梅勒妮·米歇尔 Melanie Mitchell

Melanie Mitchell is a professor of computer science at Portland State University. She has worked at the Santa Fe Institute and Los Alamos National Laboratory. Her major work has been in the areas of analogical reasoning, complex systems, genetic algorithms and cellular automata, and her publications in those fields are frequently cited.

Melanie Mitchell is a professor of computer science at Portland State University. She has worked at the Santa Fe Institute and Los Alamos National Laboratory. Her major work has been in the areas of analogical reasoning, complex systems, genetic algorithms and cellular automata, and her publications in those fields are frequently cited.[2]

Melanie Mitchell 梅勒妮·米歇尔，是波特兰州立大学的计算机科学教授。她曾在圣菲研究所和洛斯阿拉莫斯国家实验室工作。她的主要工作是在类比推理，复杂系统，遗传算法和细胞自动机领域，她在这些领域的出版物经常被引用。[2]

She received her PhD in 1990 from the University of Michigan under Douglas Hofstadter and John Holland, for which she developed the Copycat cognitive architecture. She is the author of "Analogy-Making as Perception", essentially a book about Copycat. She has also critiqued Stephen Wolfram's A New Kind of Science and showed that genetic algorithms could find better solutions to the majority problem for one-dimensional cellular automata. She is the author of An Introduction to Genetic Algorithms, a widely known introductory book published by MIT Press in 1996. She is also author of Complexity: A Guided Tour (Oxford University Press, 2009), which won the 2010 Phi Beta Kappa Science Book Award, and Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux).

She received her PhD in 1990 from the University of Michigan under Douglas Hofstadter and John Holland, for which she developed the Copycat cognitive architecture. She is the author of "Analogy-Making as Perception", essentially a book about Copycat. She has also critiqued Stephen Wolfram's A New Kind of Science[3] and showed that genetic algorithms could find better solutions to the majority problem for one-dimensional cellular automata. She is the author of An Introduction to Genetic Algorithms, a widely known introductory book published by MIT Press in 1996. She is also author of Complexity: A Guided Tour (Oxford University Press, 2009), which won the 2010 Phi Beta Kappa Science Book Award, and Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux).

1990年，她在密歇根大学获得了博士学位，在侯世达和 John Holland 的指导下，她开发了模仿的认知结构。她是《作为感知的类比-做法》一书的作者，这本书本质上是关于模仿者的。她还批评了斯蒂芬 · 沃尔夫拉姆的《一种新的科学》 ，并指出遗传算法可以为一维细胞自动机的大多数问题找到更好的解决方案。她是《遗传算法导论》的作者，这是一本广为人知的介绍性书籍，由麻省理工学院出版社于1996年出版。她也是《复杂性: 导游》(牛津大学出版社，2009年)一书的作者，该书获得了2010年斐陶斐卡帕科学图书奖和《人工智能: 人类思考指南》(Farrar，Straus，和 Giroux 出版社)。

观点

While expressing strong support for AI research, Mitchell has expressed concern about AI's vulnerability to hacking as well as its ability to inherit social biases. On artificial general intelligence, Mitchell states that "commonsense knowledge" and "humanlike abilities for abstraction and analogy making" might constitute the final step required to build superintelligent machines, but that current technology is not close to being able to solve this problem. Mitchell believes that humanlike visual intelligence would require "general knowledge, abstraction, and language", and hypothesizes that visual understanding may have to be learned as an embodied agent rather than merely viewing pictures.

While expressing strong support for AI research, Mitchell has expressed concern about AI's vulnerability to hacking as well as its ability to inherit social biases. On artificial general intelligence, Mitchell states that "commonsense knowledge" and "humanlike abilities for abstraction and analogy making" might constitute the final step required to build superintelligent machines, but that current technology is not close to being able to solve this problem.[4] Mitchell believes that humanlike visual intelligence would require "general knowledge, abstraction, and language", and hypothesizes that visual understanding may have to be learned as an embodied agent rather than merely viewing pictures.[5]

虽然米切尔强烈支持人工智能的研究，但他也对人工智能在黑客攻击面前的脆弱性以及继承社会偏见的能力表示担忧。关于人工一般智能，米切尔指出，”常识性知识”和”抽象和类比的类人能力”可能是构建超级智能机器所需的最后一步，但目前的技术还不能解决这个问题。[4]米切尔认为类人的视觉智能需要“一般知识、抽象概念和语言” ，并假设视觉理解可能必须作为一种具体化的媒介来学习，而不仅仅是观看图片。[5]

=书籍

• Mitchell, Melanie (1993). Analogy-Making as Perception. ISBN 0-262-13289-3. 
• Mitchell, Melanie (1998). An Introduction to Genetic Algorithms. Cambridge, Massachusetts: MIT Press. ISBN 0-262-63185-7. 
• Mitchell, Melanie (2009). Complexity: A Guided Tour. Oxford, U.K.: Oxford University Press. ISBN 0-19-512441-3. 
• Mitchell, Melanie (October 15, 2019) (in English). Artificial Intelligence: A Guide for Thinking Humans (First ed.). Farrar, Straus and Giroux. ISBN 978-0374257835. 

文章

• Mitchell, M., Holland, J. H., and Forrest, S. (1994). "When will a genetic algorithm outperform hill climbing?". Advances in Neural Information Processing Systems. 6: 51–58.{{cite journal}}: CS1 maint: multiple names: authors list (link)
• Melanie Mitchell, Peter T. Hraber, and James P. Crutchfield (1993). "Revisiting the edge of chaos: Evolving cellular automata to perform computations" (PDF). Complex Systems. 7: 89–130.{{cite journal}}: CS1 maint: multiple names: authors list (link)
• Cowan, George; David Pines; David Elliott Meltzer (1999). Complexity : metaphors, models, and reality. Cambridge, Massachusetts: Perseus Books. pp. 731. ISBN 978-0738202327. https://archive.org/details/complexity00gcow. 

相关链接

• Mitchell's professional homepage
• 梅勒妮·米歇尔 Melanie Mitchell publications indexed by Google Scholar