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'''克拉克 · 格莱莫尔'''（Clark N. Glymour）生于1942年，是卡内基梅隆大学哲学系的校友大学名誉教授。他也是佛罗里达人类和机器认知研究所（[[Florida Institute for Human and Machine Cognition]]）的高级研究科学家。<ref>{{cite web|url=https://www.cmu.edu/dietrich/philosophy/people/emeritus/glymour.html|title=Clark Glymour|publisher=Carnegie Mellon University|accessdate=December 16, 2019}}</ref>
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'''克拉克 · 格里默'''（Clark N. Glymour）生于1942年，是卡内基梅隆大学哲学系的校友大学名誉教授。他也是佛罗里达人类和机器认知研究所（[[Florida Institute for Human and Machine Cognition]]）的高级研究科学家。<ref>{{cite web|url=https://www.cmu.edu/dietrich/philosophy/people/emeritus/glymour.html|title=Clark Glymour|publisher=Carnegie Mellon University|accessdate=December 16, 2019}}</ref>
  
 
== 工作经历 ==
 
== 工作经历 ==
  
  
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格莱默是卡内基梅隆大学哲学系的创始人，古根海姆研究员（[[Guggenheim Fellowship|Guggenheim Fellow]]），行为科学高级研究中心研究员<ref>{{cite web|url=https://casbs.stanford.edu/news/awards-and-elections-fall-2019|title=Awards and Elections, Fall 2019|publisher=Center for Advanced Study in Behavioral Sciences|accessdate=December 16, 2019}}</ref>，[[Phi Beta Kappa Society|Phi Beta Kappa]]联谊会讲师<ref>{{cite web|url=https://www.pbk.org/Awards/Romanell/PastWinners|title=Romanell-Phi Beta Kappa Professorship Past Winners|publisher=Phi Beta Kappa|accessdate=December 16, 2019}}</ref>，美国科学促进会（AAAS）统计部门研究员<ref>{{cite web|url=https://www.amacad.org/person/clark-glymour|title=Clark Glymour|publisher=American Academy of Arts and Sciences|accessdate=December 16, 2019}}</ref>。格莱默和他的合作者创造了贝叶斯网络的因果解释<ref>P. Spirtes, C. Glymour, R. Scheines, Causation, Prediction and Search, Springer Lecture Notes in Statistics, 1993.</ref>。他的研究兴趣领域包括: 认识论（[[epistemology]]）<ref>Epistemology: 5 Questions Edited by Vincent F. Hendricks and Duncan Pritchard, September 2008, [[wikipedia:ISBN_(identifier)|ISBN]] [[wikipedia:Special:BookSources/87-92130-07-0|87-92130-07-0]]. </ref>(尤其是 Android 认识论（[[Android epistemology]]）)、机器学习（[[machine learning]],）、自动推理（[[automated reasoning]]）、判断心理学（[[psychology]] of judgment）和数学心理学（[[mathematical psychology]]）。<ref>{{cite web|url=https://www.ihmc.us/groups/clark-glymour/|title=Clark Glymour|accessdate=December 16, 2019}}</ref>格莱莫尔对科学哲学的主要贡献之一是在贝叶斯概率（[[Bayesian probability]]）领域，特别是在他对贝叶斯“旧证据问题”的分析中<ref>{{cite web|url=http://plato.stanford.edu/entries/epistemology-bayesian/|title=Bayesian Epistemology|date=July 12, 2001}}</ref><ref>Glymour, C.; Theory and evidence (1981), pp. 63-93.</ref>。格莱默与彼得 · 斯皮尔茨（Peter Spirtes）和理查德 · 谢恩斯（Richard Scheines）合作，还开发了一种自动因果推理算法，以软件形式实现，命名为[[TETRAD]]<ref>[http://www.phil.cmu.edu/projects/tetrad/publications.html Publications] TETRAD. Retrieved December 16, 2019.</ref>。采用多元统计数据作为输入，TETRAD 从所有可能的因果关系模型中快速搜索，并根据这些变量之间的条件依赖关系输出最合理的因果模型。该算法基于统计学、图论、科学哲学和人工智能的原理<ref>Glymour, Clark; Scheines, Richard; Spirtes, Peter; Kelly, Kevin. "TETRAD: Discovering Causal Structure" Multivariate Behavioral Research 23.2 (1988). 10 July 2010. doi:[https://doi.org/10.1207%2Fs15327906mbr2302_13 10.1207/s15327906mbr2302_13]. [[wikipedia:PMID_(identifier)|PMID]] [https://pubmed.ncbi.nlm.nih.gov/26764954 26764954].</ref>。
 
