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Journal articles on the topic 'Elicitation of expert belief'

Author: Grafiati

Published: 10 March 2023

Last updated: 31 July 2025

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1

RENOOIJ, SILJA. "Probability elicitation for belief networks: issues to consider." Knowledge Engineering Review 16, no. 3 (2001): 255–69. http://dx.doi.org/10.1017/s0269888901000145.

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Upon assessing probabilities for Bayesian belief networks, the knowledge and practical experience of experts is often the only available source of probabilistic information. It is important to realise that issues concerning human capabilities with respect to making judgements come into play when relying on experts for probability elicitation. A number of methods for the elicitation of probabilities are known from the field of decision analysis. These methods try, to some extent, to deal with those issues. I present here an overview of the issues to consider when relying on expert judgements an

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Phillipson, Frank, Peter Langenkamp, and Reinder Wolthuis. "Alternative Initial Probability Tables for Elicitation of Bayesian Belief Networks." Mathematical and Computational Applications 26, no. 3 (2021): 54. http://dx.doi.org/10.3390/mca26030054.

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Bayesian Belief Networks are used in many fields of application. Defining the conditional dependencies via conditional probability tables requires the elicitation of expert belief to fill these tables, which grow very large quickly. In this work, we propose two methods to prepare these tables based on a low number of input parameters using specific structures and one method to generate the table using probability tables of each relation of a child node with a certain parent. These tables can be used further as a starting point for elicitation.

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COUPÉ, VEERLE M. H., LINDA C. VAN DER GAAG, and J. DIK F. HABBEMA. "Sensitivity analysis: an aid for belief-network quantification." Knowledge Engineering Review 15, no. 3 (2000): 215–32. http://dx.doi.org/10.1017/s0269888900003027.

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When building a Bayesian belief network, usually a large number of probabilities have to be assessed by experts in the domain of application. Experience shows that experts are often reluctant to assess all probabilities required, feeling that they are unable to give assessments with a high level of accuracy. We argue that the elicitation of probabilities from experts can be supported to a large extent by iteratively performing sensitivity analyses of the belief network in the making, starting with rough, initial assessments. Since it gives insight into which probabilities require a high level

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Bojke, Laura, Marta Soares, Karl Claxton, et al. "Developing a reference protocol for structured expert elicitation in health-care decision-making: a mixed-methods study." Health Technology Assessment 25, no. 37 (2021): 1–124. http://dx.doi.org/10.3310/hta25370.

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Background Many decisions in health care aim to maximise health, requiring judgements about interventions that may have higher health effects but potentially incur additional costs (cost-effectiveness framework). The evidence used to establish cost-effectiveness is typically uncertain and it is important that this uncertainty is characterised. In situations in which evidence is uncertain, the experience of experts is essential. The process by which the beliefs of experts can be formally collected in a quantitative manner is structured expert elicitation. There is heterogeneity in the existing

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Kreinovich, Vladik. "INTERVAL METHODS IN KNOWLEDGE REPRESENTATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 04, no. 05 (1996): 467–90. http://dx.doi.org/10.1142/s0218488596000433.

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In this issues, we continue to publish abstracts and reviews of recents papers on interval methods in knowledge representation. In knowledge representation, intervals are used for two main purposes: • to describe durations of events; and • to describe uncertainty of measurement results and expert estimates of different quantities; often, we do not know the exact value of a quantity, but we know its lower and upper bounds (e.g., we may not know the exact value of someone's weight, but we may know that this weight is in between 140 and 160 pounds). An important case of this uncertainty occurs in

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Anuar, Nadia, Ahmad Mazli Muhammad, and Zainudin Awang. "An Exploratory Factor Analysis of Elicited Students’ Salient Beliefs Toward Critical Reading." International Journal of Modern Languages And Applied Linguistics 4, no. 4 (2020): 101. http://dx.doi.org/10.24191/ijmal.v4i4.11288.

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Critical reading was named a key aspiration in the Malaysian Education Blueprint (2015-2025) and is an essential skill students must acquire. However, an increased number of students was reported to demonstrate poor critical reading performance at the workplace. Thus, Theory of Planned Behaviour (TPB) was utilised to examine students’ beliefs critical reading which encompass behavioural belief (advantages and disadvantages of critical reading), normative belief (identification of people who approve participating in critical reading), and control belief (difficulties in critical reading). A thr

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Carvalho, Arthur. "A Note on Sandroni-Shmaya Belief Elicitation Mechanism." Journal of Prediction Markets 10, no. 2 (2017): 14–21. http://dx.doi.org/10.5750/jpm.v10i2.1225.

