21 papers · ranked by Valyu relevance
Fabio Cuzzolin
Belief functions are a powerful and popular framework for the mathematical characterisation of uncertainty, in particular in situations in which lack of data renders learning a probability distribution for the problem impractical. The first step in a reasoning chain based on belief functions is inference: how to learn…
Fabio Cuzzolin
Computer vision is an ever growing discipline whose ambitious goal is to equip machines with the intelligent visual skills humans and animals are provided by Nature, allowing them to interact effortlessly with complex, dynamic environments. Designing automated visual recognition and sensing systems typically involves…
Fabio Cuzzolin
In this paper, we discuss a potential agenda for future work in the theory of random sets and belief functions, touching upon a number of focal issues: the development of a fully-fledged theory of statistical reasoning with random sets, including the generalisation of logistic regression and of the classical laws of…
Wenyu Zhang, Zhenjiang Zhang, Leonhard M. Reindl
Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective…
Jing Zhu, Yupin Luo, Jianjun Zhou
In the target classification based on belief function theory, sensor reliability evaluation has two basic issues: reasonable dissimilarity measure among evidences, and adaptive combination of static and dynamic discounting. One solution to the two issues has been proposed here. Firstly, an improved dissimilarity…
Sabine Frittella, Ondrej Majer, Sajad Nazari
Belief and plausibility are weaker measures of uncertainty than that of probability. They are motivated by the situations when full probabilistic information is not available. However, information can also be contradictory. Therefore, the framework of classical logic is not necessarily the most adequate. Belnap—Dunn…
Timber Kerkvliet, Ronald Meester
We first show that there are practical situations in for instance forensic and gambling settings, in which applying classical probability theory, that is, based on the axioms of Kolmogorov, is problematic. We then introduce and discuss Shafer belief functions. Technically, Shafer belief functions generalize probability…
Michael S. K. M. Wong, Yiyu Yao, Pawan 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 consiJered in the context of belief functions. In this paper, the compatibility of various quantitative belief measures and qualitative belief…
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…
Jon Williamson
This paper presents a new argument for the Principle of Indifference. This argument can be thought of in two ways: as a pragmatic argument, justifying the principle as needing to hold if one is to minimise worst-case expected loss, or as an epistemic argument, justifying the principle as needing to hold in order to…
Lipeng Pan, Yong Deng
How to measure the uncertainty of the basic probability assignment (BPA) function is an open issue in Dempster-Shafer (D-S) theory. The main work of this paper is to propose a new belief entropy, which is mainly used to measure the uncertainty of BPA. The proposed belief entropy is based on Deng entropy and probability…
Shuang Ni, Yan Lei, Yongchuan Tang
Due to the nature of the Dempster combination rule, it may produce results contrary to intuition. Therefore, an improved method for conflict evidence fusion is proposed. In this paper, the belief entropy in D-S theory is used to measure the uncertainty in each evidence. First, the initial belief degree is constructed…
Hans-Ferdinand Angel
Beliefs differ from knowledge because they imply subjective meaning. Thus, one key issue for understanding believing is centered on the role of emotional valuations and subjective meaning-making. A series of publications emphasizes relevant aspects of this (Angel, ). (a) Like other cognitive processes, the process…
Emily Bruns, Immanuel Scholz, Georgia Koppe, Peter Kirsch + 1 more
Belief processing as well as self-referential processing have both been consistently associated with cortical midline structures. In addition, seminal neuroimaging papers have implicated cortical regions such as the vmPFC in general belief processing. However, the neural correlates of self-referential belief are yet to…
Martin Fungisai Gerchen, Samantha Ullrich, Mathis Lessau, Peter Kirsch
Belief was defined by William James as “the psychological process or function of cognizing reality”, and the recent philosophical literature has emphasized that there are two types of belief: categorical and graded. The relationship between these two belief types is complex, and it is often assumed that the degrees of…
Hans-Ferdinand Angel, Rüdiger J. Seitz
For the purpose of this communication it is postulated that violation of expectation means a disturbing event or conflict interfering with a previously established mental state that affords a firm belief or confident feeling. According to this hypothesis a violation of an expectation contradicts predictions and…
Martin Fungisai Gerchen, Samantha Ullrich, Mathis Lessau, Peter Kirsch
Belief was defined by William James as “the psychological process or function of cognizing reality”, and the recent philosophical literature has emphasized that there are two types of belief: categorical and graded. The relationship between these two belief types is complex, and it is often assumed that the degrees of…
Cheng Xue, Lily E. Kramer, Marlene R. Cohen
Natural decisions involve two seemingly separable processes: inferring the relevant task (task-belief) and performing the believed-relevant task. The assumed separability has led to the traditional practice of studying task-switching and perceptual decision-making individually. Here, we used a novel paradigm to…
Aryan Deshwal, Cory Simon, Janardhan Rao Doppa
Given a gas storage or separation task, we wish to search a library of nanoporous materials (NPMs) for the one with the optimal adsorption property. The high cost of measuring the adsorption property of an NPM, whether in the lab or a simulation, precludes exhaustive search. We explain, demonstrate, and advocate…
Ofer Perl, Anastasia Shuster, Matthew Heflin, Soojung Na + 5 more
Could non-pharmacological constructs, such as beliefs, impact brain activities in a dose-dependent manner as drugs do? While beliefs shape many aspects of our behavior and wellbeing, the precise mapping between subjective beliefs and neural substrates remains elusive. Here, nicotine-addicted humans were instructed to…
Charley M. Wu, Eric Schulz, Samuel J. Gershman
From social networks to public transportation, graph structures are a ubiquitous feature of life. Yet little is known about how humans learn functions on graphs, where relationships are defined by the connectivity structure. We adapt a Bayesian framework for function learning to graph structures, and propose that…