Academic literature on the topic 'Elicitation of expert belief'
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Journal articles on the topic "Elicitation of expert belief"
RENOOIJ, SILJA. "Probability elicitation for belief networks: issues to consider." Knowledge Engineering Review 16, no. 3 (September 2001): 255–69. http://dx.doi.org/10.1017/s0269888901000145.
Full textPhillipson, Frank, Peter Langenkamp, and Reinder Wolthuis. "Alternative Initial Probability Tables for Elicitation of Bayesian Belief Networks." Mathematical and Computational Applications 26, no. 3 (July 28, 2021): 54. http://dx.doi.org/10.3390/mca26030054.
Full textCOUPÉ, 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 (September 2000): 215–32. http://dx.doi.org/10.1017/s0269888900003027.
Full textBojke, Laura, Marta Soares, Karl Claxton, Abigail Colson, Aimée Fox, Christopher Jackson, Dina Jankovic, Alec Morton, Linda Sharples, and Andrea Taylor. "Developing a reference protocol for structured expert elicitation in health-care decision-making: a mixed-methods study." Health Technology Assessment 25, no. 37 (June 2021): 1–124. http://dx.doi.org/10.3310/hta25370.
Full textKreinovich, Vladik. "INTERVAL METHODS IN KNOWLEDGE REPRESENTATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 04, no. 05 (October 1996): 467–90. http://dx.doi.org/10.1142/s0218488596000433.
Full textAnuar, 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 (December 18, 2020): 101. http://dx.doi.org/10.24191/ijmal.v4i4.11288.
Full textCarvalho, Arthur. "A Note on Sandroni-Shmaya Belief Elicitation Mechanism." Journal of Prediction Markets 10, no. 2 (January 27, 2017): 14–21. http://dx.doi.org/10.5750/jpm.v10i2.1225.
Full textBryant, Andrew, Michael Grayling, Shaun Hiu, Ketankumar Gajjar, Eugenie Johnson, Ahmed Elattar, Luke Vale, Dawn Craig, and Raj Naik. "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 (August 2022): e060183. http://dx.doi.org/10.1136/bmjopen-2021-060183.
Full textVijayan, 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 (February 3, 2020): 470–86. http://dx.doi.org/10.1177/1748006x19897828.
Full textSchlag, Karl H., and Joël J. van der Weele. "A method to elicit beliefs as most likely intervals." Judgment and Decision Making 10, no. 5 (September 2015): 456–68. http://dx.doi.org/10.1017/s1930297500005593.
Full textDissertations / Theses on the topic "Elicitation of expert belief"
Briggs, Rachael (Rachael Amy). "Partial belief and expert testimony." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/47829.
Full textIncludes bibliographical references (p. [83]-86).
My dissertation investigates two questions from within a partial belief framework: First, when and how should deference to experts or other information sources be qualified? Second, how closely is epistemology related to other philosophical fields, such as metaphysics, ethics, and decision theory? Chapter 1 discusses David Lewis's "Big Bad Bug", an argument for the conclusion that the Principal Principle-the thesis that one's credence in a proposition A should equal one's expectation of A's chance, provided one has no inadmissible information-is incompatible with Humean Supervenience-the thesis that that laws of nature, dispositions, and objective chances supervene on the distribution of categorical properties in the world (past, present, and future). I map out the logical structure of the Big Bad Bug, survey a range of possible responses to it, and argue that none of the responses are very appealing. Chapter 2 discusses Bas van Fraassen's Reflection principle-the thesis that one's current credence in a proposition A should equal one's expected future credence in A. Van Fraassen has formulated a diachronic Dutch book argument for Reflection, but other authors cite counterexamples to Reflection that appear to undermine the credibility of diachronic Dutch books. I argue that a suitably qualified version of Reflection gets around the counterexamples. I distinguish between Dutch books that reveal incoherence-like the diachronic Dutch book for conditionalization-and Dutch books that reveal a type of problem I call selfdoubt. I argue that violating Reflection is a type of self-doubt rather than a type of incoherence.
(cont.) Chapter 3 argues that the halfer and thirder solutions to Adam Elga's Sleeping Beauty problem correspond to two more general approaches to de se information. Which approach is right depends on which approach to decision theory is right. I use Dutch books and scoring rules to argue that causal decision theorists should favor the approach that corresponds to thirding, while evidential decision theorists should favor the approach that corresponds to halfing.
by Rachael Briggs.
Ph.D.
Selvidge, Jordan R. "Managing One-to-One Initiatives: Implementation Analysis Through Expert Elicitation." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3143.
