22,067 research outputs found
Belief Revision in Science: Informational Economy and Paraconsistency
In the present paper, our objective is to examine the application of belief revision models to scientific rationality. We begin by considering the standard model AGM, and along the way a number of problems surface that make it seem inadequate for this specific application. After considering three different heuristics of informational economy that seem fit for science, we consider some possible adaptations for it and argue informally that, overall, some paraconsistent models seem to better satisfy these principles, following Testa (2015). These models have been worked out in formal detail by Testa, Cogniglio, & Ribeiro (2015, 2017)
A Rational and Efficient Algorithm for View Revision in Databases
The dynamics of belief and knowledge is one of the major components of any
autonomous system that should be able to incorporate new pieces of information.
In this paper, we argue that to apply rationality result of belief dynamics
theory to various practical problems, it should be generalized in two respects:
first of all, it should allow a certain part of belief to be declared as
immutable; and second, the belief state need not be deductively closed. Such a
generalization of belief dynamics, referred to as base dynamics, is presented,
along with the concept of a generalized revision algorithm for Horn knowledge
bases. We show that Horn knowledge base dynamics has interesting connection
with kernel change and abduction. Finally, we also show that both variants are
rational in the sense that they satisfy certain rationality postulates stemming
from philosophical works on belief dynamics
Gender differences in survival among adult patients starting antiretroviral therapy in South Africa: a multicentre cohort study.
Increased mortality among men on antiretroviral therapy (ART) has been documented but remains poorly understood. We examined the magnitude of and risk factors for gender differences in mortality on ART
Marrying out of the lower classes in nineteenth-century Belgium
In this article we address one of the most prominent questions in historical sociology: did economic modernization in the nineteenth century lead to societal openness? In an attempt to answer the question we examine the chances for lower-class grooms of marrying upwardly in five Belgian cities (Aalst, Leuven, Ghent, Verviers, and Liège). Our findings show that there is no support for a meritocracy hypothesis. The chances of marrying out of the lower classes did not increase, in either absolute or relative terms. Social closure strategies were efficient in that they apparently prevented upward marital mobility for lower-class grooms. As these findings were measured in a highly advanced economic context, this study casts strong doubts on the relationship between economic modernization, meritocracy, and marital mobility, at least for the nineteenth century
Evaluation of mineralogy per geological layers by Approximate Bayesian Computation
We propose a new methodology to perform mineralogic inversion from wellbore
logs based on a Bayesian linear regression model. Our method essentially relies
on three steps. The first step makes use of Approximate Bayesian Computation
(ABC) and selects from the Bayesian generator a set of candidates-volumes
corresponding closely to the wellbore data responses. The second step gathers
these candidates through a density-based clustering algorithm. A mineral
scenario is assigned to each cluster through direct mineralogical inversion,
and we provide a confidence estimate for each lithological hypothesis. The
advantage of this approach is to explore all possible mineralogy hypotheses
that match the wellbore data. This pipeline is tested on both synthetic and
real datasets
Causality and the semantics of provenance
Provenance, or information about the sources, derivation, custody or history
of data, has been studied recently in a number of contexts, including
databases, scientific workflows and the Semantic Web. Many provenance
mechanisms have been developed, motivated by informal notions such as
influence, dependence, explanation and causality. However, there has been
little study of whether these mechanisms formally satisfy appropriate policies
or even how to formalize relevant motivating concepts such as causality. We
contend that mathematical models of these concepts are needed to justify and
compare provenance techniques. In this paper we review a theory of causality
based on structural models that has been developed in artificial intelligence,
and describe work in progress on a causal semantics for provenance graphs.Comment: Workshop submissio
Case Base Mining for Adaptation Knowledge Acquisition
In case-based reasoning, the adaptation of a source case in order to solve
the target problem is at the same time crucial and difficult to implement. The
reason for this difficulty is that, in general, adaptation strongly depends on
domain-dependent knowledge. This fact motivates research on adaptation
knowledge acquisition (AKA). This paper presents an approach to AKA based on
the principles and techniques of knowledge discovery from databases and
data-mining. It is implemented in CABAMAKA, a system that explores the
variations within the case base to elicit adaptation knowledge. This system has
been successfully tested in an application of case-based reasoning to decision
support in the domain of breast cancer treatment
Analysis reuse exploiting taxonomical information and belief assignment in industrial problem solving
To take into account the experience feedback on solving complex problems in business is deemed as a way to improve the quality of products and processes. Only a few academic works, however, are concerned with the representation and the instrumentation of experience feedback systems. We propose, in this paper, a model of experiences and mechanisms to use these experiences. More specifically, we wish to encourage the reuse of already performed expert analysis to propose a priori analysis in the solving of a new problem. The proposal is based on a representation in the context of the experience of using a conceptual marker and an explicit representation of the analysis incorporating expert opinions and the fusion of these opinions. The experience feedback models and inference mechanisms are integrated in a commercial support tool for problem solving methodologies. The results obtained to this point have already led to the definition of the role of ‘‘Rex Manager’’ with principles of sustainable management for continuous improvement of industrial processes in companies
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