David A. McAllester: Difference between revisions
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| field = [[Computer Science]], [[Artificial Intelligence]] |
| field = [[Computer Science]], [[Artificial Intelligence]], [[Machine Learning]] |
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| work_institutions = [[Toyota Technological Institute at Chicago]] |
| work_institutions = [[Toyota Technological Institute at Chicago]] |
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| alma_mater = [[Massachusetts Institute of Technology|MIT]] |
| alma_mater = [[Massachusetts Institute of Technology|MIT]] |
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''This article is about the computer scientist, David A. McAllester. For the ethnomusicologist, see [[David P. McAllester]]'' |
''This article is about the computer scientist, David A. McAllester. For the ethnomusicologist, see [[David P. McAllester]]'' |
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Professor '''David A. McAllester''' (born 1956) received his B.S., M.S., and Ph.D. degrees from the [[Massachusetts Institute of Technology]] in 1978, 1979, and 1987 respectively. His PhD was supervised by [[Gerald Sussman]]. He served on the faculty of Cornell University for the academic year of 1987-1988 and |
Professor '''David A. McAllester''' (born 1956) received his B.S., M.S., and Ph.D. degrees from the [[Massachusetts Institute of Technology]] in 1978, 1979, and 1987 respectively. His PhD was supervised by [[Gerald Sussman]]. He served on the faculty of Cornell University for the academic year of 1987-1988 and on on the faculty of MIT from 1988 to 1995. He was a member of technical staff at [[AT&T Labs|AT&T Labs-Research]] from 1995 to 2002. He has been a fellow of the [[American Association of Artificial Intelligence]] since 1997.<ref>{{cite web |url=http://ttic.uchicago.edu/~dmcallester/bio.html |title=David McAllester bio |website=Toyota Technological Institute at Chicago|access-date=19 August 2016}}</ref> He has authored over 100 refereed publications. |
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Professor McAllester's research areas include machine learning theory, the theory of programming languages, automated reasoning, AI planning, computer game playing (computer chess), and computational linguistics. A 1991 paper on AI planning<ref>{{cite journal |last=McAllester |first=David |last2=Rosenblitt |first2=David |date=December 1991 |title=Systematic Nonlinear Planning |url=http://www.aaai.org/Papers/AAAI/1991/AAAI91-099.pdf |journal=Proceedings AAAI-91|publisher=[[AAAI]] |pages=634–639 |doi= |access-date=19 August 2016}}</ref> proved to be one of the most influential papers of the decade in that area.<ref>{{cite web |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=nbpafUkAAAAJ&citation_for_view=nbpafUkAAAAJ:u5HHmVD_uO8C |title=Google Scholar Citations |last1= |first1= |last2= |first2= |date=2016 |website=[[Google Scholar]] |publisher= |access-date=19 August 2016 |quote=}}</ref> A 1993 paper on computer game algorithms<ref>{{cite journal |last=McAllester |first=David |last2=Yuret |first2=Deniz |date=20 October 1993 |title=Alpha-Beta-Conspiracy Search|url=http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.44.6969&rep=rep1&type=pdf |volume=Draft|access-date=19 August 2016}}</ref> influenced the design of the algorithms used in the [[Deep Blue (chess computer)|Deep Blue]] system that defeated [[Garry Kasparov]].<ref>{{cite journal |last=Campbell |first=Murray S. |last2=Joseph Hoane, Jr. |first2=A. |last3=Hsu |first3=Feng-hsiung|date=1999 |title=Search Control Methods in Deep Blue |url=http://aaaipress.org/Papers/Symposia/Spring/1999/SS-99-07/SS99-07-004.pdf |journal=AAAI Technical Report SS-99-07 |publisher=[[AAAI]] |volume= |issue= |pages=19–23 |doi= |access-date=16 August 2016|quote="To the best of our knowledge, the idea of separating the white and black depth computation was first suggested by David McAllester. A later paper (McAllester and Yuret 1993) derived an algorithm, ABC, from conspiracy theory (McAllester 1988)."}}</ref> A 1998 paper on machine learning theory<ref>{{cite journal |last=McAllester |first=David |date=1998 |title=Some PAC-Bayesian theorems |url=http://dl.acm.org/citation.cfm?id=279989 |journal=Proceedings of the eleventh annual conference on Computational learning theory|publisher=[[Association for Computing Machinery]] |pages=230–234 |doi=10.1145/279943.279989 |access-date=19 August 2016}}</ref> introduced PAC-Bayesian theorems which combine Bayesian and non-Bayesian methods. His plans for future research are focused on the integration of semantics into statistical approaches to computational linguistics. |