  
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格里默是卡内基梅隆大学哲学系的创始人，古根海姆研究员（[[Guggenheim Fellowship|Guggenheim Fellow]]），行为科学高级研究中心研究员<ref>{{cite web|url=https://casbs.stanford.edu/news/awards-and-elections-fall-2019|title=Awards and Elections, Fall 2019|publisher=Center for Advanced Study in Behavioral Sciences|accessdate=December 16, 2019}}</ref>，[[Phi Beta Kappa Society|Phi Beta Kappa]]联谊会讲师<ref>{{cite web|url=https://www.pbk.org/Awards/Romanell/PastWinners|title=Romanell-Phi Beta Kappa Professorship Past Winners|publisher=Phi Beta Kappa|accessdate=December 16, 2019}}</ref>，美国科学促进会（AAAS）统计部门研究员<ref>{{cite web|url=https://www.amacad.org/person/clark-glymour|title=Clark Glymour|publisher=American Academy of Arts and Sciences|accessdate=December 16, 2019}}</ref>。格里默和他的合作者创造了贝叶斯网络的因果解释<ref>P. Spirtes, C. Glymour, R. Scheines, Causation, Prediction and Search, Springer Lecture Notes in Statistics, 1993.</ref>。他的研究兴趣领域包括: 认识论（[[epistemology]]）<ref>Epistemology: 5 Questions Edited by Vincent F. Hendricks and Duncan Pritchard, September 2008, [[wikipedia:ISBN_(identifier)|ISBN]] [[wikipedia:Special:BookSources/87-92130-07-0|87-92130-07-0]]. </ref>(尤其是 Android 认识论（[[Android epistemology]]）)、机器学习（[[machine learning]],）、自动推理（[[automated reasoning]]）、判断心理学（[[psychology]] of judgment）和数学心理学（[[mathematical psychology]]）<ref>{{cite web|url=https://www.ihmc.us/groups/clark-glymour/|title=Clark Glymour|accessdate=December 16, 2019}}</ref>。格里默对科学哲学的主要贡献之一是在贝叶斯概率（[[Bayesian probability]]）领域，特别是在他对贝叶斯“旧证据问题”的分析中<ref>{{cite web|url=http://plato.stanford.edu/entries/epistemology-bayesian/|title=Bayesian Epistemology|date=July 12, 2001}}</ref><ref>Glymour, C.; Theory and evidence (1981), pp. 63-93.</ref>。格里默与彼得 · 斯皮尔茨（Peter Spirtes）和理查德 · 谢恩斯（Richard Scheines）合作，还开发了一种自动因果推理算法，以软件形式实现，命名为[[TETRAD]]<ref>[http://www.phil.cmu.edu/projects/tetrad/publications.html Publications] TETRAD. Retrieved December 16, 2019.</ref>。采用多元统计数据作为输入，TETRAD 从所有可能的因果关系模型中快速搜索，并根据这些变量之间的条件依赖关系输出最合理的因果模型。该算法基于统计学、图论、科学哲学和人工智能的原理<ref>Glymour, Clark; Scheines, Richard; Spirtes, Peter; Kelly, Kevin. "TETRAD: Discovering Causal Structure" Multivariate Behavioral Research 23.2 (1988). 10 July 2010. doi:[https://doi.org/10.1207%2Fs15327906mbr2302_13 10.1207/s15327906mbr2302_13]. [[wikipedia:PMID_(identifier)|PMID]] [https://pubmed.ncbi.nlm.nih.gov/26764954 26764954].</ref>。
  
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格莱默获得了化学（[[chemistry]]）和哲学（[[philosophy]]）的本科学位。他研究生工作专注于化学物理学（[[chemical physics]]），并于1969年获得印第安纳大学（ [[Indiana University (Bloomington)|Indiana University]]）历史与科学哲学博士学位。
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格里默获得了化学（[[chemistry]]）和哲学（[[philosophy]]）的本科学位。他研究生工作专注于化学物理学（[[chemical physics]]），并于1969年获得印第安纳大学（ [[Indiana University (Bloomington)|Indiana University]]）历史与科学哲学博士学位。
  
 
==发表的成果==
 
==发表的成果==

2022年3月20日 (日) 17:08的版本

克拉克 · 格里默（Clark N. Glymour）生于1942年，是卡内基梅隆大学哲学系的校友大学名誉教授。他也是佛罗里达人类和机器认知研究所（Florida Institute for Human and Machine Cognition）的高级研究科学家。[1]

