Belief Model Research Articles

Privacy-Preserving and Diversity-Aware Trust-based Team Formation in Online Social Networks

As online social networks (OSNs) become more prevalent, a new paradigm for problem-solving through crowd-sourcing has emerged. By leveraging the OSN platforms, users can post a problem to be solved and then form a team to collaborate and solve the problem. A common concern in OSNs is how to form effective collaborative teams, as various tasks are completed through online collaborative networks. A team’s diversity in expertise has received high attention to producing high team performance in developing team formation (TF) algorithms. However, the effect of team diversity on performance under different types of tasks has not been extensively studied. Another important issue is how to balance the need to preserve individuals’ privacy with the need to maximize performance through active collaboration, as these two goals may conflict with each other. This research has not been actively studied in the literature. In this work, we develop a team formation (TF) algorithm in the context of OSNs that can maximize team performance and preserve team members’ privacy under different types of tasks. Our proposed PR iv A cy- D iversity- A ware T eam F ormation framework, called PRADA-TF , is based on trust relationships between users in OSNs where trust is measured based on a user’s expertise and privacy preference levels. The PRADA-TF algorithm considers the team members’ domain expertise, privacy preferences, and the team’s expertise diversity in the process of team formation. Our approach employs game-theoretic principles Mechanism Design to motivate self-interested individuals within a team formation context, positioning the mechanism designer as the pivotal team leader responsible for assembling the team. We use two real-world datasets (i.e., Netscience and IMDb) to generate different semi-synthetic datasets for constructing trust networks using a belief model (i.e., Subjective Logic) and identifying trustworthy users as candidate team members. We evaluate the effectiveness of our proposed PRADA-TF scheme in four variants against three baseline methods in the literature. Our analysis focuses on three performance metrics for studying OSNs: social welfare, privacy loss, and team diversity.

Free entropy minimizing persuasion in a predictor–corrector dynamic

Persuasion is the process of changing an agent’s belief distribution from a given (or estimated) prior to a desired posterior. A common assumption in the acceptance of information or misinformation as fact is that the (mis)information must be consistent with or familiar to the individual who accepts it. We model the process as a control problem in which the state is given by a (time-varying) belief distribution following a predictor–corrector dynamic. Persuasion is modeled as the corrector control signal with the performance index defined using the Fisher–Rao information metric, reflecting a fundamental cost associated to altering the agent’s belief distribution. To compensate for the fact that information production arises naturally from the predictor dynamic (i.e., expected beliefs change) we modify the Fisher–Rao metric to account just for information generated by the control signal. The resulting optimal control problem produces non-geodesic paths through distribution space that are compared to the geodesic paths found using the standard free entropy minimizing Fisher metric in several example belief models: a Kalman Filter, a Boltzmann distribution and a joint Kalman/Boltzmann belief system.

Causal mapping for evaluators

Evaluators are interested in capturing how things causally influence one another. They are also interested in capturing how stakeholders think things causally influence one another. Causal mapping – the collection, coding and visualisation of interconnected causal claims – has been used widely for several decades across many disciplines for this purpose. It makes the provenance or source of such claims explicit and provides tools for gathering and dealing with this kind of data and for managing its Janus-like double-life: on the one hand, providing information about what people believe causes what, and on the other hand, preparing this information for possible evaluative judgements about what causes what. Specific reference to causal mapping in the evaluation literature is sparse, which we aim to redress here. In particular, the authors address the Janus dilemma by suggesting that causal maps can be understood neither as models of beliefs about causal pathways nor as models of causal pathways per se but as repositories of evidence for those pathways.

Attack-Resistant, Energy-Adaptive Monitoring for Smart Farms: Uncertainty-Aware Deep Reinforcement Learning Approach

This work proposes an energy-adaptive monitoring system for a smart farm using solar sensors attached to cows. The proposed system aims to achieve a high monitoring quality in the smart farm under fluctuating energy and cyber attacks disrupting the collection of sensed data from solar sensors, such as protocol non-compliance, false data injection, denial-of-service, and state manipulation. We adopt Subjective Logic, a belief model, to consider multidimensional uncertainty in sensed data. We employ Deep Reinforcement Learning (DRL) for agents on gateways to collect high-quality sensed data from the solar sensors. The DRL agents aim to collect high-quality sensed data with low uncertainty and high freshness under fluctuating energy levels in solar sensors. We analyze the performance of the proposed energy-adaptive smart farm system in accumulated reward, monitoring error rate, and system overload. We conduct a comparative performance analysis of the uncertainty-aware DRL algorithms against their counterparts in choosing the number of sensed data to be updated to collect high-quality sensed data to achieve high resilience against attacks. Our results prove that Multi-Agent Proximal Policy Optimization (MAPPO) using the uncertainty maximization technique outperforms other counterparts, showing about 4% lower monitoring error rate and the system overload.