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Incentive-compatible methods for eliciting beliefs, such as proper scoring rules, often rely on strong assumptions about how humans behave when making decisions under risk and uncertainty. For example, standard proper scoring rules assume that humans are risk neutral, an assumption that is often violated in practice. Under such an assumption, proper scoring rules induce honest reporting of beliefs, in a sense that experts maximize their expected scores from a proper scoring rule by honestly reporting their beliefs.Sandroni and Shmaya [Economic Theory Bulletin, volume 1, issue 1, 2013] suggeste

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Bryant, Andrew, Michael Grayling, Shaun Hiu, et al. "Residual disease after primary surgery for advanced epithelial ovarian cancer: expert elicitation exercise to explore opinions about potential impact of publication bias in a planned systematic review and meta-analysis." BMJ Open 12, no. 8 (2022): e060183. http://dx.doi.org/10.1136/bmjopen-2021-060183.

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ObjectivesWe consider expert opinion and its incorporation into a planned meta-analysis as a way of adjusting for anticipated publication bias. We conduct an elicitation exercise among eligible British Gynaecological Cancer Society (BGCS) members with expertise in gynaecology.DesignExpert elicitation exercise.SettingBGCS.ParticipantsMembers of the BGCS with expertise in gynaecology.MethodsExperts were presented with details of a planned prospective systematic review and meta-analysis, assessing overall survival for the extent of excision of residual disease (RD) after primary surgery for advan

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Vijayan, Vimal, Sanjay K. Chaturvedi, and Ritesh Chandra. "A failure interaction model for multicomponent repairable systems." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234, no. 3 (2020): 470–86. http://dx.doi.org/10.1177/1748006x19897828.

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Modeling of stochastic dependency among components in a repairable system is still a challenging task when dealing with the maintenance of multicomponent systems. With the help of stochastic dependency information, failure of a component brings attention to the components having strong interactions with the failed component. With this information, one can plan the maintenance of components in a better way. Since a change in failure probability of a component (due to deterioration or failure of a component in a given time interval) influences the failure probabilities of other components in the

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Schlag, Karl H., and Joël J. van der Weele. "A method to elicit beliefs as most likely intervals." Judgment and Decision Making 10, no. 5 (2015): 456–68. http://dx.doi.org/10.1017/s1930297500005593.

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AbstractWe show how to elicit the beliefs of an expert in the form of a “most likely interval”, a set of future outcomes that are deemed more likely than any other outcome. Our method, called the Most Likely Interval elicitation rule (MLI), asks the expert for an interval and pays according to how well the answer compares to the actual outcome. We show that the MLI performs well in economic experiments, and satisfies a number of desirable theoretical properties such as robustness to the risk preferences of the expert.

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Mearns, Linda O., Melissa S. Bukovsky, and Vanessa J. Schweizer. "Potential Value of Expert Elicitation for Determining Differential Credibility of Regional Climate Change Simulations: An Exercise with the NARCCAP co-PIs for the Southwest Monsoon Region of North America." Bulletin of the American Meteorological Society 98, no. 1 (2017): 29–35. http://dx.doi.org/10.1175/bams-d-15-00019.1.

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Abstract In this brief article, we report the initial results of an expert elicitation with the co-PIs (regional climate modelers) of the North American Regional Climate Change Assessment Program regarding their evaluation of the relative quality of regional climate model simulations focusing on the subregion dominated by the North American monsoon (NAM). We assumed that an expert elicitation framework might reveal interesting beliefs and understanding that would be different from what would be obtained from calculating quantitative metrics associated with model quality. The simulations consid

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Zainuddin, Ahmad Nur Fikry, Nurul Ain Syuhadah Mohammad Khorri, Nurul Sa’aadah Sulaiman, and Fares Ahmed Alaw. "Elicitation of Conditional Probability Table (CPT) For Risk Analysis of Biomass Boiler in Energy Plant." Pertanika Journal of Science and Technology 30, no. 2 (2022): 1327–42. http://dx.doi.org/10.47836/pjst.30.2.26.

