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Academic literature on the topic 'Belief-Tracking'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Belief-Tracking"

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Baltag, Alexandru, Nina Gierasimczuk, and Sonja Smets. "Truth-Tracking by Belief Revision." Studia Logica 107, no. 5 (July 20, 2018): 917–47. http://dx.doi.org/10.1007/s11225-018-9812-x.

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Xu, Jian-min, Shu-fang Wu, and Yu Hong. "Topic tracking with Bayesian belief network." Optik 125, no. 9 (May 2014): 2164–69. http://dx.doi.org/10.1016/j.ijleo.2013.10.044.

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Adams, Fred, John A. Barker, and Murray Clarke. "Knowledge as Fact-Tracking True Belief." Manuscrito 40, no. 4 (December 2017): 1–30. http://dx.doi.org/10.1590/0100-6045.2017.v40n4.fa.

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Brafman, Ronen I., and Guy Shani. "Online belief tracking using regression for contingent planning." Artificial Intelligence 241 (December 2016): 131–52. http://dx.doi.org/10.1016/j.artint.2016.08.005.

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Grainger, Sarah A., Julie D. Henry, Claire K. Naughtin, Marita S. Comino, and Paul E. Dux. "Implicit false belief tracking is preserved in late adulthood." Quarterly Journal of Experimental Psychology 71, no. 9 (January 1, 2018): 1980–87. http://dx.doi.org/10.1177/1747021817734690.

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It is now well established that relative to their younger counterparts, older adults experience difficulties on tasks that require the conscious and explicit processing of others’ mental states (e.g., beliefs, intentions; theory of mind [ToM]). Despite the importance of relatively automatic and unconscious mental state attribution processes in everyday life, no study to date has tested whether tasks that require the implicit processing of others’ belief states also show age-related changes. In this study, younger and older adults completed an implicit false belief task, in which their eye movement patterns were monitored while they passively viewed true and false belief movies. In addition, they were assessed on measures of explicit ToM processing. While older adults showed impairments in explicit ToM processing relative to younger adults, both age groups demonstrated a similar capacity for implicit false belief processing. These findings suggest that implicit components of ToM are preserved in late adulthood and are consistent with dual process models of ageing that emphasise age-related stability in automatic processing and declines in more controlled and effortful cognitive operations. We discuss the potential implications of these findings for social interactions in old age.
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KHONGKRAPHAN, Kittiya, and Pakorn KAEWTRAKULPONG. "Efficient Human Body Tracking by Quick Shift Belief Propagation." IEICE Transactions on Information and Systems E94-D, no. 4 (2011): 905–12. http://dx.doi.org/10.1587/transinf.e94.d.905.

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Schneider, Dana, Virginia P. Slaughter, and Paul E. Dux. "What do we know about implicit false-belief tracking?" Psychonomic Bulletin & Review 22, no. 1 (May 22, 2014): 1–12. http://dx.doi.org/10.3758/s13423-014-0644-z.

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Xue, Jianru, Nanning Zheng, Jason Geng, and Xiaopin Zhong. "Tracking Multiple Visual Targets via Particle-Based Belief Propagation." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 38, no. 1 (February 2008): 196–209. http://dx.doi.org/10.1109/tsmcb.2007.910533.

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Jogan, Matjaz, Alan He, Alexander Tank, and Alan Stocker. "Humans maintain probabilistic belief states when tracking occluded objects." Journal of Vision 15, no. 12 (September 1, 2015): 188. http://dx.doi.org/10.1167/15.12.188.

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Xue, Jianru, Nanning Zheng, and Xiaopin Zhong. "Sequential stratified sampling belief propagation for multiple targets tracking." Science in China Series F 49, no. 1 (January 2006): 48–62. http://dx.doi.org/10.1007/s11432-004-0140-6.

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Dissertations / Theses on the topic "Belief-Tracking"

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Kominis, Filippos. "Belief tracking for multi-agent planning." Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/457705.