Professor McAllester's research areas include machine learning theory, the theory of programming languages, automated reasoning, AI planning, computer game playing (computer chess), and computational linguistics. A 1991 paper on AI planning<ref>{{cite journal |last=McAllester |first=David |last2=Rosenblitt |first2=David |date=December 1991 |title=Systematic Nonlinear Planning |url=http://www.aaai.org/Papers/AAAI/1991/AAAI91-099.pdf |journal=Proceedings AAAI-91|publisher=[[AAAI]] |pages=634–639 |doi= |access-date=19 August 2016}}</ref> proved to be one of the most influential papers of the decade in that area.<ref>{{cite web |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=nbpafUkAAAAJ&citation_for_view=nbpafUkAAAAJ:u5HHmVD_uO8C |title=Google Scholar Citations |last1= |first1= |last2= |first2= |date=2016 |website=[[Google Scholar]] |publisher= |access-date=19 August 2016 |quote=}}</ref> A 1993 paper on computer game algorithms<ref>{{cite journal |last=McAllester |first=David |last2=Yuret |first2=Deniz |date=20 October 1993 |title=Alpha-Beta-Conspiracy Search|url=http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.44.6969&rep=rep1&type=pdf |volume=Draft|access-date=19 August 2016}}</ref> influenced the design of the algorithms used in the [[Deep Blue (chess computer)|Deep Blue]] system that defeated [[Garry Kasparov]].<ref>{{cite journal |last=Campbell |first=Murray S. |last2=Joseph Hoane, Jr. |first2=A. |last3=Hsu |first3=Feng-hsiung|date=1999 |title=Search Control Methods in Deep Blue |url=http://aaaipress.org/Papers/Symposia/Spring/1999/SS-99-07/SS99-07-004.pdf |journal=AAAI Technical Report SS-99-07 |publisher=[[AAAI]] |volume= |issue= |pages=19–23 |doi= |access-date=16 August 2016|quote="To the best of our knowledge, the idea of separating the white and black depth computation was first suggested by David McAllester. A later paper (McAllester and Yuret 1993) derived an algorithm, ABC, from conspiracy theory (McAllester 1988)."}}</ref> A 1998 paper on machine learning theory<ref>{{cite journal |last=McAllester |first=David |date=1998 |title=Some PAC-Bayesian theorems |url=http://dl.acm.org/citation.cfm?id=279989 |journal=Proceedings of the eleventh annual conference on Computational learning theory|publisher=[[Association for Computing Machinery]] |pages=230–234 |doi=10.1145/279943.279989 |access-date=19 August 2016}}</ref> introduced PAC-Bayesian theorems which combine Bayesian and non-Bayesian methods. His plans for future research are focused on the integration of semantics into statistical approaches to computational linguistics. |
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McAllester is currently a professor and chief academic officer at the [[Toyota Technological Institute at Chicago]], an accredited research institute closely affiliated with the University of Chicago.<ref>{{cite web |url=http://www.ttic.edu/faculty.php |title=TTIC faculty|website=Toyota Technological Institute at Chicago|date=2016|access-date=19 August 2016}}</ref> |
McAllester is currently a professor and chief academic officer at the [[Toyota Technological Institute at Chicago]], an accredited research institute closely affiliated with the University of Chicago.<ref>{{cite web |url=http://www.ttic.edu/faculty.php |title=TTIC faculty|website=Toyota Technological Institute at Chicago|date=2016|access-date=19 August 2016}}</ref> |
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==Opinons on Artifical Intelligence== |
