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第1行： − {{Infobox academic − |image = − |caption = − |birth_date = 1942 − |birth_place = − |death_date = − |death_place = − |alma_mater = [[Indiana University (Bloomington)|Indiana University]] ({{midsize|Ph.D., 1969}}) − |workplaces = [[Carnegie Mellon University]] − }} − − + 第25行：
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第103行： − = = = 期刊文章 = = = =”发现的评估: 模型，模拟和通过”大数据”的搜索”，开放哲学，2019年。可用的在线(开放存取) : https://doi.org/10.1515/opphil-2019-0005 + − − * (与大卫 · 丹克斯合著)《贝叶斯认识论中的原因》 ，《哲学杂志》 ，2008年。 − * 《马尔可夫性质与量子实验》 ，w. Demopoulos and i. Pitowsky，eds。物理学理论及其解释: 纪念杰弗里 · 巴布的文章，斯普林格2006年。 − * (与 Chu，t. 和 David Danks 合著)“数据驱动的格兰杰因果关系和同时期的因果关系与非线性校正: 气候遥相关机制”，2004年。 − * 《回顾 Phil Dowe 和 Paul Nordhoff: 原因和机会: 不确定世界中的因果关系》 ，Mind，2005年。 − * (与埃伯哈特、弗雷德里克和理查德 · 谢因斯)。“ n-1实验足以确定 n 个变量之间的因果关系”，2004年。 − * (与 f. Eberhardt 和 r. Scheines 合作) ，“ Log2(n)实验是充分的，在最坏的情况下是必要的，以确定因果结构”，UAI Proceedings，2005 − * ，(与 Handley，Daniel，Nicoleta Serban，David Peters，Robert o’doherty，Melvin Field，Larry Wasserman，Peter Spirtes，和 Richard Scheines 合作) ，“ cDNA 微阵列上系统性的表达序列标签图像克隆交叉杂交的证据”，Vol。83，Issue 6(June，2004) ，1169-1175. − * (与 Handley、 Daniel、 Nicoleta Serban 和 David g. Peters 合作)。“关于由于交叉杂交和序列错误引起的斑点 cDNA 微阵列的不可靠数据的关注”，遗传学和分子生物学统计应用，卷。第三期第一期(二○○四年十月六日)第二十五条。 − * 《对 d. Lerner 的评论》 ，《有意识的错觉》 ，《行为与脑科学》 ，出版社。 − *”约瑟夫 · e · 厄利先生评论”。(教育署。《化学解释: 特征、发展、自主》 ，载《科学哲学》第卷。71，No.3(2004年7月) ，415-418。 − * (与 Spirtes 和 Peter Glymour 合作)。“因果推理”，社会科学百科全书，出版 − * “我们相信意志的自由，所以我们可以学习”，行为和脑科学，卷。27，No.5 (2004), 661-662. − * 《发现的自动化》 ，代达罗斯，第一卷。冬季(2004) ，69-77。 − * (与 Serban、 Nicoleta、 Larry Wasserman、 David Peters、 Peter Spirtes、 Robert o’doherty、 Dan Handley 和 Richard Scheines 合作)。“处理过的脂肪细胞的微阵列数据分析”，(2003)。 − * (与丹克斯、大卫和彼得 · 斯皮尔特斯合作)。“调控网络搜索的基因扰动的计算和实验复杂性”，(2003)。 − * (与席尔瓦、里卡多、理查德•谢因斯和彼得•斯皮尔特斯)。“未观测变量的学习测量模型”，UAI’03，第19届人工智能不确定性会议论文集，2003年8月7-10，Acapulco (2003) ，543-550。 − * (与丹克斯、大卫和彼得 · 斯皮尔特斯合作)。“调控网络搜索的基因扰动的计算和实验复杂性”，ijcai-2003计算基因组学习图形模型研讨会论文集，(2003) ，22-31。 − * (与弗兰克 · 温伯利、托马斯 · 海曼和约瑟夫 · 拉姆齐)。“从微阵列表达水平推断基因调控网络结构的算法准确性实验”，人工智能研讨会国际联席会议，2003年 − * “ Ceteris Paribus 的语义学和方法学”，Erkenntnis，Vol。57 (2002), 395-405. − * 《詹姆斯 · 伍德沃德评论，使事情发生: 因果解释理论》 ，《英国科学哲学杂志》 ，第一卷。55 (2004), 779-790. − * (与芬伯格、斯蒂芬和理查德 · 谢恩斯)。“专家统计证据和流行病学证据: 铅暴露对儿童的毒性影响”，《计量经济学杂志》 ，2003年第113卷，33-48页。 − *”学习、预测和因果贝叶斯网络”，《认知科学趋势》 ，第一卷。7，No.1 (2003), 43-47. − * (与艾莉森•高普尼克、大卫•索贝尔、劳拉• e •舒尔茨、塔玛•库什尼尔和大卫•丹克斯)。“儿童因果学习理论: 因果地图和贝叶斯网”，《心理学评论》 ，第卷。111，No.1 (2004). − * 《弗洛伊德、开普勒与临床证据》 ，载于 r. Wollheim 和 j. Hopkins 出版社编辑。弗洛伊德哲学论文集，剑桥大学出版社，1982。 − * 还有许多可以追溯到1970年的作品。 − + − + − + − + − + − − *IHMC website − *Carnegie Mellon Department of Philosophy faculty page − *TETRAD Project − − = = = 外部链接 = = − * IHMC 网站 − * 卡内基梅隆大学哲学系主页 − * 四维项目 第172行：
第126行： − − − Category:1942 births − Category:Living people − Category:American logicians − Category:Philosophers of science − Category:Indiana University alumni − Category:Florida Institute for Human and Machine Cognition people − Category:20th-century American philosophers − Category:Carnegie Mellon University faculty − Category:Place of birth missing (living people) − Category:Fellows of the American Academy of Arts and Sciences − − 类别: 1942年出生类别: 活人类别: 美国逻辑学家类别: 科学哲学家类别: 印第安纳大学校友类别: 佛罗里达人类与机器认知类别: 20世纪美国哲学家类别: 卡内基梅隆大学教员类别: 出生地缺失(活人)类别: 美国艺术与科学院院士 − − <noinclude> − − <small>This page was moved from [[wikipedia:en:Clark Glymour]]. Its edit history can be viewed at [[Clark Glymour/edithistory]]</small></noinclude>