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The utilization of Empty fruit bunch (EFB) in energy production has increased in Malaysia over the last two decades. The EFB can be used as a solid fuel in a boiler system for heat and power generation. However, numerous safety and technical issues lead to a lower energy production rate. A holistic probabilistic risk analysis is developed using the Bayesian Belief Network (BBN) to reduce the risk in the boiler system. The Conditional Probability Table (CPT) indicates the influence strength between the parent node and child node in BBN. Due to scarcely available information on EFB boiler, elici

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Wang, Meng, Eric E. Smith, Nils Daniel Forkert, et al. "Integrating expert knowledge for dementia risk prediction in individuals with mild cognitive impairment (MCI): a study protocol." BMJ Open 11, no. 11 (2021): e051185. http://dx.doi.org/10.1136/bmjopen-2021-051185.

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IntroductionTo date, there is no broadly accepted dementia risk score for use in individuals with mild cognitive impairment (MCI), partly because there are few large datasets available for model development. When evidence is limited, the knowledge and experience of experts becomes more crucial for risk stratification and providing MCI patients with prognosis. Structured expert elicitation (SEE) includes formal methods to quantify experts’ beliefs and help experts to express their beliefs in a quantitative form, reducing biases in the process. This study proposes to (1) assess experts’ beliefs

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Pibouleau, Leslie, and Sylvie Chevret. "AN INTERNET-BASED METHOD TO ELICIT EXPERTS’ BELIEFS FOR BAYESIAN PRIORS: A CASE STUDY IN INTRACRANIAL STENT EVALUATION." International Journal of Technology Assessment in Health Care 30, no. 4 (2014): 446–53. http://dx.doi.org/10.1017/s0266462314000403.

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Rationale: Bayesian methods provide an interesting approach to assessing an implantable medical device (IMD) that has evolved through successive versions because they allow for explicit incorporation of prior knowledge into the analysis. However, the literature is sparse on the feasibility and reliability of elicitation in cases where expert beliefs are used to form priors.Objectives: To develop an Internet-based method for eliciting experts’ beliefs about the success rate of an intracranial stenting procedure and to assess their impact on the estimated benefit of the latest version.Study Desi

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Khodabakhshian, Ania, Fulvio Re Cecconi, and Enrique Lopez Droguett. "Probabilistic risk identification and assessment model for construction projects using elicitation based bayesian network." Journal of Information Technology in Construction 30 (March 7, 2025): 185–212. https://doi.org/10.36680/j.itcon.2025.009.

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While risks in construction projects have severe consequences on the project schedule, budget, quality, and safety, the realm of Risk Management (RM) falls short in terms of efficiency, productivity, and automation. Artificial Intelligence technologies, especially Machine Learning, can address these issues and utilize risk data effectively for informed decision-making. However, due to the infrequent and unstructured data registration in projects, deterministic RM approaches with a frequentist inference are inapplicable to such small databases and cannot represent the actual risk exposure accur

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Neyman, Eric, and Tim Roughgarden. "Strictly Proper Contract Functions Can Be Arbitrage-Free." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 5 (2022): 5150–55. http://dx.doi.org/10.1609/aaai.v36i5.20449.

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We consider mechanisms for truthfully eliciting probabilistic predictions from a group of experts. The standard approach --- using a proper scoring rule to separately reward each expert --- is not robust to collusion: experts may collude to misreport their beliefs in a way that guarantees them a larger total reward no matter the eventual outcome. It is a long-standing open question whether there is a truthful elicitation mechanism that makes any such collusion (also called "arbitrage") impossible. We resolve this question positively, exhibiting a class of strictly proper arbitrage-free contrac

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Carey, Niamh, Conor Hickey, Laura Mc Cullagh, and Michael Barry. "OP206 Expert Elicitation Of Probabilistic Distributions to Inform Survival Modelling of CD19 Chimeric Antigen Receptor T-Cell Therapies." International Journal of Technology Assessment in Health Care 36, S1 (2020): 3. http://dx.doi.org/10.1017/s0266462320000951.