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McAllester has voiced concerns about the [[Existential risk from advanced artificial intelligence|potential dangers]] of [[Artificial Intelligence|artificial intelligence]], stating in an article to the [[Pittsburgh Tribune-Review]] that it is inevitable that fully automated intelligent machines will be able to design and build smarter, better versions of themselves, an event known as the [[Technological singularity|Singularity]]. The Singularity would enable machines to become infinitely intelligent, and would pose an "incredibly dangerous scenario". McAllester estimates a 10 percent probability of the Singularity occurring within 25 years, and a 90 percent probability of it occurring within 75 years.<ref>{{cite news |last=Cronin |first=Mike |date=2 November 2009 |title=Futurists' report reviews dangers of smart robots |url=http://triblive.com/x/pittsburghtrib/news/s_651056.html |newspaper=[[Pittsburgh Tribune-Review]] |location= |access-date=20 August 2016 }}</ref> He appeared on the [[AAAI]] Presidential Panel on Long-Term AI Futures in 2009:<ref>{{cite web |url=http://research.microsoft.com/en-us/um/people/horvitz/AAAI_Presidential_Panel_2008-2009.htm|title=Asilomar Meeting on Long-Term AI Futures |date=2009 |website=Microsoft Research |access-date=20 August 2016 |quote=}}</ref> and was later described as discussing the Singularity in terms of two major milestones in artificial intelligence: {{Quote|1) Operational Sentience: We can easily converse with computers. |
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2) The AI Chain Reaction: A computer that boot straps itself to a better self. Repeat.<ref>{{cite web |url=http://blog.computationalcomplexity.org/2009/07/singularity.html |title=The Singularity |
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|last=Fortnow |first=Lance |date=31 July 2009 |website=Computational Complexity|publisher=[[Blogger]] |access-date=20 August 2016 |quote=}}</ref>}} |
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McAllester has also written on [[friendly artificial intelligence]] on his blog. He states that before machines become capable of programming themselves (potentially leading to the Singularity), there should be a period where they are moderately intelligent in which it should be possible to test out giving them a purpose or mission that should render them safe to humans: {{Quote|I personally believe that it is likely that within a decade agents will be capable of compelling conversation about the everyday events that are the topics of non-technical dinner conversations. I think this will happen long before machines can program themselves leading to an intelligence explosion. The early stages of artificial general intelligence (AGI) will be safe. However, the early stages of AGI will provide an excellent test bed for the servant mission or other approaches to friendly AI ... If there is a coming era of safe (not too intelligent) AGI then we will have time to think further about later more dangerous eras.<ref>{{cite web |url=https://machinethoughts.wordpress.com/2014/08/10/friendly-ai-and-the-servant-mission/ |title=Friendly AI and the Servant Mission |
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|last=McAllester |first=David |date=10 August 2014 |website=Machine Thoughts |publisher=[[Wordpress]] |access-date=20 August 2016 |quote=}}</ref>}} |
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==External links== |
==External links== |
Revision as of 13:18, 20 August 2016
David A. McAllester | |
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Born | 1956 (age 67–68) |
Alma mater | MIT |
Known for | Artificial intelligence |
Awards | AAAI Classic Paper Award (2010)[1] International Conference on Logic Programming Test of Time award (2014)[2] |
Scientific career | |
Fields | Computer Science, Artificial Intelligence, Machine Learning |
Institutions | Toyota Technological Institute at Chicago |
Doctoral advisor | Gerald Sussman |
Doctoral students | Robert Givan, Jr. |
This article is about the computer scientist, David A. McAllester. For the ethnomusicologist, see David P. McAllester
Professor David A. McAllester (born 1956) received his B.S., M.S., and Ph.D. degrees from the Massachusetts Institute of Technology in 1978, 1979, and 1987 respectively. His PhD was supervised by Gerald Sussman. He served on the faculty of Cornell University for the academic year of 1987-1988 and on on the faculty of MIT from 1988 to 1995. He was a member of technical staff at AT&T Labs-Research from 1995 to 2002. He has been a fellow of the American Association of Artificial Intelligence since 1997.[3] He has authored over 100 refereed publications.
