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.[2]

Melanie Mitchell
Born	United States
Alma mater	Brown University University of Michigan
Awards	Phi Beta Kappa Award in Science (2010)
Scientific career
Fields	Complex systems Genetic algorithms
Institutions	University of Michigan Santa Fe Institute Los Alamos National Laboratory OGI School of Science and Engineering Portland State University
Thesis	Copycat: A Computer Model of High-Level Perception and Conceptual Slippage in Analogy-Making (1990)
Doctoral advisor	Douglas Hofstadter and John Holland
Notes
Brother, Jonathan Mitchell[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[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).

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.[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]

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). 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.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.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.

References

1. Mitchell, Melanie (September 1, 2011). Complexity: A Guided Tour. Oxford University Press. pp. xvi. ISBN 0199798109. Retrieved November 6, 2018.
2. Google Scholar search for Melanie Mitchell
3. Mitchell, Melanie (October 4, 2002). "IS the Universe a Universal Computer?" (pdf). Science (www.sciencemag.org). pp. 65–68. Retrieved March 23, 2013.
4. "Fears about robot overlords are (perhaps) premature". Christian Science Monitor. October 25, 2019. Retrieved May 10, 2020.
5. "What Is Computer Vision?". PCMAG. February 9, 2020. Retrieved May 10, 2020.

External links

• Mitchell's professional homepage
• Melanie Mitchell publications indexed by Google Scholar