On the progression of belief

Based on weighted possible-world semantics, Belle and Lakemeyer recently proposed the logic DS, a probabilistic extension of a modal variant of the situation calculus with a model of belief. The logic has many desirable properties like full introspection and it is able to precisely capture the beliefs of a probabilistic knowledge base in terms of the notion of only-believing. While the proposal is intuitively appealing, it is unclear how to do planning with such logic. The reason behind this is that the logic lacks projection reasoning mechanisms and projection lies at the heart of planning. Projection reasoning, in general, is to decide what holds after actions. Two main solutions to projection exist: regression and progression. Roughly, regression reduces a query about the future to a query about the initial state while progression, on the other hand, changes the initial state according to the effects of actions and then checks whether the formula holds in the updated state. In this paper, we study projection by progression in the logic DS. It is known that the progression of a categorical knowledge base wrt a noise-free action corresponds to what is only-known after that action. We show how to progress a type of probabilistic knowledge base wrt noisy actions by the notion of only-believing after actions. Our notion of only-believing is closely related to Lin and Reiter's notion of progression.

Bir İlim Alanı Olarak Dinler Tarihi Tevhid İnancı Bağlamında Nasıl Okunabilir?

Dinler Tarihi ilmi, “ilk insan/peygamber Hz. Âdem’den günümüze uzanan süreçde yaşanmış bütün dinleri, dinî hareketleri, mezhep ve tarikatları; tarihleri, doktrinleri, kutsal kitap metinleri, âyinleri, mabedleri, ruhbanları, hiyerarşisi, kurbanları, cemaatleri ile birlikte objektif metodlarla inceleyen bir din ilmidir” diye tarif edilir. 
 Alan temalarını oluşturan asal kaynağının vahyin son kitabı Kur’an-ı Kerim’de; Yahudilik, Hıristiyanlık, Budizm, Sâbiîlik, Haniflik, Ehl-i Kitap, Hz. Musa, Hz. İsa, Hz. Muhammed, kurban, esâtîr, Arap şirk ve Mısır/Firavun pagan dinlerinin, terim ve temalarının anlam alanlarına değinilirken, Dinler Tarihi ilmine mukâyeseli yönleri ile de saha çalışması teşkil etmektedir. 
 Gerek Batı gerek Doğu dünyasında yoğun sayıda din ilimleri araştırmacısına alan oluşturan karakteri yanında deskriptif ve normatif metodların yörüngesinde Dinler Tarihi, Kur’an’ı temel kabul eden vasfı ile politeizm, pagan kültleri, şirk, küfür türü inançsızlık tanımları üzerinden tevhid inancına yönlendirme eksenlerinde yüksek düzeyli ve etkin rol oynamaktadır.
 Yerkürede, üzerine en yoğun analizlerin yapıldığı, dünyanın; popülasyonu en yoğun teoloji, Haçlı Seferleri üzerinden siyasî, askerî, savaş tarihinde en etkili dinin, Kur’an’da detaylı beyanla anlatılan Hıristiyanlığın olduğu Dinler Tarihi alanında, az sayıdaki nüfusuna rağmen Yahudilik de benzer sebeplerle üzerinde durulan bir başka dindir.

Judgment aggregation, discursive dilemma and reflective equilibrium: Neural language models as self-improving doxastic agents.