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IntroductionIn 2018, the National Centre for Pharmacoeconomics (NCPE) was commissioned to conduct a health technology assessment (HTA) of one of the first commercially available chimeric antigen receptor (CAR) T-cell therapies, tisagenlecleucel. CAR T-cells are a major advance in personalized cancer treatment, demonstrating promising outcomes in relapsed/refractory pediatric acute lymphoblastic leukemia (pALL). However, the results are based on short-term follow up, limiting their value in predicting long-term survival and leading to uncertainty about the most appropriate survival modeling met

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Yusuf, Muhammad, Yusuf Latief, Ayomi Dita Rarasati, Bambang Trigunarsyah, and Naufal Budi Laksono. "Fuzzy Bayesian Belief Networks Method on Risk Assessment of EPC Pipeline Project." Civil Engineering Journal 11, no. 3 (2025): 1050–71. https://doi.org/10.28991/cej-2025-011-03-013.

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Subsea gas pipeline projects are experiencing significant technical and managerial challenges across Engineering, Procurement, and Construction (EPC) phases. To address the challenges, effective risk management in the early project phases is essential to mitigating cascading failures that cause significant schedule delay and cost overrun. Therefore, this study aimed to apply the Fuzzy Bayesian Belief Networks (FBBNs) method to model risk assessment during EPC phases. The findings showed that FBBNs made it possible for a new way to evaluate risks, find interdependencies, and guess what would ha

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Barrera-Causil, Carlos, Juan Correa, Andrew Zamecnik, Francisco Torres-Avilés, and Fernando Marmolejo-Ramos. "An FDA-Based Approach for Clustering Elicited Expert Knowledge." Stats 4, no. 1 (2021): 184–204. http://dx.doi.org/10.3390/stats4010014.

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Expert knowledge elicitation (EKE) aims at obtaining individual representations of experts’ beliefs and render them in the form of probability distributions or functions. In many cases the elicited distributions differ and the challenge in Bayesian inference is then to find ways to reconcile discrepant elicited prior distributions. This paper proposes the parallel analysis of clusters of prior distributions through a hierarchical method for clustering distributions and that can be readily extended to functional data. The proposed method consists of (i) transforming the infinite-dimensional pro

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Grimm, Sabine E., Simon Dixon, and John W. Stevens. "Assessing the Expected Value of Research Studies in Reducing Uncertainty and Improving Implementation Dynamics." Medical Decision Making 37, no. 5 (2017): 523–33. http://dx.doi.org/10.1177/0272989x16686766.

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Background. With low implementation of cost-effective health technologies being a problem in many health systems, it is worth considering the potential effects of research on implementation at the time of health technology assessment. Meaningful and realistic implementation estimates must be of dynamic nature. Objective. To extend existing methods for assessing the value of research studies in terms of both reduction of uncertainty and improvement in implementation by considering diffusion based on expert beliefs with and without further research conditional on the strength of evidence. Method

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JOHNSON, SINDHU R., JOHN T. GRANTON, GEORGE A. TOMLINSON, HADDAS A. GROSBEIN, GILLIAN A. HAWKER, and BRIAN M. FELDMAN. "Effect of Warfarin on Survival in Scleroderma-associated Pulmonary Arterial Hypertension (SSc-PAH) and Idiopathic PAH. Belief Elicitation for Bayesian Priors." Journal of Rheumatology 38, no. 3 (2010): 462–69. http://dx.doi.org/10.3899/jrheum.100632.

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Objective.Warfarin use in scleroderma (SSc)-associated pulmonary arterial hypertension (PAH) and idiopathic PAH (IPAH) is controversial. A prerequisite for a trial is the demonstration of community uncertainty. We evaluated experts’ beliefs about the effect of warfarin on 3-year survival in SSc-PAH and IPAH, and factors that influence warfarin use.Methods.PAH experts attending the 2008 American College of Rheumatology or American Thoracic Society meetings expressed the probability of 3-year survival without and with warfarin and their degree of uncertainty by applying adhesive dots, each repre

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Shin, Mi Kyung, and Hee Sue Kim. "A Study on the Development and Validity of the Sexual Orientation Beliefs Scale." Korean Association For Learner-Centered Curriculum And Instruction 23, no. 14 (2023): 565–84. http://dx.doi.org/10.22251/jlcci.2023.23.14.565.