工作经历

格里默是卡内基梅隆大学哲学系的创始人，古根海姆研究员（Guggenheim Fellow），行为科学高级研究中心研究员[2]，Phi Beta Kappa联谊会讲师[3]，美国科学促进会（AAAS）统计部门研究员[4]。格里默和他的合作者创造了贝叶斯网络的因果解释[5]。他的研究兴趣领域包括: 认识论（epistemology）[6](尤其是 Android 认识论（Android epistemology）)、机器学习（machine learning,）、自动推理（automated reasoning）、判断心理学（psychology of judgment）和数学心理学（mathematical psychology）[7]。格里默对科学哲学的主要贡献之一是在贝叶斯概率（Bayesian probability）领域，特别是在他对贝叶斯“旧证据问题”的分析中[8][9]。格里默与彼得 · 斯皮尔茨（Peter Spirtes）和理查德 · 谢恩斯（Richard Scheines）合作，还开发了一种自动因果推理算法，以软件形式实现，命名为TETRAD[10]。采用多元统计数据作为输入，TETRAD 从所有可能的因果关系模型中快速搜索，并根据这些变量之间的条件依赖关系输出最合理的因果模型。该算法基于统计学、图论、科学哲学和人工智能的原理[11]。


格里默获得了化学（chemistry）和哲学（philosophy）的本科学位。他研究生工作专注于化学物理学（chemical physics），并于1969年获得印第安纳大学（ Indiana University）历史与科学哲学博士学位。

发表的成果

书籍

  • Theory and Evidence (Princeton, 1980)
  • Examining Holistic Medicine (with D. Stalker), Prometheus, 1985
  • Foundations of Space-Time Theories (with J. Earman), University of Minnesota Press, 1986
  • Discovering Causal Structure (with R. Scheines, P. Spirtes and K.Kelly) Academic Press, 1987
  • Causation, Prediction and Search (with P.Spirtes and R. Scheines), Springer, 1993, 2nd Edition MIT Press, 2001
  • Thinking Things Through, MIT Press, 1994
  • Android Epistemology (with K. Ford and P. Hayes) MIT/AAAI Press, 1996
  • The Mind's Arrows: Bayes Nets and Graphical Causal Models in Psychology, MIT Press, 2001
  • Galileo in Pittsburgh Harvard University Press, 2010.
  • Theory and Evidence (Princeton, 1980)
  • Examining Holistic Medicine (with D. Stalker), Prometheus, 1985
  • Foundations of Space-Time Theories (with J. Earman), University of Minnesota Press, 1986
  • Discovering Causal Structure (with R. Scheines, P. Spirtes and K.Kelly) Academic Press, 1987
  • Causation, Prediction and Search (with P.Spirtes and R. Scheines), Springer, 1993, 2nd Edition MIT Press, 2001
  • Thinking Things Through, MIT Press, 1994
  • Android Epistemology (with K. Ford and P. Hayes) MIT/AAAI Press, 1996
  • The Mind's Arrows: Bayes Nets and Graphical Causal Models in Psychology, MIT Press, 2001
  • Galileo in Pittsburgh Harvard University Press, 2010.