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Classical planning is the problem of finding a sequence of actions that achieve a desired goal from an initial state, assuming deterministic actions. Dynamic epistemic logic (DEL) on the other hand, provides formal frameworks that allow the modeling of complex beliefs in multi-agent settings and define how those beliefs change due to physical and communication actions. In this dissertation we focus on bridging the gap between the expressivity of DEL and the computational approaches used in classical planning. First, we present formulations that capture a fragment of the expressivity of DEL and can model nested knowledge in two different multi-agent settings. Second, we tackle the computational problem of finding plans by providing translations to classical planning that allow the use of classical planners and heuristic search. We empirically evaluate our approaches and discuss their formal properties.
La Planificació Clàssica és un problema que busca una seqüèencia d’accions per arribar a una meta o objectiu des d’un estat inicial, assumint que les accions són deterministes. Per una altra banda, la Lògica Epistèmica Dinàmica (LED), proporciona una eina de treball formal que permet el modelatge de creences complexes en un entorn de múltiples agents, i defineix com aquestes creences varien aplicant accions físiques i de comunicació. En aquesta disertació ens centrem en connectar l’expressivitat de LED amb els diferents enfocaments que s’utilitzen a planificació clàssica. Primer presentem les formulacions que capturen un fragment de l’expressivitat de LED i que pot modelar coneixement anidat en dos configuracions diferents amb múltiples agents. Després abordem el problema computacional de trobar plans, tot proporcionant traduccions de planificació clàssica que permeten utilitzar planificadors clàssics amb búsquedes heurístiques. Finalment, evaluem de forma empírica els nostres enfocaments i parlem sobre les seves propietats formals.
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Roberts, Matthew Simon. "Tracking and classification with wireless sensor networks and the transferable belief model." Thesis, Cardiff University, 2010. http://orca.cf.ac.uk/55134/.

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The use of small, cheap, networked devices to collaboratively perform a task presents an attractive opportunity for many scenarios. One such scenario is the tracking and classification of an object moving through a region of interest. A single sensor is capable of very little, but a group of sensors can potentially provide a flexible, self-organising system that can carry out tasks in harsh conditions for long periods of time. This thesis presents a new framework for tracking and classification with a wire less sensor network. Existing algorithms have been integrated and extended within this framework to perform tracking and classification whilst managing energy usage in order to balance the quality of information with the cost of obtaining it. Novel improvements are presented to perform tracking and classification in more realistic scenarios where a target is moving in a non-linear fashion over a varying terrain. The framework presented in this thesis can be used not only in algorithm development, but also as a tool to aid sensor deployment planning. All of the algorithms presented in this thesis have a common basis that results from the integration of a wireless sensor network management algorithm and a tracking and classification algorithm both of which are considered state-of-the-art. Tracking is performed with a particle filter, and classification is performed with the Transferable Belief Model. Simulations are used throughout this thesis in order to compare the performance of different algorithms. A large number of simulations are used in each experiment with various parameter combinations in order to provide a detailed analysis of each algorithm and scenario. The work presented in this thesis could be of use to developers of wireless sensor network algorithms, and also to people who plan the deployment of nodes. This thesis focuses on military scenarios, but the research presented is not limited to this.
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Bharathan, Vivek. "Belief Revision in Dynamic Abducers through Meta-Abduction." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1276787509.

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Savic, Vladimir. "Nonparametric Message Passing Methods for Cooperative Localization and Tracking." Doctoral thesis, Technical University of Madrid, Spain, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-81446.

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The objective of this thesis is the development of cooperative localization and tracking algorithms using nonparametric message passing techniques. In contrast to the most well-known techniques, the goal is to estimate the posterior probability density function (PDF) of the position of each sensor. This problem can be solved using Bayesian approach, but it is intractable in general case. Nevertheless, the particle-based approximation (via nonparametric representation), and an appropriate factorization of the joint PDFs (using message passing methods), make Bayesian approach acceptable for inference in sensor networks. The well-known method for this problem, nonparametric belief propagation (NBP), can lead to inaccurate beliefs and possible non-convergence in loopy networks. Therefore, we propose four novel algorithms which alleviate these problems: nonparametric generalized belief propagation (NGBP) based on junction tree (NGBP-JT), NGBP based on pseudo-junction tree (NGBP-PJT), NBP based on spanning trees (NBP-ST), and uniformly-reweighted NBP (URW-NBP). We also extend NBP for cooperative localization in mobile networks. In contrast to the previous methods, we use an optional smoothing, provide a novel communication protocol, and increase the efficiency of the sampling techniques. Moreover, we propose novel algorithms for distributed tracking, in which the goal is to track the passive object which cannot locate itself. In particular, we develop distributed particle filtering (DPF) based on three asynchronous belief consensus (BC) algorithms: standard belief consensus (SBC), broadcast gossip (BG), and belief propagation (BP). Finally, the last part of this thesis includes the experimental analysis of some of the proposed algorithms, in which we found that the results based on real measurements are very similar with the results based on theoretical models.
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Lin, Chung-Ching. "Detecting and tracking moving objects from a moving platform." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/49014.