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Objectives The purpose of this study is to develop and justify a multidimensional sexual-oriented belief scale for adults over the age of 20. Methods To this end, the construct concept of gender orientation was newly established and questions were prepared, and the validity was verified by conducting preliminary tests and main tests on 1,372 adults living in Seoul and other regions. Results Overall, it is a concept of gender-oriented beliefs that can not only confirm the level of one's beliefs based on one's gender orientation after gender identity, but can also be used for selective intervent

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Kinnersley, Nelson, and Simon Day. "Structured approach to the elicitation of expert beliefs for a Bayesian-designed clinical trial: a case study." Pharmaceutical Statistics 12, no. 2 (2013): 104–13. http://dx.doi.org/10.1002/pst.1552.

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Stefanini, Federico M. "Chain Graph Models to Elicit the Structure of a Bayesian Network." Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/749150.

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Bayesian networks are possibly the most successful graphical models to build decision support systems. Building the structure of large networks is still a challenging task, but Bayesian methods are particularly suited to exploit experts’ degree of belief in a quantitative way while learning the network structure from data. In this paper details are provided about how to build a prior distribution on the space of network structures by eliciting a chain graph model on structural reference features. Several structural features expected to be often useful during the elicitation are described. The

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Mario, Moroo, and Anindita Das. "Development of an Instrument Based on Salient Behavioral Beliefs to Measure Attitude towards Physical Education." Physical Education Theory and Methodology 22, no. 3s (2022): S102—S109. http://dx.doi.org/10.17309/tmfv.2022.3s.14.

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Study purpose. The study purpose was to develop an instrument to measure students’ attitude towards physical education through salient behavioral beliefs. Materials and methods. The participants of the study were both boys and girls of grades 7 to 10 from the state of Manipur (India) in the first, second and fourth phase. In the first phase, based on the recommendation of the theory of reasoned action and its extension, the theory of planned behavior, an elicitation study was conducted using open-ended questions, where a total of 308 student responses were collected. The student response

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Jousselme, Anne-Laure, Giuliana Pallotta, and John Locke. "Risk Game: Capturing impact of information quality on human belief assessment and decision making." International Journal of Serious Games 5, no. 4 (2018): 23–44. http://dx.doi.org/10.17083/ijsg.v5i4.258.

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This paper presents the Risk Game, a general methodology to elicit experts’ knowledge and know-how, in their ability to deal with information provided by different types of sources (sensors or humans) of variable quality, to take into account the information quality and to reason about concurrent events. It is a contrived technique capturing data expressing human reasoning features during a specific task of situation assessment. The information is abstracted by cards and its quality, which varies along the three dimensions of uncertainty, imprecision and falseness, is randomly selected by dice

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Schapira, Marilyn M., Keri L. Rodriguez, Sumedha Chhatre, et al. "When Is a Harm a Harm? Discordance between Patient and Medical Experts’ Evaluation of Lung Cancer Screening Attributes." Medical Decision Making 41, no. 3 (2021): 317–28. http://dx.doi.org/10.1177/0272989x20987221.

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Background A shared decision-making (SDM) process for lung cancer screening (LCS) includes a discussion between clinicians and patients about benefits and potential harms. Expert-driven taxonomies consider mortality reduction a benefit and consider false-positives, incidental findings, overdiagnosis, overtreatment, radiation exposure, and direct and indirect costs of LCS as potential harms. Objective To explore whether patients conceptualize the attributes of LCS differently from expert-driven taxonomies. Design Cross-sectional study with semistructured interviews and a card-sort activity. Par

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Chambers, Christopher P., and Nicolas S. Lambert. "Dynamic Belief Elicitation." Econometrica 89, no. 1 (2021): 375–414. http://dx.doi.org/10.3982/ecta15293.

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At an initial time, an individual forms a belief about a future random outcome. As time passes, the individual may obtain, privately or subjectively, further information, until the outcome is eventually revealed. How can a protocol be devised that induces the individual, as a strict best response, to reveal at the outset his prior assessment of both the final outcome and the information flows he anticipates and, subsequently, what information he privately receives? The protocol can provide the individual with payoffs that depend only on the outcome realization and his reports. We develop a fra

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Tsakas, Elias. "Obvious belief elicitation." Games and Economic Behavior 118 (November 2019): 374–81. http://dx.doi.org/10.1016/j.geb.2019.07.002.