Neural language models (NLMs) are susceptible to producing inconsistent output. This paper proposes a new diagnosis as well as a novel remedy for NLMs' incoherence. We train NLMs on synthetic text corpora that are created by simulating text production in a society. For diagnostic purposes, we explicitly model the individual belief systems of artificial agents (authors) who produce corpus texts. NLMs, trained on those texts, can be shown to aggregate the judgments of individual authors during pre-training according to sentence-wise vote ratios (roughly, reporting frequencies), which inevitably leads to so-called discursive dilemmas: aggregate judgments are inconsistent even though all individual belief states are consistent. As a remedy for such inconsistencies, we develop a self-training procedure-inspired by the concept of reflective equilibrium-that effectively reduces the extent of logical incoherence in a model's belief system, corrects global mis-confidence, and eventually allows the model to settle on a new, epistemically superior belief state. Thus, social choice theory helps to understand why NLMs are prone to produce inconsistencies; epistemology suggests how to get rid of them.

Expert Opinion Fusion Framework Using Subjective Logic for Fault Diagnosis.

Fault diagnosis plays a critical role in maintaining and troubleshooting engineered systems. Various diagnosis models, such as Bayesian networks (BNs), have been proposed to deal with this kind of problem in the past. However, the diagnosis results may not be reliable if second-order uncertainty is involved. This article proposes a hierarchical system diagnosis fusion framework that considers the uncertainty based on a belief model, called subjective logic (SL), which explicitly deals with uncertainty representing a lack of evidence. The proposed system diagnosis fusion framework consists of three steps: 1) individual subjective BNs (SBNs) are designed to represent the knowledge architectures of individual experts; 2) experts are clustered as expert groups according to their similarity; and 3) after inferring expert opinions from respective SBNs, the one opinion fusion method was used to combine all opinions to reach a consensus based on the aggregated opinion for system diagnosis. Via extensive simulation experiments, we show that the proposed fusion framework, consisting of two operators, outperforms the state-of-the-art fusion operator counterparts and has stable performance under various scenarios. Our proposed fusion framework is promising for advancing state-of-the-art fault diagnosis of complex engineered systems.

Ethics, a humanitarian act in Nursing and Gerontological research

Speaking of ethics in the field of nursing research entails the guided search for solutions to problems which are susceptible to intervention from human health sciences. In the disciplines of nursing and obstetrics, there is direct interaction between the professional and the patient at different stages of the process. There are numerous rules and criteria that every professional must learn and put into practice. A model of beliefs, personal family values, and the new normal are reflected in the professional performance of each individual.

Ramsey’s conditionals

In this paper, we propose a unified account of conditionals inspired by Frank Ramsey. Most contemporary philosophers agree that Ramsey’s account applies to indicative conditionals only. We observe against this orthodoxy that his account covers subjunctive conditionals as well—including counterfactuals. In light of this observation, we argue that Ramsey’s account of conditionals resembles Robert Stalnaker’s possible worlds semantics supplemented by a model of belief. The resemblance suggests to reinterpret the notion of conditional degree of belief in order to overcome a tension in Ramsey’s account. The result of the reinterpretation is a tenable account of conditionals that covers indicative and subjunctive as well as qualitative and probabilistic conditionals.

Professionals' beliefs in patient involvement for hospital safety.

to analyze the beliefs of health care professionals about the benefits of patient involvement in care during hospitalization. a descriptive, exploratory, qualitative study was conducted with 87 health professionals from a teaching hospital. Semi-structured interviews were conducted between December 2019 and January 2020 - data was submitted to content analysis and interpreted in light of Rosenstock's Model of Beliefs in Health. participants included nursing technicians, nurses, doctors, and other professionals. The categories "Professionals' beliefs about patient involvement in care", "Practices of patient involvement in care" and "Factors favoring patient involvement in hospital care" emerged. The perception of professionals revealed the influence of patient involvement in care outcomes and benefits for the safety of care. involving the patient in care is associated with the healthcare professional's belief in the benefits of this practice for reducing incidents.

Development and validation of a conceptual model of femininity-related intermediate beliefs about alcohol use among female undergraduate students

Development and validation of a conceptual model of femininity-related intermediate beliefs about alcohol use among female undergraduate students

Generating Stories that Include Failed Actions by Modeling False Character Beliefs

Previous work on story planning has lacked a knowledge representation for characters that make mistakes in the execution of their actions. In particular, characters' execution mistakes that arise from errors in belief have not been modeled. In this paper, we describe a state-space planning system and its belief model, together called HeadSpace, that generates stories that track and manipulates characters' belief about the story world around them. This model is used to produce actions in stories that are attempted but that fail. We show an example story plan that contains failed-action content that cannot be generated by typical planning-based approaches to story creation.

