36,425 research outputs found
Perspectives for proof unwinding by programming languages techniques
In this chapter, we propose some future directions of work, potentially
beneficial to Mathematics and its foundations, based on the recent import of
methodology from the theory of programming languages into proof theory. This
scientific essay, written for the audience of proof theorists as well as the
working mathematician, is not a survey of the field, but rather a personal view
of the author who hopes that it may inspire future and fellow researchers
A Fuzzy Logic Programming Environment for Managing Similarity and Truth Degrees
FASILL (acronym of "Fuzzy Aggregators and Similarity Into a Logic Language")
is a fuzzy logic programming language with implicit/explicit truth degree
annotations, a great variety of connectives and unification by similarity.
FASILL integrates and extends features coming from MALP (Multi-Adjoint Logic
Programming, a fuzzy logic language with explicitly annotated rules) and
Bousi~Prolog (which uses a weak unification algorithm and is well suited for
flexible query answering). Hence, it properly manages similarity and truth
degrees in a single framework combining the expressive benefits of both
languages. This paper presents the main features and implementations details of
FASILL. Along the paper we describe its syntax and operational semantics and we
give clues of the implementation of the lattice module and the similarity
module, two of the main building blocks of the new programming environment
which enriches the FLOPER system developed in our research group.Comment: In Proceedings PROLE 2014, arXiv:1501.0169
A Declarative Semantics for CLP with Qualification and Proximity
Uncertainty in Logic Programming has been investigated during the last
decades, dealing with various extensions of the classical LP paradigm and
different applications. Existing proposals rely on different approaches, such
as clause annotations based on uncertain truth values, qualification values as
a generalization of uncertain truth values, and unification based on proximity
relations. On the other hand, the CLP scheme has established itself as a
powerful extension of LP that supports efficient computation over specialized
domains while keeping a clean declarative semantics. In this paper we propose a
new scheme SQCLP designed as an extension of CLP that supports qualification
values and proximity relations. We show that several previous proposals can be
viewed as particular cases of the new scheme, obtained by partial
instantiation. We present a declarative semantics for SQCLP that is based on
observables, providing fixpoint and proof-theoretical characterizations of
least program models as well as an implementation-independent notion of goal
solutions.Comment: 17 pages, 26th Int'l. Conference on Logic Programming (ICLP'10
MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging -- design, implementation and application on the example of DCE-MRI
Many medical imaging techniques utilize fitting approaches for quantitative
parameter estimation and analysis. Common examples are pharmacokinetic modeling
in DCE MRI/CT, ADC calculations and IVIM modeling in diffusion-weighted MRI and
Z-spectra analysis in chemical exchange saturation transfer MRI. Most available
software tools are limited to a special purpose and do not allow for own
developments and extensions. Furthermore, they are mostly designed as
stand-alone solutions using external frameworks and thus cannot be easily
incorporated natively in the analysis workflow. We present a framework for
medical image fitting tasks that is included in MITK, following a rigorous
open-source, well-integrated and operating system independent policy. Software
engineering-wise, the local models, the fitting infrastructure and the results
representation are abstracted and thus can be easily adapted to any model
fitting task on image data, independent of image modality or model. Several
ready-to-use libraries for model fitting and use-cases, including fit
evaluation and visualization, were implemented. Their embedding into MITK
allows for easy data loading, pre- and post-processing and thus a natural
inclusion of model fitting into an overarching workflow. As an example, we
present a comprehensive set of plug-ins for the analysis of DCE MRI data, which
we validated on existing and novel digital phantoms, yielding competitive
deviations between fit and ground truth. Providing a very flexible environment,
our software mainly addresses developers of medical imaging software that
includes model fitting algorithms and tools. Additionally, the framework is of
high interest to users in the domain of perfusion MRI, as it offers
feature-rich, freely available, validated tools to perform pharmacokinetic
analysis on DCE MRI data, with both interactive and automatized batch
processing workflows.Comment: 31 pages, 11 figures URL: http://mitk.org/wiki/MITK-ModelFi
Towards a Systematic Account of Different Semantics for Logic Programs
In [Hitzler and Wendt 2002, 2005], a new methodology has been proposed which
allows to derive uniform characterizations of different declarative semantics
for logic programs with negation. One result from this work is that the
well-founded semantics can formally be understood as a stratified version of
the Fitting (or Kripke-Kleene) semantics. The constructions leading to this
result, however, show a certain asymmetry which is not readily understood. We
will study this situation here with the result that we will obtain a coherent
picture of relations between different semantics for normal logic programs.Comment: 20 page
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