Full textSchneider, Mark. "Studies in risk perception and financial literacy: applications using subjective belief elicitation." Doctoral thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/30349.
Full textWest, Daune. "Towards a subjective knowledge elicitation methodology for the development of expert systems." Thesis, University of Portsmouth, 1991. https://researchportal.port.ac.uk/portal/en/theses/towards-a-subjective-knowledge-elicitation-methodology-for-the-development-of-expert-systems(d63c460a-f71c-492d-9150-15c31becdb5b).html.
Full textAlkhairy, Ibrahim H. "Designing and Encoding Scenario-based Expert Elicitation for Large Conditional Probability Tables." Thesis, Griffith University, 2020. http://hdl.handle.net/10072/390794.
Full textThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Info & Comm Tech
Science, Environment, Engineering and Technology
Full Text
Akram, Muhammad Farooq. "A methodology for uncertainty quantification in quantitative technology valuation based on expert elicitation." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/47717.
Full textIamsumang, Chonlagarn. "A framework for nuclear facility safeguard evaluation using probabilistic methods and expert elicitation." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/76528.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (p. 99-100).
With the advancement of the next generation of nuclear fuel cycle facilities, concerns of the effectiveness of nuclear facility safeguards have been increasing due to the inclusion of highly enriched material and reprocessing capability into fuel cycles. Therefore, an extensive and quantitative safeguard evaluation is required in order for the decision makers to have a consistent measure to verify safeguards level of protection, and to effectively improve the current safeguard scheme. The framework presented in this study provides a systematic method for safeguard evaluation of any nuclear facility. Using scenario analysis approach, a diversion scenario consists of target material, target location, diversion technique, set of tactics to help elude the safeguards, and the amount of material diverted per attempt. The success tree methodology and expert elicitation is used to construct logical models and obtain the probabilities of basic events. Then proliferator diversion success probabilities can be derived from the model for all possible scenarios in a given facility. Using Rokkasho reprocessing facility as an example, diversion pathways, uncertainty, sensitivity, and importance measure analyses are shown. Results from the analyses can be used by the safeguarder to gauge the level of protection provided by the current safeguard scheme, and to identify the weak points for improvements. The safeguarder is able to further analyze the effectiveness of the safeguard scheme for different facility designs, and the cost effectiveness analysis will help the safeguarder allocate limited resources for maximum possible protection against a material diversion.
by Chonlagarn Iamsumang.
S.M.
Okoli, Justin. "Expert knowledge elicitation in the firefighting domain and the implications for training novices." Thesis, Middlesex University, 2016. http://eprints.mdx.ac.uk/22940/.
Full textBurge, Janet E. "Knowledge Elicitation for Design Task Sequencing Knowledge." Digital WPI, 1999. https://digitalcommons.wpi.edu/etd-theses/1062.
Full textZampa, Nicholas Joseph. "Structured Expert Judgment Elicitation of Use Error Probabilities for Drug Delivery Device Risk Assessment." Thesis, The George Washington University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10841440.
Full textIn the pharmaceutical industry, estimating the probability of occurrence for use errors and use-error-causes (here forth referred to as use error probabilities) when developing drug delivery devices is hindered by a lack of data, ultimately limiting the ability to conduct robust usability risk assessments. A lack of reliable data is the result of small sample sizes and challenges simulating actual use environments in simulated use studies, compromising the applicability of observed use error rates. Further, post-market surveillance databases and internal complaint databases are limited in their ability to provide reliable data for product development. Inadequate usability risk assessment hinders drug delivery device manufacturers' understanding of safety and efficacy risks. The current industry and regulatory paradigm with respect to use error probabilities is to de-emphasize them, focusing instead of assessing the severity of harms. However, de-emphasis of use error probabilities is not rooted in a belief that probability estimates inherently lack value. Rather, the status quo is based on the absence of suitable methodologies for estimating use error probabilities.
In instances in which data is lacking, engineers and scientist may turn to structured expert judgment elicitation methodologies, in which subjective expert opinions are quantified and aggregated in a scientific manner. This research is a case study in adapting and applying one particular structured expert judgment methodology, Cooke’s Classical model, to human factors experts for estimating use error probabilities for a drug delivery device. Results indicate that a performance-weighted linear pooling of expert judgments significantly outperforms any one expert and an equal-weighted linear pooling. Additionally, this research demonstrates that a performance-weighted linear pooling of expert judgments is statistically accurate, robust to the choice of experts, and robust to choice elicitation questions. Lastly, this research validates the good statistical accuracy of a performance-weighted linear pooling of experts on a new set of use error probabilities, indicating that good expert performance translates to use error probabilities estimates for different devices. Through structured expert judgment elicitation according to Cooke’s Classical model, this research demonstrates that it is possible to reinstall use error probability estimates, with quantified uncertainty, into usability risk assessments for drug delivery devices.