期刊论文

  • "The Evaluation of Discovery: Models, Simulation and Search through “Big Data”", Open Philosophy, 2019. Available on-line (Open Access): https://doi.org/10.1515/opphil-2019-0005
  • "When is a Brain Like the Planet?", Philosophy of Science, 2008.
  • (with David Danks) "Reasons as Causes in Bayesian Epistemology", Journal of Philosophy, 2008.
  • "Markov Properties and Quantum Experiments", in W. Demopoulos and I. Pitowsky, eds. Physical Theory and Its Interpretation: Essays in Honor of Jeffrey Bub, Springer 2006.
  • (with Chu, T. and David Danks) "Data Driven Methods for Granger Causality and Contemporaneous Causality with Non-Linear Corrections: Climate Teleconnection Mechanisms", 2004.
  • "Review of Phil Dowe and Paul Nordhoff: Cause and Chance: Causation in an Indeterministic World", Mind, 2005.
  • (with Eberhardt, Frederick, and Richard Scheines). "N-1 Experiments Suffice to Determine the Causal Relations Among N Variables", 2004.
  • (with F. Eberhardt and R. Scheines), "Log2(N) Experiments are Sufficient, and in the Worst Case Necessary, for Identifying Causal Structure", UAI Proceedings, 2005
  • (with Handley, Daniel, Nicoleta Serban, David Peters, Robert O'Doherty, Melvin Field, Larry Wasserman, Peter Spirtes, and Richard Scheines), "Evidence of systematic expressed sequence tag IMAGE clone cross-hybridization on cDNA microarrays", Genomics, Vol. 83, Issue 6 (June, 2004), 1169-1175.
  • (with Handley, Daniel, Nicoleta Serban, and David G. Peters). "Concerns About Unreliable Data from Spotted cDNA Microarrays Due to Cross-Hybridization and Sequence Errors", Statistical Applications in Genetics and Molecular Biology, Vol. 3, Issue 1 (October 6, 2004), Article 25.
  • "Comment on D. Lerner", "The Illusion of Conscious Will", Behavioral and Brain Sciences, in press.
  • "Review of Joseph E. Early, Sr. (Ed.): Chemical Explanation: Characteristics, Development, Autonomy", Philosophy of Science, Vol. 71, No. 3 (July, 2004), 415-418.
  • (with Spirtes, and Peter Glymour). "Causal Inference", Encyclopedia of Social Science, in press
  • "We believe in freedom of the will so that we can learn", Behavioral and Brain Sciences, Vol. 27, No. 5 (2004), 661-662.
  • "The Automation of Discovery", Daedelus, Vol. Winter (2004), 69-77.
  • (with Serban, Nicoleta, Larry Wasserman, David Peters, Peter Spirtes, Robert O'Doherty, Dan Handley, and Richard Scheines). "Analysis of microarray data for treated fat cells", (2003).
  • (with Danks, David, and Peter Spirtes). "The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search", (2003).
  • (with Silva, Ricardo, Richard Scheines, and Peter Spirtes). "Learning Measurement Models for Unobserved Variables", UAI '03, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence, August 7–10, 2003, Acapulco, Mexico (2003), 543-550.
  • (with Danks, David and Peter Spirtes). "The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search", Proceedings of IJCAI-2003 Workshop on Learning Graphical Models for Computational Genomics, (2003), 22-31.
  • (with Frank Wimberly, Thomas Heiman, and Joseph Ramsey). "Experiments on the Accuracy of Algorithms for Inferring the Structure of Genetic Regulatory Networks from Microarray Expression Levels", International Joint Conference on Artificial Intelligence Workshop, 2003
  • "A Semantics and Methodology for Ceteris Paribus Hypotheses", Erkenntnis, Vol. 57 (2002), 395-405.
  • "Review of James Woodward, Making Things Happen: A Theory of Causal Explanation", British Journal for Philosophy of Science, Vol. 55 (2004), 779-790.
  • (with Fienberg, Stephen, and Richard Scheines). "Expert statistical testimony and epidemiological evidence: the toxic effects of lead exposure on children", Journal of Econometrics, Vol 113 (2003), 33-48.
  • "Learning, prediction and causal Bayes Nets", Trends in Cognitive Sciences, Vol. 7, No. 1 (2003), 43-47.
  • (with Alison Gopnik, David M. Sobel, Laura E. Schulz, Tamar Kushnir, and David Danks). "A theory of causal learning in children: Causal maps and Bayes nets", Psychological Review, Vol. 111, No. 1 (2004).
  • "Freud, Kepler, and the clinical evidence", in R. Wollheim and J. Hopkins, eds. Philosophical Essays on Freud, Cambridge University Press 1982.
  • and many others dating back to 1970.
  • "The Evaluation of Discovery: Models, Simulation and Search through “Big Data”", Open Philosophy, 2019. Available on-line (Open Access): https://doi.org/10.1515/opphil-2019-0005
  • "When is a Brain Like the Planet?", Philosophy of Science, 2008.
  • (with David Danks) "Reasons as Causes in Bayesian Epistemology", Journal of Philosophy, 2008.
  • "Markov Properties and Quantum Experiments", in W. Demopoulos and I. Pitowsky, eds. Physical Theory and Its Interpretation: Essays in Honor of Jeffrey Bub, Springer 2006.
  • (with Chu, T. and David Danks) "Data Driven Methods for Granger Causality and Contemporaneous Causality with Non-Linear Corrections: Climate Teleconnection Mechanisms", 2004.
  • "Review of Phil Dowe and Paul Nordhoff: Cause and Chance: Causation in an Indeterministic World", Mind, 2005.
  • (with Eberhardt, Frederick, and Richard Scheines). "N-1 Experiments Suffice to Determine the Causal Relations Among N Variables", 2004.
  • (with F. Eberhardt and R. Scheines), "Log2(N) Experiments are Sufficient, and in the Worst Case Necessary, for Identifying Causal Structure", UAI Proceedings, 2005
  • (with Handley, Daniel, Nicoleta Serban, David Peters, Robert O'Doherty, Melvin Field, Larry Wasserman, Peter Spirtes, and Richard Scheines), "Evidence of systematic expressed sequence tag IMAGE clone cross-hybridization on cDNA microarrays", Genomics, Vol. 83, Issue 6 (June, 2004), 1169-1175.
  • (with Handley, Daniel, Nicoleta Serban, and David G. Peters). "Concerns About Unreliable Data from Spotted cDNA Microarrays Due to Cross-Hybridization and Sequence Errors", Statistical Applications in Genetics and Molecular Biology, Vol. 3, Issue 1 (October 6, 2004), Article 25.
  • "Comment on D. Lerner", "The Illusion of Conscious Will", Behavioral and Brain Sciences, in press.
  • "Review of Joseph E. Early, Sr. (Ed.): Chemical Explanation: Characteristics, Development, Autonomy", Philosophy of Science, Vol. 71, No. 3 (July, 2004), 415-418.
  • (with Spirtes, and Peter Glymour). "Causal Inference", Encyclopedia of Social Science, in press
  • "We believe in freedom of the will so that we can learn", Behavioral and Brain Sciences, Vol. 27, No. 5 (2004), 661-662.
  • "The Automation of Discovery", Daedelus, Vol. Winter (2004), 69-77.
  • (with Serban, Nicoleta, Larry Wasserman, David Peters, Peter Spirtes, Robert O'Doherty, Dan Handley, and Richard Scheines). "Analysis of microarray data for treated fat cells", (2003).
  • (with Danks, David, and Peter Spirtes). "The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search", (2003).
  • (with Silva, Ricardo, Richard Scheines, and Peter Spirtes). "Learning Measurement Models for Unobserved Variables", UAI '03, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence, August 7–10, 2003, Acapulco, Mexico (2003), 543-550.
  • (with Danks, David and Peter Spirtes). "The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search", Proceedings of IJCAI-2003 Workshop on Learning Graphical Models for Computational Genomics, (2003), 22-31.
  • (with Frank Wimberly, Thomas Heiman, and Joseph Ramsey). "Experiments on the Accuracy of Algorithms for Inferring the Structure of Genetic Regulatory Networks from Microarray Expression Levels", International Joint Conference on Artificial Intelligence Workshop, 2003
  • "A Semantics and Methodology for Ceteris Paribus Hypotheses", Erkenntnis, Vol. 57 (2002), 395-405.
  • "Review of James Woodward, Making Things Happen: A Theory of Causal Explanation", British Journal for Philosophy of Science, Vol. 55 (2004), 779-790.
  • (with Fienberg, Stephen, and Richard Scheines). "Expert statistical testimony and epidemiological evidence: the toxic effects of lead exposure on children", Journal of Econometrics, Vol 113 (2003), 33-48.
  • "Learning, prediction and causal Bayes Nets", Trends in Cognitive Sciences, Vol. 7, No. 1 (2003), 43-47.
  • (with Alison Gopnik, David M. Sobel, Laura E. Schulz, Tamar Kushnir, and David Danks). "A theory of causal learning in children: Causal maps and Bayes nets", Psychological Review, Vol. 111, No. 1 (2004).
  • "Freud, Kepler, and the clinical evidence", in R. Wollheim and J. Hopkins, eds. Philosophical Essays on Freud, Cambridge University Press 1982.
  • and many others dating back to 1970.