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Detecting and tracking moving objects are important topics in computer vision research. Classical methods perform well in applications of steady cameras. However, these techniques are not suitable for the applications of moving cameras because the unconstrained nature of realistic environments and sudden camera movement makes cues to object positions rather fickle. A major difficulty is that every pixel moves and new background keeps showing up when a handheld or car-mounted camera moves. In this dissertation, a novel estimation method of camera motion parameters will be discussed first. Based on the estimated camera motion parameters, two detection algorithms are developed using Bayes' rule and belief propagation. Next, an MCMC-based feature-guided particle filtering method is presented to track detected moving objects. In addition, two detection algorithms without using camera motion parameters will be further discussed. These two approaches require no pre-defined class or model to be trained in advance. The experiment results will demonstrate robust detecting and tracking performance in object sizes and positions.
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Rekik, Wafa. "Vers le suivi d’objets dans un cadre évidentiel : représentation, filtrage dynamique et association." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112040/document.

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Les systèmes intelligents sont de plus en plus présents dans notre société à l’instar des systèmes de surveillance et de protection de sites civils ou militaires. Leur but est de détecter les intrus et remonter une alarme ou une menace à un opérateur distant. Dans nos travaux, nous nous intéressons à de tels systèmes avec comme objectif de gérer au mieux la qualité de l’information présentée à l’opérateur en termes de fiabilité et précision. Nous nous concentrons sur la modalité image en vue de gérer des détections à la fois incertaines et imprécises de façon à présenter des objets fiables à l’opérateur.Pour préciser notre problème nous posons les contraintes suivantes. La première est que le système soit modulaire, l’une des briques (ou sous-fonctions) du système étant la détection de fragments correspondant potentiellement à des objets. Notre deuxième contrainte est alors de n’utiliser que des informations issues de la géométrie des détections fragmentaires : localisation spatiale dans l’image et taille des détections. Une menace est alors supposée d’autant plus importante que les détections sont de tailles importantes et temporellement persistantes.Le cadre formel choisi est la théorie des fonctions de croyance qui permet de modéliser des données à la fois imprécises et incertaines. Les contributions de cette thèse concernent la représentation des objets en termes de localisation imprécise et incertaine et le filtrage des objets.La représentation pertinente des informations est un point clé pour les problèmes d’estimation ou la prise de décision. Une bonne représentation se reconnaît au fait qu’en découlent des critères simples et performants pour résoudre des sous-problèmes. La représentation proposée dans cette thèse a été valorisée par le fait qu’un critère d’association entre nouvelles détections (fragments) et objets en construction, a pu être défini d’une façon simple et rigoureuse. Rappelons que cette association est une étape clé pour de nombreux problèmes impliquant des données non étiquettées, ce qui étend notre contribution au-delà de l’application considérée.Le filtrage des données est utilisé dans de nombreuses méthodes ou algorithmes pour robustifier les résultats en s’appuyant sur la redondance attendue des données s’opposant à l’inconsistance du bruit. Nous avons alors formulé ce problème en termes d’estimation dynamique d’un cadre de discernement contenant les ‘vraies hypothèses’. Ce cadre est estimé dynamiquement avec la prise en compte de nouvelles données (ou observations) permettant de détecter deux principaux types d’erreurs : la duplication de certaines hypothèses (objets dans notre application), la présence de fausses alarmes (dues au bruit ou aux fausses détections dans notre cas).Pour finir nous montrons la possibilité de coupler nos briques de construction des objets et de filtrage de ces derniers avec une brique de suivi utilisant des informations plus haut niveau, telle que les algorithmes de tracking classiques de traitement d’image.Mots clés: théorie des fonctions des croyances, association de données, filtrage
Intelligent systems are more and more present in our society, like the systems of surveillance and civilian or military sites protection. Their purpose is to detect intruders and present the alarms or threats to a distant operator. In our work, we are interested in such systems with the aim to better handle the quality of information presented to the operator in terms of reliability and precision. We focus on the image modality and we have to handle detections that are both uncertain and imprecise in order to present reliable objects to the operator.To specify our problem, we consider the following constraints. The first one is that the system is modular; one subpart of the system is the detection of fragments corresponding potentially to objects. Our second constraint is then to use only information derived from the geometry of these fragmentary detections: spatial location in the image and size of the detections. Then, a threat is supposed all the more important as the detections have an important size and are temporally persistent.The chosen formal framework is the belief functions theory that allows modeling imprecise and uncertain data. The contributions of this thesis deal with the objects representation in terms of imprecise and uncertain location of the objects and object filtering.The pertinent representation of information is a key point for estimation problems and decision making. A representation is good when simple and efficient criteria for the resolution of sub problems can be derived. The representation proposed has allowed us to derive, in a simple and rigorous way, an association criterion between new detections (fragments) and objects under construction. We remind that this association is a key step for several problems with unlabelled data that extends our contribution beyond of the considered application.Data filtering is used in many methods and algorithms to robustify the results using the expected data redundancy versus the noise inconsistency. Then, we formulated our problem in terms of dynamic estimation of a discernment frame including the 'true hypotheses'. This frame is dynamically estimated taking into account the new data (or observations) that allow us to detect two main types of errors, namely the duplication of some hypotheses (objects in our application) and the presence of false alarms (due to noise or false detections in our case).Finally, we show the possibility of coupling our sub-functions dealing with object construction and their filtering with a tracking process using higher level information such as classical tracking algorithm in image processing.Keywords: belief functions theory, data association, filtering
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Hachour, Samir. "Suivi et classification d'objets multiples : contributions avec la théorie des fonctions de croyance." Thesis, Artois, 2015. http://www.theses.fr/2015ARTO0206/document.