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Knippen, Kerri Lynn, Natalie Walkup, Cameron Burmeister, Joseph Dake, and Kent Bishop. "Factors Associated with Breastfeeding Duration and Satisfaction after Gestational Diabetes among Women Living in Northwest Ohio." Ohio Journal of Public Health 3, no. 1 (2020): 9–18. http://dx.doi.org/10.18061/ojph.v3i1.9016.

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Background: Given the potential for type 2 diabetes and the protective benefits of breastfeeding after gestational diabetes mellitus (GDM), there is a need to promote and support breastfeeding; however, delayed lactogenesis and postpartum experiences may challenge breastfeeding success. We aimed to describe factors that influence breastfeeding duration and satisfaction after GDM.Methods: A cross-sectional survey, informed by an elicitation phase and subject matter expert review, was conducted to evaluate factors associated with breastfeeding satisfaction and duration after GDM. The study inclu

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O'Hagan, A. "Eliciting expert beliefs in substantial practical applications [Read before The Royal Statistical Society at ameeting on 'Elicitation' on Wednesday, april 16th, 1997, the President, Professor A. F. M. Smithin the Chair]." Journal of the Royal Statistical Society: Series D (The Statistician) 47, no. 1 (1998): 21–35. http://dx.doi.org/10.1111/1467-9884.00114.

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Burdea, Valeria, and Jonathan Woon. "Online belief elicitation methods." Journal of Economic Psychology 90 (June 2022): 102496. http://dx.doi.org/10.1016/j.joep.2022.102496.

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Falahee, Marie, Gwenda Simons, Rachael L. DiSantostefano, et al. "Treatment preferences for preventive interventions for rheumatoid arthritis: protocol of a mixed methods case study for the Innovative Medicines Initiative PREFER project." BMJ Open 11, no. 4 (2021): e045851. http://dx.doi.org/10.1136/bmjopen-2020-045851.

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IntroductionAmidst growing consensus that stakeholder decision-making during drug development should be informed by an understanding of patient preferences, the Innovative Medicines Initiative project ‘Patient Preferences in Benefit-Risk Assessments during the Drug Life Cycle’ (PREFER) is developing evidence-based recommendations about how and when patient preferences should be integrated into the drug life cycle. This protocol describes a PREFER clinical case study which compares two preference elicitation methodologies across several populations and provides information about benefit–risk tr

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Danz, David, Lise Vesterlund, and Alistair J. Wilson. "Belief Elicitation and Behavioral Incentive Compatibility." American Economic Review 112, no. 9 (2022): 2851–83. http://dx.doi.org/10.1257/aer.20201248.

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Subjective beliefs are crucial for economic inference, yet behavior can challenge the elicitation. We propose that belief elicitation should be incentive compatible not only theoretically but also in a de facto behavioral sense. To demonstrate, we show that the binarized scoring rule, a state-of-the-art elicitation, violates two weak conditions for behavioral incentive compatibility: (i) within the elicitation, information on the incentives increases deviations from truthful reporting; and (ii) in a pure choice over the set of incentives, most deviate from the theorized maximizer. Moreover, we

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Schotter, Andrew, and Isabel Trevino. "Belief Elicitation in the Laboratory." Annual Review of Economics 6, no. 1 (2014): 103–28. http://dx.doi.org/10.1146/annurev-economics-080213-040927.

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Chambers, Christopher P., and Nicolas S. Lambert. "Introduction to dynamic belief elicitation." ACM SIGecom Exchanges 14, no. 1 (2015): 80–83. http://dx.doi.org/10.1145/2845926.2845930.

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Middlestadt, Susan E. "Beliefs Underlying Eating Better and Moving More." ANNALS of the American Academy of Political and Social Science 640, no. 1 (2012): 81–100. http://dx.doi.org/10.1177/0002716211425015.

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The reasoned action approach has been used to identify the determinants of a behavior to be modified by social and behavioral interventions. Information on the specific beliefs underlying behavioral decisions is vital to intervention design. More attention is needed on the salient belief elicitation—a critical step in a theory-based formative research process. This article considers the methodological issues involved in conducting a salient belief elicitation with special attention to an elicitation that allows the comparison of results across several behaviors and priority groups. The author

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Eyting, Markus, and Patrick Schmidt. "Belief elicitation with multiple point predictions." European Economic Review 135 (June 2021): 103700. http://dx.doi.org/10.1016/j.euroecorev.2021.103700.

