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.[1]
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[2] 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).
Views
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.[3] 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.[4]
Selected publications
Books
- 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.
Articles
- 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.
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: 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.
References
- ↑ Google Scholar search for Melanie Mitchell
- ↑ Mitchell, Melanie (October 4, 2002). "IS the Universe a Universal Computer?" (pdf). Science (www.sciencemag.org). pp. 65–68. Retrieved March 23, 2013.
- ↑ "Fears about robot overlords are (perhaps) premature". Christian Science Monitor. 25 October 2019. Retrieved 10 May 2020.
- ↑ "What Is Computer Vision?". PCMAG (in English). 9 February 2020. Retrieved 10 May 2020.
External links
- Mitchell's professional homepage
- 梅勒妮·米歇尔 Melanie Mitchell publications indexed by Google Scholar
- CS1 English-language sources (en)
- CS1 maint: multiple names: authors list
- AC with 0 elements
- Pages with red-linked authority control categories
- Cellular automatists
- Complex systems scientists
- Living people
- Portland State University faculty
- University of Michigan alumni
- Santa Fe Institute people
- Brown University alumni
- Los Alamos National Laboratory personnel
- Oregon Health & Science University faculty
- Year of birth missing (living people)
- Researchers of artificial life