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Cette thèse aborde le problèeme du suivi et de la classification de plusieurs objets simultanément.Il est montré dans la thèese que les fonctions de croyance permettent d'améliorer les résultatsfournis par des méthodes classiques à base d'approches Bayésiennes. En particulier, une précédenteapproche développée dans le cas d'un seul objet est étendue au cas de plusieurs objets. Il est montréque dans toutes les approches multi-objets, la phase d'association entre observations et objetsconnus est fondamentale. Cette thèse propose également de nouvelles méthodes d'associationcrédales qui apparaissent plus robustes que celles trouvées dans la littérature. Enfin, est abordée laquestion de la classification multi-capteurs qui nécessite une seconde phase d'association. Dans cedernier cas, deux architectures de fusion des données capteurs sont proposées, une dite centraliséeet une autre dite distribuée. De nombreuses comparaisons illustrent l'intérêt de ces travaux, queles classes des objets soient constantes ou variantes dans le temps
This thesis deals with multi-objet tracking and classification problem. It was shown that belieffunctions allow the results of classical Bayesian methods to be improved. In particular, a recentapproach dedicated to a single object classification which is extended to multi-object framework. Itwas shown that detected observations to known objects assignment is a fundamental issue in multiobjecttracking and classification solutions. New assignment solutions based on belief functionsare proposed in this thesis, they are shown to be more robust than the other credal solutions fromrecent literature. Finally, the issue of multi-sensor classification that requires a second phase ofassignment is addressed. In the latter case, two different multi-sensor architectures are proposed, aso-called centralized one and another said distributed. Many comparisons illustrate the importanceof this work, in both situations of constant and changing objects classes
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Yogeswaran, Arjun. "Self-Organizing Neural Visual Models to Learn Feature Detectors and Motion Tracking Behaviour by Exposure to Real-World Data." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37096.