Books on the topic "Elicitation of expert belief"
D, Diaper, ed. Knowledge elicitation: Principles, techniques, and applications. Chichester: E. Horwood, 1989.
Find full textAyyub, Bilal M. Elicitation of expert opinions for uncertainty and risks. Boca Raton, Fla: CRC Press, 2001.
Find full textKornfeld, Ari. Belief-network expert systems. Menlo Park, CA: SRI International, 1990.
Find full textDave, Hellens, ed. Knowledge elicitation: A practical handbook. New York: Prentice Hall, 1991.
Find full textSwackhamer, Deborah Liebl, and James K. Hammit. Review of EPA's Draft expert elicitation task force white paper. Washington, D.C: U.S. Environmental Protection Agency, Office of the Administrator, Science Advisory Board, 2010.
Find full textPeter, Gärdenfors, ed. Belief revision. Cambridge: Cambridge University Press, 1992.
Find full textGrdenfors, Peter. Belief Revision. Cambridge: Cambridge University Press, 1992.
Find full textWest, Daune. Towards a subjective knowledge elicitation methodology for the development of expert systems. Portsmouth: Portsmouth Polytechnic, School of Information Science, 1991.
Find full textJ, Bonano E., U.S. Nuclear Regulatory Commission. Division of High-Level Waste Management., Sandia National Laboratories, and Sandia Corporation, eds. Elicitation and use of expert judgement in performance assessment for high-level radioactive waste repositories. Washington, DC: Division of High-Level Waste Management, Office of Nuclear Material Safety and Safeguards, U.S. Nuclear Regulatory Commission, 1990.
Find full textUnited States. Congress. Office of Technology Assessment. and Decision Science Consortium Inc, eds. Personalized decision analysis as an expert elicitation tool: An instructive experience in information security policy. [Washington, D.C.?]: The Office, 1985.
Find full textBook chapters on the topic "Elicitation of expert belief"
Hoang, Tuan Nha, Tien Tuan Dao, and Marie-Christine Ho Ba Tho. "A Method for Uncertainty Elicitation of Experts Using Belief Function." In Modern Approaches for Intelligent Information and Database Systems, 39–49. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76081-0_4.
Full textSoares, Marta O., and Laura Bojke. "Expert Elicitation to Inform Health Technology Assessment." In Elicitation, 479–94. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65052-4_18.
Full textBolger, Fergus. "The Selection of Experts for (Probabilistic) Expert Knowledge Elicitation." In Elicitation, 393–443. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65052-4_16.
Full textGottschalk, Petter, and Lars Gunnesdal. "Expert Elicitation for Estimation." In White-Collar Crime in the Shadow Economy, 37–48. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75292-1_4.
Full textMerrick, Jason R. W., and Laura A. Albert. "Expert Judgment Based Nuclear Threat Assessment for Vessels Arriving in the US." In Elicitation, 495–509. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65052-4_19.
Full textWerner, Christoph, Anca M. Hanea, and Oswaldo Morales-Nápoles. "Eliciting Multivariate Uncertainty from Experts: Considerations and Approaches Along the Expert Judgement Process." In Elicitation, 171–210. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65052-4_8.
Full textLeplat, Jacques. "The Elicitation of Expert Knowledge." In NATO ASI Series, 107–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-50329-0_7.
Full textDean, Geoff. "Research Project: Expert Elicitation Study." In Neurocognitive Risk Assessment for the Early Detection of Violent Extremists, 61–94. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06719-3_4.
Full textYoe, Charles. "Characterizing Uncertainty through Expert Elicitation." In Principles of Risk Analysis, 511–38. Second edition. | Boca Raton : Taylor and Francis, CRC Press, 2019.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429021121-14.
Full textSagheb-Tehrani, Mehdi. "Knowledge Elicitation: Towards its Transparency." In Database and Expert Systems Applications, 548. Vienna: Springer Vienna, 1992. http://dx.doi.org/10.1007/978-3-7091-7557-6_96.
Full textConference papers on the topic "Elicitation of expert belief"
Profir, Bogdan, Murat Hakki Eres, James Scanlan, Michael Moss, and Ron Bates. "Uncertainty Quantification via Elicitation of Expert Judgements." In 16th AIAA Aviation Technology, Integration, and Operations Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-3459.
Full text"Pragmatic Expert Elicitation for Defence Capability Analysis." In 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2017. http://dx.doi.org/10.36334/modsim.2017.d1.donohoo.
