning. Yet its computational complexity, which is inherent to the expressiveness of the underlying theory, remains a disadvantage. Even when restricting the representation to Horn formulae the problem is NP-complete. Hence, finding procedures that can efficiently solve abductive diagnosis problems is of particular interest from a research as well as practical point of view. In this paper, we aim at providing guidance on choosing an algorithm or tool when confronted with the issue of computing explanations in propositional logic-based abduction. Our focus lies on Horn representations, which provide a suitable language to describe most diagnostic scenarios. We illustrate abduction via two contrasting problem formulations: direct proof methods and conflict-driven techniques. While the former is based on determining logical consequences, the later searches for suitable refutations involving possible causes. To reveal runtime performance trends we conducted a case study, in which we compared publicly available general purpose tools, established Horn reasoning engines, as well as new variations of known methods as a means for abduction.

Conditioning is very often considered in connection with probability; both look strongly entwined in the usual notion of conditional probability. This connection has created a gap between probability theory and logic: while the former seems to ignore material implication when representing conditional knowledge, the latter has no genuine tool to account for conditioning. This chapter is an investigation of the relationship between conditional objects of the form q\p, obtained as a qualitative counterpart to conditional probabilities P(g|p), and non-monotonic reasoning. Viewed as an inference rule, the conditional object possesses properties of a well-behaved non-monotonic consequence relation. The basic tool is the 3-valued semantics of conditional objects that differs from the preferential semantics of Lehmann and colleagues and does not require probabilistic semantics. Semantic entailment of a conditional object q\p from a knowledge base made of conditional objects is equivalent to the inference of the conditional assertion p |˜ q in Lehmann’s system P.

Dynamic light scattering (DLS) has become a primary nanoparticle characterization technique with applications from material characterization to biological and environmental detection. With the expansion in DLS use from homogeneous spheres to more complicated nanostructures comes a decrease in accuracy. Much research has been performed to develop different diffusion models that account for the vastly different structures, but little attention has been given to the effect on the light scattering properties in relation to DLS. In this work, small (core size < 5 nm) core-shell nanoparticles were used as a case study to measure the capping thickness of a layer of dodecanethiol (DDT) on Au and ZnO nanoparticles by DLS. We find that the DDT shell has very little effect on the scattering properties of the inorganic core and, hence, can be ignored to a first approximation. However, this results in conventional DLS analysis overestimating the hydrodynamic size in the volume- and number-weighted distributions. With the introduction of a simple correction formula that more accurately yields hydrodynamic size distributions, a more precise determination of the molecular shell thickness is obtained. With this correction, the measured thickness of the DDT shell was found to be 7.3 ± 0.3 Å, much less than the extended chain length of 16 Å. This organic layer thickness suggests that, on small nanoparticles, the DDT monolayer adopts a compact disordered structure rather than an open ordered structure on both ZnO and Au nanoparticle surfaces. These observations are in agreement with published molecular dynamics results.

This chapter reviews Fodor’s contribution to the epic Chomsky-Piaget Royaumont debate. The issue that was under discussion was a familiar one, namely, what psychological processes underlie concept learning. Piaget thought concept learning involved the formation and confirmation of hypotheses that a learner generates through the construction and organization of stimuli gathered from the environment, and modifying them when they proved to be inconsistent. However, Fodor pointed out a fundamental flaw in this theory: it is silent about the origin of the concepts used in generating the hypotheses. Fodor argued that in order for these hypotheses to be tested, let alone generated, they needed to have been readily available to the learner, suggesting that all primitive concepts are innate, and that concept acquisition relies on the process of triggering these concepts that are innately available to the learner, and not through construction by means of progressive guesses and trial-and-error.

High entropy alloys (HEAs) are single phase crystals that consist of random solid solutions of multiple elements in approximately equal proportions. This class of novel materials have exhibited superb mechanical properties, such as high strength combined with other desired features. The strength of crystalline materials is associated with the motion of dislocations. In this paper, we derive a stochastic continuum model based on the Peierls--Nabarro framework for interlayer dislocations in a bilayer HEA from an atomistic model that incorporates the atomic level randomness. We use asymptotic analysis and limit theorem in the convergence from the atomistic model to the continuum model. The total energy in the continuum model consists of a stochastic elastic energy in the two layers, and a stochastic misfit energy that accounts for the interlayer nonlinear interaction. The obtained continuum model can be considered as a stochastic generalization of the classical, deterministic Peierls--Nabarro model for the dislocation core and related properties. This derivation also validates the stochastic model adopted by Zhang et al. [Acta Mater., 166 (2019), pp. 424--434].

A number of conceptual difficulties were identified in a comprehensive diagnostic study of learning and teaching in high school biology laboratories in Israel. Most prominent among these were those related to understanding and applying basic inquiry skills such as problem identification, hypothesis formulation, and designing experiments. In order to improve the command of these skills by high school students an original module entitled 'Basic concepts of scientific research' has been developed. The module includes invitations to inquiry and a variety of exercises which lead the students gradually from simple to more complex, and some highly sophisticated, problem-solving experiences. The concepts of scientific research are developed in their historical context so that the student acquires a realistic image of scientific research as well as working ability in applying inquiry skills to the solving of novel problems. Students who used the module demonstrated substantial gains in understanding concepts and a...