参考文献

  1. ↑ "Clark Glymour". Carnegie Mellon University. Retrieved December 16, 2019.
  2. ↑ "Awards and Elections, Fall 2019". Center for Advanced Study in Behavioral Sciences. Retrieved December 16, 2019.
  3. ↑ "Romanell-Phi Beta Kappa Professorship Past Winners". Phi Beta Kappa. Retrieved December 16, 2019.
  4. ↑ "Clark Glymour". American Academy of Arts and Sciences. Retrieved December 16, 2019.
  5. ↑ P. Spirtes, C. Glymour, R. Scheines, Causation, Prediction and Search, Springer Lecture Notes in Statistics, 1993.
  6. ↑ Epistemology: 5 Questions Edited by Vincent F. Hendricks and Duncan Pritchard, September 2008, ISBN 87-92130-07-0.
  7. ↑ "Clark Glymour". Retrieved December 16, 2019.
  8. ↑ "Bayesian Epistemology". July 12, 2001.
  9. ↑ Glymour, C.; Theory and evidence (1981), pp. 63-93.
  10. ↑ Publications TETRAD. Retrieved December 16, 2019.
  11. ↑ Glymour, Clark; Scheines, Richard; Spirtes, Peter; Kelly, Kevin. "TETRAD: Discovering Causal Structure" Multivariate Behavioral Research 23.2 (1988). 10 July 2010. doi:10.1207/s15327906mbr2302_13. PMID 26764954.

外部链接

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