Full textAyyub, Bilal M. "Uncertainties in Expert-Opinion Elicitation for Risk Studies." In Ninth United Engineering Foundation Conference on Risk-Based Decisionmaking in Water Resources. Reston, VA: American Society of Civil Engineers, 2001. http://dx.doi.org/10.1061/40577(306)10.
Full textSoare, Marta, Muhammad Ammad-Ud-Din, and Samuel Kaski. "Regression with n→1 by Expert Knowledge Elicitation." In 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2016. http://dx.doi.org/10.1109/icmla.2016.0131.
Full textBauby, C. E., P. Haik, E. Remy, B. Ricard, and F. Billy. "Asset Management Evaluation: The Key Role of Expert Elicitation." In ASME 2006 Pressure Vessels and Piping/ICPVT-11 Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/pvp2006-icpvt-11-93237.
Full textAkram, Farooq, and Dimitri Mavris. "Uncertainty Propagation in Technology Valuation Based on Expert Elicitation." In 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2012. http://dx.doi.org/10.2514/6.2012-882.
Full textScott, Paul M., Robert Lee Tregoning, and Lee Richard Abramson. "Revised LOCA Frequency Estimates From an Expert Elicitation Process." In ASME 2008 Pressure Vessels and Piping Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/pvp2008-61562.
Full textKoonchanok, Ratanond, Parul Baser, Abhinav Sikharam, Nirmal Kumar Raveendranath, and Khairi Reda. "Data Prophecy: Exploring the Effects of Belief Elicitation in Visual Analytics." In CHI '21: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3411764.3445798.
Full textWang, Shijie, and Marco Valtorta. "A prototype belief network-based expert systems shell." In the third international conference. New York, New York, USA: ACM Press, 1990. http://dx.doi.org/10.1145/98784.98877.
Full textSingleton, Joseph, and Richard Booth. "Who’s the Expert? On Multi-source Belief Change." In 19th International Conference on Principles of Knowledge Representation and Reasoning {KR-2022}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/kr.2022/33.
Full textReports on the topic "Elicitation of expert belief"
Danz, David, Lise Vesterlund, and Alistair Wilson. Belief Elicitation: Limiting Truth Telling with Information on Incentives. Cambridge, MA: National Bureau of Economic Research, June 2020. http://dx.doi.org/10.3386/w27327.
Full textCoppersmith, K. J. Unsaturated Zone Flow Model Expert Elicitation Project. Office of Scientific and Technical Information (OSTI), May 1997. http://dx.doi.org/10.2172/762969.
Full textBaca, Elena, Ritu Treisa Philip, David Greene, and Hoyt Battey. Expert Elicitation for Wave Energy LCOE Futures. Office of Scientific and Technical Information (OSTI), August 2022. http://dx.doi.org/10.2172/1885577.
Full textCoppersmith, Kevin J., and Roseanne C. Perman. Saturated Zone Flow and Transport Expert Elicitation Project. Office of Scientific and Technical Information (OSTI), January 1998. http://dx.doi.org/10.2172/763124.
Full textEngel, David W., and Angela C. Dalton. CCSI Risk Estimation: An Application of Expert Elicitation. Office of Scientific and Technical Information (OSTI), October 2012. http://dx.doi.org/10.2172/1064598.
Full textRonald L. Boring, David Gertman, Jeffrey Joe, Julie Marble, William Galyean, Larry Blackwood, and Harold Blackman. Simplified Expert Elicitation Procedure for Risk Assessment of Operating Events. Office of Scientific and Technical Information (OSTI), June 2005. http://dx.doi.org/10.2172/911228.
Full textBratzel, D. R. Flammable gas project expert elicitation results for Hanford Site double-shell tanks. Office of Scientific and Technical Information (OSTI), July 1998. http://dx.doi.org/10.2172/348862.
Full textK.J. Coppersmith, R.C. Perman, and R.R. Youngs. Lessons Learned- The Use of Formal Expert Elicitation in Probablistic Seismic Hazard. Office of Scientific and Technical Information (OSTI), May 2006. http://dx.doi.org/10.2172/893709.
Full textBratzel, D. R. Flammable gas double shell tank expert elicitation presentations (Part A and Part B). Office of Scientific and Technical Information (OSTI), April 1998. http://dx.doi.org/10.2172/10148313.
Full textFarmer, J. C. ,LLNL. Waste package degradation expert elicitation panel: input on corrosion of CRM alloy C-22. Office of Scientific and Technical Information (OSTI), March 1998. http://dx.doi.org/10.2172/289846.
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