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Advances in unsupervised learning and deep neural networks have led to increased performance in a number of domains, and to the ability to draw strong comparisons between the biological method of self-organization conducted by the brain and computational mechanisms. This thesis aims to use real-world data to tackle two areas in the domain of computer vision which have biological equivalents: feature detection and motion tracking. The aforementioned advances have allowed efficient learning of feature representations directly from large sets of unlabeled data instead of using traditional handcrafted features. The first part of this thesis evaluates such representations by comparing regularization and preprocessing methods which incorporate local neighbouring information during training on a single-layer neural network. The networks are trained and tested on the Hollywood2 video dataset, as well as the static CIFAR-10, STL-10, COIL-100, and MNIST image datasets. The induction of topography or simple image blurring via Gaussian filters during training produces better discriminative features as evidenced by the consistent and notable increase in classification results that they produce. In the visual domain, invariant features are desirable such that objects can be classified despite transformations. It is found that most of the compared methods produce more invariant features, however, classification accuracy does not correlate to invariance. The second, and paramount, contribution of this thesis is a biologically-inspired model to explain the emergence of motion tracking behaviour in early development using unsupervised learning. The model’s self-organization is biased by an original concept called retinal constancy, which measures how similar visual contents are between successive frames. In the proposed two-layer deep network, when exposed to real-world video, the first layer learns to encode visual motion, and the second layer learns to relate that motion to gaze movements, which it perceives and creates through bi-directional nodes. This is unique because it uses general machine learning algorithms, and their inherent generative properties, to learn from real-world data. It also implements a biological theory and learns in a fully unsupervised manner. An analysis of its parameters and limitations is conducted, and its tracking performance is evaluated. Results show that this model is able to successfully follow targets in real-world video, despite being trained without supervision on real-world video.
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Chang, Chun-Kai, and 張鈞凱. "Adapting Measurement and Belief Sharing in Multi-Robot Simultaneous Localization and Tracking." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/15113269748197904348.

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碩士
國立臺灣大學
資訊工程學研究所
103
Existing multi-robot cooperative perception solutions can be mainly classified into two categories, measurement-based and belief-based, according to the information shared among robots. With well-controlled communication, measurement-based approaches are expected to achieve theoretically optimal estimates while belief-based approaches are not. Nevertheless, belief-based approaches perform relatively stable under unstable communication as a belief contains the information of multiple previous measurements. Motivated by the observation that measurement sharing and belief sharing are respectively superior in different conditions, in this thesis an adapting algorithm, communication adaptive multi-robot simultaneous localization and tracking (ComAd MRSLAT), is proposed to combine the advantages of both to tackle the unstable communication conditions. However, the decision process of what kind of information to share is only based on a probability distribution of states, which is estimated according to a set of observations and observation probabilities. Therefore, it could be seen as a multi-robot partially observable Markov decision process (POMDP) problem. The information to share is decided by maximizing the expected uncertainty reduction, based on which the algorithm dynamically alternates between measurement-sharing and belief-sharing without information loss or reuse. With using the expected effective communication and information receiving, the proposed ComAd MR-SLAT can tackle the complexity issue and online decide the sharing strategy to adapt different communication conditions. The proposed ComAd MR-SLAT is evaluated in communication conditions with different packet loss rates, bursty loss lengths, and data association conditions. The proposed ComAd MR-SLAT outperforms both measurement-based and belief-based MR-SLAT in both localization and data association accuracy. In addition, the real data are also collected and evaluated, the experimental results demonstrate the effectiveness of the proposed adapting algorithm and exhibit that the ComAd MR-SLAT is robust in the simulation and real data experiment.
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LIU, LUN CHI, and 劉倫綺. "Study on behavior tracking of cases with positive colorectal cancer screening test by using health belief model." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/kyh6w9.