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Schlag, Karl, and James Tremewan. "Simple belief elicitation: An experimental evaluation." Journal of Risk and Uncertainty 62, no. 2 (2021): 137–55. http://dx.doi.org/10.1007/s11166-021-09349-6.

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Crosetto, Paolo, Antonio Filippin, Peter Katuščák, and John Smith. "Central tendency bias in belief elicitation." Journal of Economic Psychology 78 (June 2020): 102273. http://dx.doi.org/10.1016/j.joep.2020.102273.

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Bosetti, Valentina, Francis Dennig, Ning Liu, Massimo Tavoni, and Elke U. Weber. "Forward-Looking Belief Elicitation Enhances Intergenerational Beneficence." Environmental and Resource Economics 81, no. 4 (2022): 743–61. http://dx.doi.org/10.1007/s10640-022-00648-3.

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Mahmood, Yasir, Nof Yasir, Nita Yodo, Ying Huang, Di Wu, and Roy A. McCann. "Comprehensive Risk Assessment of Power Grids Using Fuzzy Bayesian Networks Through Expert Elicitation: A Technical Analysis." Algorithms 18, no. 6 (2025): 321. https://doi.org/10.3390/a18060321.

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Power grid infrastructures, essential to modern societies for electricity distribution, are prone to vulnerabilities due to their numerous sensitive components, necessitating a comprehensive risk assessment. Uncertainty in historical failure data often compromises accurate risk quantification, leading to the integration of expert elicitation as a solution. This study develops a Bayesian network (BN) risk assessment model integrated with fuzzy set theory (FST), referred to as the fuzzy Bayesian network (FBN). By incorporating expert insights, this model quantifies internal and external risk var

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O’Hagan, Anthony. "Expert Knowledge Elicitation: Subjective but Scientific." American Statistician 73, sup1 (2019): 69–81. http://dx.doi.org/10.1080/00031305.2018.1518265.

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van Wingerden, J. W., P. A. Fleming, T. Göçmen, et al. "Expert Elicitation on Wind Farm Control." Journal of Physics: Conference Series 1618 (September 2020): 022025. http://dx.doi.org/10.1088/1742-6596/1618/2/022025.

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Tregoning, Robert Lee, Lee Richard Abramson, Paul Michael Scott, and Nilesh Chokshi. "LOCA frequency evaluation using expert elicitation." Nuclear Engineering and Design 237, no. 12-13 (2007): 1429–36. http://dx.doi.org/10.1016/j.nucengdes.2006.09.036.

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Astfalck, L. C., E. J. Cripps, J. P. Gosling, M. R. Hodkiewicz, and I. A. Milne. "Expert elicitation of directional metocean parameters." Ocean Engineering 161 (August 2018): 268–76. http://dx.doi.org/10.1016/j.oceaneng.2018.04.047.

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Bedford, Tim, John Quigley, and Lesley Walls. "Expert Elicitation for Reliable System Design." Statistical Science 21, no. 4 (2006): 428–50. http://dx.doi.org/10.1214/088342306000000510.

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Albert, Isabelle, Sophie Donnet, Chantal Guihenneuc-Jouyaux, Samantha Low-Choy, Kerrie Mengersen, and Judith Rousseau. "Combining Expert Opinions in Prior Elicitation." Bayesian Analysis 7, no. 3 (2012): 503–32. http://dx.doi.org/10.1214/12-ba717.

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Ko, Li Ling, David Hsu, Wee Sun Lee, and Sylvie Ong. "Structured Parameter Elicitation." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (2010): 1102–7. http://dx.doi.org/10.1609/aaai.v24i1.7744.

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The behavior of a complex system often depends on parameters whose values are unknown in advance. To operate effectively, an autonomous agent must actively gather information on the parameter values while progressing towards its goal. We call this problem parameter elicitation. Partially observable Markov decision processes (POMDPs) provide a principled framework for such uncertainty planning tasks, but they suffer from high computational complexity. However, POMDPs for parameter elicitation often possess special structural properties, specifically, factorization and symmetry. This work identi

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Trautmann, Stefan T., and Gijs van de Kuilen. "Belief Elicitation: A Horse Race among Truth Serums." Economic Journal 125, no. 589 (2014): 2116–35. http://dx.doi.org/10.1111/ecoj.12160.

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