This paper summarizes and formally presents methods in use during the past 25 years at Bell Telephone Laboratories for the design of high-quality inductors. The quality factor, Q, of annular core inductors can be maximized by adapting core dimensions, winding details, etc., to the specific properties of the magnetic core. Commercial core materials include 2–81 Mo-permalloy powder and carbonyl iron powder. Analysis of the relationships of dimensions and magnetic properties is given first in terms of the bare fundamentals of dc copper resistance and magnetic core losses. The paper then derives expressions for, and considers the effects of, additional losses due to the windings, such as eddy currents in the copper, dielectric losses and the contribution to effective resistance due to parallel distributed capacitance. Finally, a graph is supplied showing the maximum Q and optimum frequency for many commercial sizes of annular cores.

Certain extensions of Nelson's constructive logic N with strong negation have recently become important in arti.cial intelligence and nonmonotonic reasoning, since they yield a logical foundation for answer set programming (ASP). In this paper we look at some extensions of Nelson's .rst-order logic as a basis for de.ning nonmonotonic inference relations that underlie the answer set programming semantics. The extensions we consider are those based on 2-element, here-and-there Kripke frames. In particular, we prove completeness for .rst-order here-and-there logics, and their minimal strong negation extensions, for both constant and varying domains. We choose the constant domain version, which we denote by QNc5, as a basis for de.ning a .rst-order nonmonotonic extension called equilibrium logic. We establish several metatheoretic properties of QNc5, including Skolem forms and Herbrand theorems and Interpolation, and show that the .rst-oder version of equilibrium logic can be used as a foundation for answer set inference.

The information-processing (IP) approach to perception and cognition arose as a reaction to behaviourism. This reaction mainly concerned the nature of explanation in scientific psychology. The "standard" account of behaviour, phrased in strictly external terms, was replaced by a "realist" account, phrased in terms of internal entities and processes. An analysis of the theoretical language used in IP psychology shows an undisciplined state of affairs. A great number of languages is simultaneously in use; no level of analysis is unambiguously referred to; and basic concepts such as information and processing remain largely undefined. Nevertheless, over the past 25 years the IP approach has developed into a disciplined and sophisticated experimental science. A look at actual practice hints at the basic reason for its success. The approach is not so much concerned with absolute or intrinsic properties of the human information processor, but with what can be called its relative or differential properties. A further analysis of this feature of the IP approach in terms of the formal language of a logical system makes explicit the basis of its success. The IP approach can be regarded as developing an empirical difference calculus on an unspecified class of objects, phrased in terms of a simulated "theory-neutral" observation language, and with operators that are structurally analogous to logical operators. This reinterpretation of what the IP approach is about brings a number of advantages. It strengthens its position as an independent science, clarifies its relation with other approaches within psychology and other sciences within the cognitive science group, and makes it independent of philosophical subtleties.

The objectives of the work presented in this paper, were development and testing of techniques for measurement of relative permeability of gas condensate fluid systems by pressure depletion and dynamic displacement of retrograde liquid at different interfacial tensions. The experiments employed a six component model system and were based on measurements of basic core and fluid properties, preliminary compositional simulation of fluid behaviour, slim tube tests and displacement in long Berea core1-4. The measurements showed that the relative permeability curves to the gas condensate model system in a depletion process, are similar to curves of ordinary gas/oil systems, and that gravitational segregation of condensate is pronounced even at liquid saturations below the critical saturation for flow. During dynamic displacement of retrograde liquid by gas in equilibrium with the liquid, the relative permeability to gas and liquid showed strong dependence on interfacial tension between the two phases.

New laboratory measurements of sediment properties in cores from the Bering Sea, North Sea, Mediterranean Sea, equatorial Pacific, and other areas, have been combined with older measurements and the results, with statistical analyses, are presented (for various sediment types in three general environments) in tables, diagrams, and regression equations. The measured properties are sound velocity, density, porosity, grain density, and grain size; computed properties are velocity ratios (sediment velocity/water velocity) and impedance. Mineral-grain microstructures of sediments are critical in determining density, porosity, and sound velocity; compressibility of pore water is the critical factor in determining sound velocity. New regression equations are provided for important empirical relationships between properties. Corrections of laboratory values to sea-floor values are discussed. It is concluded that sound velocity and density are about the same for a given sediment type in the same environment in any ocean if porosity is about the same. Given the mean size of mineral grains, or average porosity, of a sediment, the average sound velocity can be predicted within 1% or 2% in most environments. Comparisons with recent in situ measurements validate the laboratory measurements.

Multivariate analysis seeks to describe the relationship between an arbitrary number of variables. To explore highdimensional data sets, projections are often used for data visualisation to aid discovering structure or patterns that lead to the formation of statistical hypothesis. The basic concept necessitates a systematic search for lower-dimensional representations of the data that might show interesting structure(s). Motivated by the recent research on the Image Grand Tour (IGT), which can be adapted to view guided projections by using objective indexes that are capable of revealing latent structures of the data, this paper presents a signal processing perspective on constructing such indexes under the unifying exploratory frameworks of Independent Component Analysis (ICA) and Projection Pursuit (PP). Our investigation begins with an overview of dimension reduction techniques by means of orthogonal transforms, including the classical procedure of Principal Component Analysis (PCA), and extends to an application of the more powerful techniques of ICA in the context of our recent work on non-destructive testing technology by element specific x-ray imaging.