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碩士
國立臺南大學
行政管理學系碩士在職專班
107
With the impact of lifestyle changes and westernization of diet, the number of people suffering from colorectal polyps and colorectal cancer has increased year by year. In 2017, colorectal cancer mortality was the third cancer leading cause of death (Health Promotion Administration, Ministry of Health and Welfare, 2018). In this study, our research object is patients undergoing colonoscopy in a regional hospital in the south that to conduct research case collection. In the chapter 3, we use research hypotheses, research frameworks and valid questionnaire sample to do data analysis and processing by statistical methods, in order to verify the aforementioned research hypotheses. Describe the questionnaire issuing and response situation for the statistical analysis result of each variable, and analyze the valid sample questionnaire by descriptive statistics. We conducted factor analysis, reliability and validity testing for questionnaire scales. Using analysis of variance and regression analysis. Exploring whether there are significant differences between variables by t-test and ANOVA, and regression analysis was used to verify the hypothesis of dimensions. Positive impact on colorectal cancer screening behavior by the dimensions of perceived susceptibility, perceived severity, perceived benefits, perceived barriers and Cues to action. It shows that people will be affected by health beliefs and generate different feelings for different positive influences. We can speculate that the health belief model does have an influence on the willingness of the people to screen. The samples of this study focus on the people in Tainan, so its representative is slightly higher. It is difficult to conduct a random sampling method for a specific parent group. We recommend that further research extend the scope of samples to outside Tainan or to the country and compare them to do more in-depth research and analysis. There should be different contributions for study of the willingness of the people to screen. Most people think that cancer screening is more health-conscious. In this research, it shows more people did not consider healthy behavior due to the dimension of perceived barriers. It is recommended that follow-up researchers adopt qualitative research methods, and more in-depth discussions provide a reference for policy advocacy.
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Books on the topic "Belief-Tracking"

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Nagel, Jennifer. 5. Internalism and externalism. Oxford University Press, 2014. http://dx.doi.org/10.1093/actrade/9780199661268.003.0005.

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Internalism represents the first-person point of view where knowledge is grounded by your own experience and by your own capacity to reason: if you can't see for yourself why you should believe something, you don't actually know it. Externalists say knowledge is a relationship between a person and a fact, and this relationship can be in place even when the person doesn't meet the internalist's demands for first-person access to supporting grounds. ‘Internalism and externalism’ also explains Robert Nozick's externalist tracking theory of knowledge and its difficulty, the ‘Generality Problem’. Many different solutions have been advanced, drawing on everything from patterns in natural language to the science of belief formation.
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Lipton, Gregory A. Tracking the Camels of Love. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190684501.003.0002.

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This chapter is based on a revised reading of Ibn ‘Arabi’s most famous verses from The Interpreter of Desires (Tarjumān al-ashwāq) that claim to follow “the religion of Love” via a heart “capable of every form.” It thus argues that modern Euro-American presuppositions regarding the nature of “religion” as a “system of beliefs” inform how the celebrated verses are commonly received and interpreted. While Ibn ‘Arabi’s claim to a heart “capable of every form” is synonymous with a claim to be capable of every belief, it is not tantamount to accepting the validity of every religion. Rather, the celebrated verses profess to inherit the comprehensive perfection of Muhammad as God’s beloved and, in so doing, reflect a discourse of religious absolutism and a subsumptive cosmology of power. It is precisely this cosmology of power that has been almost completely occluded by readings equating religion with belief.
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Bratman, Michael E. Planning, Time, and Self-Governance. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190867850.001.0001.

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Our human capacity for planning agency plays central roles in the cross-temporal organization of our agency, in our acting and thinking together, and in our self-governance. Intentions can be understood as states in such a planning system. The practical thinking essential to this planning capacity is guided by norms that enjoin synchronic plan consistency and coherence as well as forms of plan stability over time. This book’s essays aim to deepen our understanding of these norms and defend their status as norms of practical rationality for planning agents. General guidance by these planning norms has many pragmatic benefits, especially given our cognitive and epistemic limits. But appeal to these pragmatic benefits does not fully explain the normative force of these norms in application to the particular case. In response, some think these norms are norms of theoretical rationality on belief; or are constitutive of agency; or are just a myth. These essays chart an alternative path, which sees these planning norms as tracking conditions of a planning agent’s self-governance, both at a time and over time. This path articulates associated models of self-governance; it appeals to the agent’s end of her self-governance over time; and it argues that this end is rationally self-sustaining. This end is thereby in a position to play a role in our planning framework that is analogous to the role of a concern with quality of will within the framework of the reactive attitudes, as understood by Peter Strawson.
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Book chapters on the topic "Belief-Tracking"

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Han, Tony X., and Thomas S. Huang. "Articulated Body Tracking Using Dynamic Belief Propagation." In Computer Vision in Human-Computer Interaction, 26–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11573425_3.

