9,584 research outputs found
Evidence and plausibility in neighborhood structures
The intuitive notion of evidence has both semantic and syntactic features. In
this paper, we develop an {\em evidence logic} for epistemic agents faced with
possibly contradictory evidence from different sources. The logic is based on a
neighborhood semantics, where a neighborhood indicates that the agent has
reason to believe that the true state of the world lies in . Further notions
of relative plausibility between worlds and beliefs based on the latter
ordering are then defined in terms of this evidence structure, yielding our
intended models for evidence-based beliefs. In addition, we also consider a
second more general flavor, where belief and plausibility are modeled using
additional primitive relations, and we prove a representation theorem showing
that each such general model is a -morphic image of an intended one. This
semantics invites a number of natural special cases, depending on how uniform
we make the evidence sets, and how coherent their total structure. We give a
structural study of the resulting `uniform' and `flat' models. Our main result
are sound and complete axiomatizations for the logics of all four major model
classes with respect to the modal language of evidence, belief and safe belief.
We conclude with an outlook toward logics for the dynamics of changing
evidence, and the resulting language extensions and connections with logics of
plausibility change
High-resolution optical and SAR image fusion for building database updating
This paper addresses the issue of cartographic database (DB) creation or updating using high-resolution synthetic aperture radar and optical images. In cartographic applications, objects of interest are mainly buildings and roads. This paper proposes a processing chain to create or update building DBs. The approach is composed of two steps. First, if a DB is available, the presence of each DB object is checked in the images. Then, we verify if objects coming from an image segmentation should be included in the DB. To do those two steps, relevant features are extracted from images in the neighborhood of the considered object. The object removal/inclusion in the DB is based on a score obtained by the fusion of features in the framework of DempsterâShafer evidence theory
Argument-based Belief in Topological Structures
This paper combines two studies: a topological semantics for epistemic
notions and abstract argumentation theory. In our combined setting, we use a
topological semantics to represent the structure of an agent's collection of
evidence, and we use argumentation theory to single out the relevant sets of
evidence through which a notion of beliefs grounded on arguments is defined. We
discuss the formal properties of this newly defined notion, providing also a
formal language with a matching modality together with a sound and complete
axiom system for it. Despite the fact that our agent can combine her evidence
in a 'rational' way (captured via the topological structure), argument-based
beliefs are not closed under conjunction. This illustrates the difference
between an agent's reasoning abilities (i.e. the way she is able to combine her
available evidence) and the closure properties of her beliefs. We use this
point to argue for why the failure of closure under conjunction of belief
should not bear the burden of the failure of rationality.Comment: In Proceedings TARK 2017, arXiv:1707.0825
Evidential Label Propagation Algorithm for Graphs
Community detection has attracted considerable attention crossing many areas
as it can be used for discovering the structure and features of complex
networks. With the increasing size of social networks in real world, community
detection approaches should be fast and accurate. The Label Propagation
Algorithm (LPA) is known to be one of the near-linear solutions and benefits of
easy implementation, thus it forms a good basis for efficient community
detection methods. In this paper, we extend the update rule and propagation
criterion of LPA in the framework of belief functions. A new community
detection approach, called Evidential Label Propagation (ELP), is proposed as
an enhanced version of conventional LPA. The node influence is first defined to
guide the propagation process. The plausibility is used to determine the domain
label of each node. The update order of nodes is discussed to improve the
robustness of the method. ELP algorithm will converge after the domain labels
of all the nodes become unchanged. The mass assignments are calculated finally
as memberships of nodes. The overlapping nodes and outliers can be detected
simultaneously through the proposed method. The experimental results
demonstrate the effectiveness of ELP.Comment: 19th International Conference on Information Fusion, Jul 2016,
Heidelber, Franc
From canopies to conversations: the continuing significance of "plausibility structures"
Among the most generative â but oft-misunderstood â ideas found in Peter Bergerâs magisterial work is the idea that religions depend on plausibility structures. This assertion points toward the social worlds in which religious ideas and practices take on meaning. The most powerful situation for a religious system is one in which the entire taken-for-granted world falls under a sacred canopy. The fracturing of that canopy was at the heart of the theory of secularization Berger put forward. This chapter argues that no such comprehensive canopy is necessary for sustaining religious systems. We should instead examine the social interaction at the base of the plausibility structures, namely the conversations in which a sacred view of the world is sustained. Likewise, we must situate those conversations in the practical, embodied, and material experiences described as âlived religion.
Approximated Computation of Belief Functions for Robust Design Optimization
This paper presents some ideas to reduce the computational cost of
evidence-based robust design optimization. Evidence Theory crystallizes both
the aleatory and epistemic uncertainties in the design parameters, providing
two quantitative measures, Belief and Plausibility, of the credibility of the
computed value of the design budgets. The paper proposes some techniques to
compute an approximation of Belief and Plausibility at a cost that is a
fraction of the one required for an accurate calculation of the two values.
Some simple test cases will show how the proposed techniques scale with the
dimension of the problem. Finally a simple example of spacecraft system design
is presented.Comment: AIAA-2012-1932 14th AIAA Non-Deterministic Approaches Conference.
23-26 April 2012 Sheraton Waikiki, Honolulu, Hawai
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