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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>
'''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>
==Work==
==工作经历==
Glymour is the founder of the Philosophy Department at Carnegie Mellon University, a [[Guggenheim Fellowship|Guggenheim Fellow]], a Fellow of the Center for Advanced Study in Behavioral Sciences,<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> a [[Phi Beta Kappa Society|Phi Beta Kappa]] lecturer,<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> and is a Fellow of the statistics section of the AAAS.<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> Glymour and his collaborators created the causal interpretation of Bayes nets.<ref>P. Spirtes, C. Glymour, R. Scheines, Causation, Prediction and Search, Springer Lecture Notes in Statistics, 1993.</ref> His areas of interest include [[epistemology]]<ref>Epistemology: 5 Questions Edited by Vincent F. Hendricks and Duncan Pritchard, September 2008, {{ISBN|87-92130-07-0}}.</ref> (particularly [[Android epistemology]]), [[machine learning]], [[automated reasoning]], [[psychology]] of judgment, and [[mathematical psychology]].<ref>{{cite web|url=https://www.ihmc.us/groups/clark-glymour/|title=Clark Glymour|accessdate=December 16, 2019}}</ref> One of Glymour's main contributions to the philosophy of science is in the area of [[Bayesian probability]], particularly in his analysis of the Bayesian "problem of old evidence".<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> Glymour, in collaboration with Peter Spirtes and Richard Scheines, also developed an automated causal inference algorithm implemented as software named [[TETRAD]].<ref>[http://www.phil.cmu.edu/projects/tetrad/publications.html Publications] TETRAD. Retrieved December 16, 2019.</ref> Using multivariate statistical data as input, TETRAD rapidly searches from among all possible causal relationship models and returns the most plausible causal models based on conditional dependence relationships between those variables. The algorithm is based on principles from statistics, graph theory, philosophy of science, and artificial intelligence.<ref>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}}.</ref>
Glymour is the founder of the Philosophy Department at Carnegie Mellon University, a [[Guggenheim Fellowship|Guggenheim Fellow]], a Fellow of the Center for Advanced Study in Behavioral Sciences,<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> a [[Phi Beta Kappa Society|Phi Beta Kappa]] lecturer,<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> and is a Fellow of the statistics section of the AAAS.<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> Glymour and his collaborators created the causal interpretation of Bayes nets.<ref>P. Spirtes, C. Glymour, R. Scheines, Causation, Prediction and Search, Springer Lecture Notes in Statistics, 1993.