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Xue, Jianru, Nanning Zheng, and Xiaopin Zhong. "Tracking Targets Via Particle Based Belief Propagation." In Computer Vision – ACCV 2006, 348–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11612032_36.

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Liang, Wei, Yunde Jia, and Cheng Ge. "Visual Hand Tracking Using Nonparametric Sequential Belief Propagation." In Lecture Notes in Computer Science, 679–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11538059_71.

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Hu, Dan, Xingshe Zhou, and Junjie Wu. "Visual Tracking Based on Convolutional Deep Belief Network." In Lecture Notes in Computer Science, 103–15. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23216-4_8.

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Du, Wei, and Justus Piater. "Multi-view Object Tracking Using Sequential Belief Propagation." In Computer Vision – ACCV 2006, 684–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11612032_69.

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Xue, Jianru, Nanning Zheng, and Xiaopin Zhong. "Sequential Stratified Sampling Belief Propagation for Multiple Targets Tracking." In Lecture Notes in Computer Science, 330–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11538059_35.

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Wickramarathne, Thanuka L. "Integrity Preserving Belief Update for Recursive Bayesian Tracking with Non-ideal Sensors." In Belief Functions: Theory and Applications, 231–40. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45559-4_24.

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Renna, Ilaria, Catherine Achard, and Ryad Chellali. "Combination of Annealing Particle Filter and Belief Propagation for 3D Upper Body Tracking." In Intelligent Robotics and Applications, 824–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10817-4_81.

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Vivet, Marc, Brais Martínez, and Xavier Binefa. "Real-Time Motion Detection for a Mobile Observer Using Multiple Kernel Tracking and Belief Propagation." In Pattern Recognition and Image Analysis, 144–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02172-5_20.

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Ball, Linden J., and Jeremy D. Quayle. "The Effects of Belief and Logic in Syllogistic Reasoning: Evidence from an Eye-Tracking Analysis." In Proceedings of the Twenty First Annual Conference of the Cognitive Science Society, 49–54. New York: Psychology Press, 2020. http://dx.doi.org/10.4324/9781410603494-14.

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Conference papers on the topic "Belief-Tracking"

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Mrkšić, Nikola, and Ivan Vulić. "Fully Statistical Neural Belief Tracking." In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/p18-2018.

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Ramachandran, Deepak, and Adwait Ratnaparkhi. "Belief Tracking with Stacked Relational Trees." In Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue. Stroudsburg, PA, USA: Association for Computational Linguistics, 2015. http://dx.doi.org/10.18653/v1/w15-4609.

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Baltag, Alexandru, Nina Gierasimczuk, and Sonja Smets. "Belief revision as a truth-tracking process." In hte 13th Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2000378.2000400.

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Mrkšić, Nikola, Diarmuid Ó Séaghdha, Tsung-Hsien Wen, Blaise Thomson, and Steve Young. "Neural Belief Tracker: Data-Driven Dialogue State Tracking." In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/p17-1163.

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Lindberg, C., L. S. Muppirisetty, K. Dahlen, V. Savic, and H. Wymeersch. "MAC delay in belief consensus for distributed tracking." In 2013 10th Workshop on Positioning, Navigation and Communication (WPNC). IEEE, 2013. http://dx.doi.org/10.1109/wpnc.2013.6533255.

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Lin Zheng and Quan Liu. "Articulated Body tracking based on sequential belief propagation." In 2010 2nd International Conference on Computer Engineering and Technology. IEEE, 2010. http://dx.doi.org/10.1109/iccet.2010.5486222.

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Minwoo Park, Yanxi Liu, and Robert T. Collins. "Efficient mean shift belief propagation for vision tracking." In 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2008. http://dx.doi.org/10.1109/cvpr.2008.4587508.

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Ramadan, Osman, Paweł Budzianowski, and Milica Gašić. "Large-Scale Multi-Domain Belief Tracking with Knowledge Sharing." In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/p18-2069.

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Mourllion, B., D. Gruyer, R. Royere, and S. Theroude. "Multi-hypotheses tracking algorithm based on the belief theory." In 2005 7th International Conference on Information Fusion. IEEE, 2005. http://dx.doi.org/10.1109/icif.2005.1591957.