Contribution of Eye-Tracking to Study Cognitive Impairments Among Clinical Populations.

In the field of psychology, the merge of decision-theory and neuroscientific methods produces an array of scientifically recognized paradigms. For example, by exploring consumer’s eye-movement behavior, researchers aim to deepen the understanding of how patterns of retinal activation are being meaningfully transformed into visual experiences and connected with specific reactions (e.g., purchase). Notably, eye-movements provide knowledge of one’s homeostatic balance and gatekeep information that shape decisions. Hence, vision science investigates the quality of observed environments determined under various experimental conditions. Moreover, it answers questions on how human process visual stimuli and use gained information for a successful strategy to achieve certain goals. While capturing cognitive states with the support of the eye-trackers progresses at a relatively fast pace in decision-making research, measuring the visual performance of real-life tasks, which require complex cognitive skills, is tentatively translated into clinical experiments. Nevertheless, the potential of the human eye as a highly valuable source of biomarkers has been underlined. In this article, we aim to draw readers attention to decision-making experimental paradigms supported with eye-tracking technology among clinical populations. Such interdisciplinary approach may become an important component that will (i) help in objectively illustrating patient’s models of beliefs and values, (ii) support clinical interventions, and (iii) contribute to health services. It is possible that shortly, eye-movement data from decision-making experiments will grant the scientific community a greater understanding of mechanisms underlining mental states and consumption practices that medical professionals consider as obsessions, disorders or addiction.

Two-Level Model of Attitudes and Beliefs Influencing Higher Order Thinking (HOT) Skills in Mathematics

Abstract This article focuses on a two-level model analysis of attitudes and beliefs affecting students’ higher order thinking (HOT) skills in mathematics in Aceh, Indonesia. The data used are nested within the hierarchical ordering of both student (level 1) and teacher (level 2). The variables used at level 1 in the study include liking mathematics, valuing mathematics, confidence in mathematics, and individual judgement of mathematics ability, as well as beliefs concerning mathematics related to lower order thinking (LOT) and higher order thinking (HOT). The variables at level 2 involve beliefs concerning mathematics teaching related to LOT and beliefs concerning mathematics teaching related to HOT. The analysis reveals that there are four variables at level 1 contributing to student HOT skills in mathematics: liking mathematics, individual judgement of mathematics ability, beliefs concerning mathematics related to LOT, and beliefs concerning mathematics related to HOT. At level 2, the one variable affecting student HOT skills in mathematics is teacher beliefs concerning mathematics related to HOT.

Anxiety Enhances Recall of Supernatural Agents

ABSTRACT The motivational account of religious belief – that belief fulfills some psychological need – has been historically popular, and recent studies have identified a causal role for anxiety in particular. However, the cognitive mechanisms by which anxiety ultimately produces religious belief are unclear. In two studies, we show that anxiety intensifies a known cognitive bias to recall supernatural agents via preferential processing of the threatening characteristics of these agents. Across the two studies, participants exposed to an anxiety manipulation at encoding (but not at retrieval) exhibited a stronger recall bias for supernatural agents than controls, regardless of how anxiety was elicited and regardless of participants’ religiosity. The results suggest that people in anxious states are more likely to remember and accumulate representations of supernatural or “godlike” agents than people in non-anxious states, potentially biasing them toward religious belief in these agents. This work therefore lends support and detail to the motivational account, addresses the puzzle of why some malevolent gods attract believers, and, by illustrating the importance of anxiety in recall for supernatural agents, argues for the construction of cognitive-motivational models of religious belief.