</ref> His areas of interest include [[epistemology]]<ref>Epistemology: 5 Questions Edited by Vincent F. Hendricks and Duncan Pritchard, September 2008, {{ISBN|87-92130-07-0}}.</ref> (particularly [[Android epistemology]]), [[machine learning]], [[automated reasoning]], [[psychology]] of judgment, and [[mathematical psychology]].<ref>{{cite web|url=https://www.ihmc.us/groups/clark-glymour/|title=Clark Glymour|accessdate=December 16, 2019}}</ref> One of Glymour's main contributions to the philosophy of science is in the area of [[Bayesian probability]], particularly in his analysis of the Bayesian "problem of old evidence".<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> Glymour, in collaboration with Peter Spirtes and Richard Scheines, also developed an automated causal inference algorithm implemented as software named [[TETRAD]].<ref>[http://www.phil.cmu.edu/projects/tetrad/publications.html Publications] TETRAD. Retrieved December 16, 2019.</ref> Using multivariate statistical data as input, TETRAD rapidly searches from among all possible causal relationship models and returns the most plausible causal models based on conditional dependence relationships between those variables. The algorithm is based on principles from statistics, graph theory, philosophy of science, and artificial intelligence.<ref>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}}.</ref>
获得了化学和哲学的本科学位。他毕业于化学物理学，并于1969年获得印第安纳大学历史与科学哲学博士学位。
获得了化学和哲学的本科学位。他毕业于化学物理学，并于1969年获得印第安纳大学历史与科学哲学博士学位。
==Publications==
==研究成果(Publications)==
===Books===
===书籍===
*''Theory and Evidence'' (Princeton, 1980)
*''Theory and Evidence'' (Princeton, 1980)
*''Examining Holistic Medicine'' (with D. Stalker), Prometheus, 1985
*''Examining Holistic Medicine'' (with D. Stalker), Prometheus, 1985
* 伽利略，匹兹堡哈佛大学出版社，2010。
* 伽利略，匹兹堡哈佛大学出版社，2010。
===Journal articles===
===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
*"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 (journal)|Philosophy of Science]]'', 2008.
* "When is a Brain Like the Planet?", ''[[Philosophy of Science (journal)|Philosophy of Science]]'', 2008.
*and many others dating back to 1970.
*and many others dating back to 1970.
*
* “什么时候大脑像地球？科学哲学》 ，2008年。
==References==
==参考文献==
{{Reflist}}
{{Reflist}}
==External links==
==<nowiki>= = 外部链接 =</nowiki>==
*[https://www.ihmc.us/groups/clark-glymour/ IHMC website]
*IHMC 网站：[https://www.ihmc.us/groups/clark-glymour/ IHMC website]
*[https://web.archive.org/web/20100601161806/http://www.hss.cmu.edu/philosophy/faculty-glymour.php Carnegie Mellon Department of Philosophy faculty page]
*卡内基梅隆大学哲学系主页：[https://web.archive.org/web/20100601161806/http://www.hss.cmu.edu/philosophy/faculty-glymour.php Carnegie Mellon Department of Philosophy faculty page]
*[http://www.phil.cmu.edu/projects/tetrad/publications.html TETRAD Project]
*TETRAD项目：[http://www.phil.cmu.edu/projects/tetrad/publications.html TETRAD Project]
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{{Authority control}}
[[Category:Place of birth missing (living people)]]
[[Category:Place of birth missing (living people)]]
[[Category:Fellows of the American Academy of Arts and Sciences]]
[[Category:Fellows of the American Academy of Arts and Sciences]]
[[Category:待整理页面]]
[[Category:待整理页面]]