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Du, Wei, and Justus Piater. "Data Fusion by Belief Propagation for Multi-Camera Tracking." In 2006 9th International Conference on Information Fusion. IEEE, 2006. http://dx.doi.org/10.1109/icif.2006.301712.

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Reports on the topic "Belief-Tracking"

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Phillips, Jake. Understanding the impact of inspection on probation. Sheffield Hallam University, 2021. http://dx.doi.org/10.7190/shu.hkcij.05.2021.

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Abstract:
This research sought to understand the impact of probation inspection on probation policy, practice and practitioners. This important but neglected area of study has significant ramifications because the Her Majesty’s Inspectorate of Probation has considerable power to influence policy through its inspection regime and research activities. The study utilised a mixed methodological approach comprising observations of inspections and interviews with people who work in probation, the Inspectorate and external stakeholders. In total, 77 people were interviewed or took part in focus groups. Probation practitioners, managers and leaders were interviewed in the weeks after an inspection to find out how they experienced the process of inspection. Staff at HMI Probation were interviewed to understand what inspection is for and how it works. External stakeholders representing people from the voluntary sector, politics and other non-departmental bodies were interviewed to find out how they used the work of inspection in their own roles. Finally, leaders within the National Probation Service and Her Majesty’s Prisons and Probation Service were interviewed to see how inspection impacts on policy more broadly. The data were analysed thematically with five key themes being identified. Overall, participants were positive about the way inspection is carried out in the field of probation. The main findings are: 1. Inspection places a burden on practitioners and organisations. Practitioners talked about the anxiety that a looming inspection created and how management teams created additional pressures which were hard to cope with on top of already high workloads. Staff responsible for managing the inspection and with leadership positions talked about the amount of time the process of inspection took up. Importantly, inspection was seen to take people away from their day jobs and meant other priorities were side-lined, even if temporarily. However, the case interviews that practitioners take part in were seen as incredibly valuable exercises which gave staff the opportunity to reflect on their practice and receive positive feedback and validation for their work. 2. Providers said that the findings and conclusions from inspections were often accurate and, to some extent, unsurprising. However, they sometimes find it difficult to implement recommendations due to reports failing to take context into account. Negative reports have a serious impact on staff morale, especially for CRCs and there was concern about the impact of negative findings on a provider’s reputation. 3. External stakeholders value the work of the Inspectorate. The Inspectorate is seen to generate highly valid and meaningful data which stakeholders can use in their own roles. This can include pushing for policy reform or holding government to account from different perspectives. In particular, thematic inspections were seen to be useful here. 4. The regulatory landscape in probation is complex with an array of actors working to hold providers to account. When compared to other forms of regulation such as audit or contract management the Inspectorate was perceived positively due to its methodological approach as well as the way it reflects the values of probation itself. 5. Overall, the inspectorate appears to garner considerable legitimacy from those it inspects. This should, in theory, support the way it can impact on policy and practice. There are some areas for development here though such as more engagement with service users. While recognising that the Inspectorate has made a concerted effort to do this in the last two years participants all felt that more needs to be done to increase that trust between the inspectorate and service users. Overall, the Inspectorate was seen to be independent and 3 impartial although this belief was less prevalent amongst people in CRCs who argued that the Inspectorate has been biased towards supporting its own arguments around reversing the now failed policy of Transforming Rehabilitation. There was some debate amongst participants about how the Inspectorate could, or should, enforce compliance with its recommendations although most people were happy with the primarily relational way of encouraging compliance with sanctions for non-compliance being considered relatively unnecessary. To conclude, the work of the Inspectorate has a significant impact on probation policy, practice and practitioners. The majority of participants were positive about the process of inspection and the Inspectorate more broadly, notwithstanding some of the issues raised in the findings. There are some developments which the Inspectorate could consider to reduce the burden inspection places on providers and practitioners and enhance its impact such as amending the frequency of inspection, improving the feedback given to practitioners and providing more localised feedback, and working to reduce or limit perceptions of bias amongst people in CRCs. The Inspectorate could also do more to capture the impact it has on providers and practitioners – both positive and negative - through existing procedures that are in place such as post-case interview surveys and tracking the implementation of recommendations.
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