Ambiguous characters

Artikkelissa selvitetään, miten tietäjä-hahmot esitetään 1800-luvun lopulla ja 1900-luvun alussa ruotsinkieliseltä Pohjanmaalta kerätyssä folkloristisessa aineistossa. Aineistoa lähestytään kvalitatiivisen tekstianalyysin kautta. Esitän, että pohjanmaalaiset ruotsinkieliset uskomustarinat tietäjistä pohjautuvat vakiintuneisiin vernakulaareihin uskomuksiin, jotka ovat samankaltaisia länsieurooppalaisen cunning folk-mallin kanssa. Uskomusaineistossa esiintyvät tietäjähahmot olivat yhteisön jäseniä, jotka paransivat sairauksia, löysivät kadonneita esineitä, ihmisiä ja eläimiä sekä harjoittivat vahingoittavaa magiaa. Artikkeli tarjoaa uutta tietoa vähän tutkitusta uskomusperinteestä ruotsinkielisellä Pohjanmaalla. Tietäjiin liitettyjä vernakulaareja uskomusmalleja voidaan hyödyntää myös muiden ruotsinkielisten alueiden perinteen tutkimuksessa. Artikkelissa tarkastellaan myös sitä, oliko tietäjäperinne katoamassa ruotsinkieliseltä Pohjanmaalta perinteenkeräyksen aikaan uskomustarinoiden perusteella. Tulokset osoittavat, että ruotsinkielisellä Pohjanmaalla tietäjäperinne oli vakiintunut osa paikallista folklorea.

Development and Validation of Teachers’ Assessment Belief of Mathematical Thinking Instrument

<p style="text-align: justify;">This study was conducted to corroborate in understanding the teachers’ beliefs about assessment practices. The prior studies related to teachers’ assessment beliefs in mathematics have been done to assess teachers’ beliefs in the general context of mathematics teaching. This study developed an instrument to assess teachers’ assessment beliefs of mathematical thinking. The research aimed to develop and validate a scale of assessment beliefs of mathematical thinking by using the confirmatory factor analysis. The first draft of the scale contained 25 items. The sample of the study consisted of 537 mathematics teachers from public schools in Oman. The instrument was a questionnaire with a 5-point Likert scale. The scale was validated by asking a number of experts in mathematics educational measurement and evaluation. Exploratory and confirmatory factor analysis was applied to test the model of assessment beliefs of mathematical thinking scale using AMOS 25.0. All constructs had acceptable reliability. The model had a good model fit for the assessment beliefs of mathematical thinking scale which obtainable from the fit indices tests. The findings revealed that all fit criteria indices were realized. The results also showed acceptable validity and construct reliability for the scale.</p>

The Changing Forest Utilization and Management of Mlabri Tribe at Bokluea District, Nan Province, Thailand

This study investigates the changes in forest utilization and management of the Mlabri tribe in Phufa Village, Nan Province, Thailand. This research utilizes quantitative and qualitative methods, such as interviews, community meetings, focus groups and participant observation. The population in the Mlabri village is around 40. It was found that the Mlabri villagers utilized 13 groups to collect 92 different species of forest products to earn a total income of 490,000 baht per year. For resource management, the forest communities have two forms of forest management. These are: (a) a belief model that governs the supernatural mysteries; and (b) a modern community-based management system, which reflects modern rules and regulations from the local authorities. Since the Mlabri people share the same space with other communities, they need to follow the rules set by the owners of the area. Based on the type of forests, the Mlabri tribe utilizes forest management under the concepts of conservation and awareness-raising. The Mlabri people changed from using forest resources for subsistence and exchanged for items that they could not obtain, such as iron, salt and tobacco. At present, the people in the Mlabri tribe have become labourers and agricultural workers. Hunting and gathering forest products are just for earning some extra income and relaxation. Although hunting and gathering is no longer a primary activity among the Mlabri, it is an activity that improves the quality of their life. It also creates a new identity for the Mlabri tribe, which changes the context of the Mlabri society while making the story of the "people living with the forest" interesting. Keywords: Mlabri tribe, hunting and gathering society, utilization and forest management

From hexagon to a globe: The spherical model of interests and competence beliefs by Terence Tracey

The paper presents the Spherical Model of Interests and Competence Beliefs proposed by T. Tracey (Tracey, 1997, 2002, 2010; Tracey, Rounds, 1996a, 1996b). This concept integrates Holland’s RIASEC theory (1985, 1997) and the People/Things, Data/Ideas dimensions of human activity according to Prediger (1982), supplementing them with prestige, which is an indicator of professional interests and choices. The resulting three-dimensional model allows for a more complete and detailed analysis of professional interests. It includes 8 areas of basic interest and 10 types of specific interests, depending on the preferred level of prestige. The text also describes three instruments to assess professional interests, based on the discussed concept.