Planning for success: The interdisciplinary approach to building Bayesian models

Alex Dekhtyar; Judy Goldsmith; Beth Goldstein; Krol Kevin Mathias; Cynthia Isenhour

doi:10.1016/j.ijar.2008.05.005

Planning for success: The interdisciplinary approach to building Bayesian models

Alex Dekhtyar
, Judy Goldsmith
, Beth Goldstein
, Krol Kevin Mathias
, Cynthia Isenhour

Producción científica: Article › revisión exhaustiva

5 Citas (Scopus)

Resumen

This paper describes a process by which anthropologists, computer scientists, and social welfare case managers collaborated to build a stochastic model of welfare advising in Kentucky. In the process of collaboration, the research team rethought the Bayesian network model of Markov decision processes and designed a new knowledge elicitation format. We expect that this model will have wide applicability in other domains.

Idioma original	English
Páginas (desde-hasta)	416-428
Número de páginas	13
Publicación	International Journal of Approximate Reasoning
Volumen	50
N.º	3
DOI	https://doi.org/10.1016/j.ijar.2008.05.005
Estado	Published - mar 2009

Nota bibliográfica

Funding Information:
This work was partly supported by NSF Grant ITR-0325063. The opinions expressed here are those of the authors and do not represent the Foundation, the University, or any social welfare offices. We thank Russell Almond for enabling communication between the computer scientists and social scientists about bowties, and we thank Joan Mazur for her work on the design of the HLE interface and her discussions of SCOT theory with several of the coauthors.

Financiación

This work was partly supported by NSF Grant ITR-0325063. The opinions expressed here are those of the authors and do not represent the Foundation, the University, or any social welfare offices. We thank Russell Almond for enabling communication between the computer scientists and social scientists about bowties, and we thank Joan Mazur for her work on the design of the HLE interface and her discussions of SCOT theory with several of the coauthors.

Financiadores	Número del financiador
U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China	ITR-0325063

ASJC Scopus subject areas

Software
Theoretical Computer Science
Applied Mathematics
Artificial Intelligence

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title = "Planning for success: The interdisciplinary approach to building Bayesian models",

abstract = "This paper describes a process by which anthropologists, computer scientists, and social welfare case managers collaborated to build a stochastic model of welfare advising in Kentucky. In the process of collaboration, the research team rethought the Bayesian network model of Markov decision processes and designed a new knowledge elicitation format. We expect that this model will have wide applicability in other domains.",

keywords = "Bayesian networks, Human-centered design, Knowledge elicitation, Planning, Social construction of technology",

author = "Alex Dekhtyar and Judy Goldsmith and Beth Goldstein and Mathias, \{Krol Kevin\} and Cynthia Isenhour",

note = "Funding Information: This work was partly supported by NSF Grant ITR-0325063. The opinions expressed here are those of the authors and do not represent the Foundation, the University, or any social welfare offices. We thank Russell Almond for enabling communication between the computer scientists and social scientists about bowties, and we thank Joan Mazur for her work on the design of the HLE interface and her discussions of SCOT theory with several of the coauthors.",

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AU - Goldsmith, Judy

AU - Goldstein, Beth

AU - Mathias, Krol Kevin

AU - Isenhour, Cynthia

N1 - Funding Information: This work was partly supported by NSF Grant ITR-0325063. The opinions expressed here are those of the authors and do not represent the Foundation, the University, or any social welfare offices. We thank Russell Almond for enabling communication between the computer scientists and social scientists about bowties, and we thank Joan Mazur for her work on the design of the HLE interface and her discussions of SCOT theory with several of the coauthors.

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N2 - This paper describes a process by which anthropologists, computer scientists, and social welfare case managers collaborated to build a stochastic model of welfare advising in Kentucky. In the process of collaboration, the research team rethought the Bayesian network model of Markov decision processes and designed a new knowledge elicitation format. We expect that this model will have wide applicability in other domains.

AB - This paper describes a process by which anthropologists, computer scientists, and social welfare case managers collaborated to build a stochastic model of welfare advising in Kentucky. In the process of collaboration, the research team rethought the Bayesian network model of Markov decision processes and designed a new knowledge elicitation format. We expect that this model will have wide applicability in other domains.

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KW - Knowledge elicitation

KW - Planning

KW - Social construction of technology

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SP - 416

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JO - International Journal of Approximate Reasoning

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IS - 3

ER -

Planning for success: The interdisciplinary approach to building Bayesian models

Resumen

Nota bibliográfica

Financiación

ASJC Scopus subject areas

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