Professor McAllester's research areas include machine learning theory, the theory of programming languages, automated reasoning, AI planning, computer game playing (computer chess), and computational linguistics. A 1991 paper on AI planning[4] proved to be one of the most influential papers of the decade in that area.[5] A 1993 paper on computer game algorithms[6] influenced the design of the algorithms used in the Deep Blue system that defeated Garry Kasparov.[7] A 1998 paper on machine learning theory[8] introduced PAC-Bayesian theorems which combine Bayesian and non-Bayesian methods. His plans for future research are focused on the integration of semantics into statistical approaches to computational linguistics.
McAllester is currently a professor and chief academic officer at the Toyota Technological Institute at Chicago, an accredited research institute closely affiliated with the University of Chicago.[9]
Opinons on Artifical Intelligence
McAllester has voiced concerns about the potential dangers of artificial intelligence, stating in an article to the Pittsburgh Tribune-Review that it is inevitable that fully automated intelligent machines will be able to design and build smarter, better versions of themselves, an event known as the Singularity. The Singularity would enable machines to become infinitely intelligent, and would pose an "incredibly dangerous scenario". McAllester estimates a 10 percent probability of the Singularity occurring within 25 years, and a 90 percent probability of it occurring within 75 years.[10] He appeared on the AAAI Presidential Panel on Long-Term AI Futures in 2009:[11] and was later described as discussing the Singularity in terms of two major milestones in artificial intelligence:
1) Operational Sentience: We can easily converse with computers. 2) The AI Chain Reaction: A computer that boot straps itself to a better self. Repeat.[12]
McAllester has also written on friendly artificial intelligence on his blog. He states that before machines become capable of programming themselves (potentially leading to the Singularity), there should be a period where they are moderately intelligent in which it should be possible to test out giving them a purpose or mission that should render them safe to humans:
I personally believe that it is likely that within a decade agents will be capable of compelling conversation about the everyday events that are the topics of non-technical dinner conversations. I think this will happen long before machines can program themselves leading to an intelligence explosion. The early stages of artificial general intelligence (AGI) will be safe. However, the early stages of AGI will provide an excellent test bed for the servant mission or other approaches to friendly AI ... If there is a coming era of safe (not too intelligent) AGI then we will have time to think further about later more dangerous eras.[13]
External links
- David McAllester's academic page at TTIC.
- Machine Thoughts, David McAllester's personal blog.
- David Allen McAllester at the Mathematics Genealogy Project.
References
- ^ "AAAI Classic Paper Award". AAAI. 2016. Retrieved 19 August 2016.
- ^ "Pascal's paper stands the test of time". Australian National University. 23 April 2014. Retrieved 19 August 2016.
- ^ "David McAllester bio". Toyota Technological Institute at Chicago. Retrieved 19 August 2016.
- ^ McAllester, David; Rosenblitt, David (December 1991). "Systematic Nonlinear Planning" (PDF). Proceedings AAAI-91. AAAI: 634–639. Retrieved 19 August 2016.
- ^ "Google Scholar Citations". Google Scholar. 2016. Retrieved 19 August 2016.
- ^ McAllester, David; Yuret, Deniz (20 October 1993). "Alpha-Beta-Conspiracy Search". Draft. Retrieved 19 August 2016.
{{cite journal}}
: Cite journal requires|journal=
(help) - ^ Campbell, Murray S.; Joseph Hoane, Jr., A.; Hsu, Feng-hsiung (1999). "Search Control Methods in Deep Blue" (PDF). AAAI Technical Report SS-99-07. AAAI: 19–23. Retrieved 16 August 2016.
To the best of our knowledge, the idea of separating the white and black depth computation was first suggested by David McAllester. A later paper (McAllester and Yuret 1993) derived an algorithm, ABC, from conspiracy theory (McAllester 1988).
- ^ McAllester, David (1998). "Some PAC-Bayesian theorems". Proceedings of the eleventh annual conference on Computational learning theory. Association for Computing Machinery: 230–234. doi:10.1145/279943.279989. Retrieved 19 August 2016.
- ^ "TTIC faculty". Toyota Technological Institute at Chicago. 2016. Retrieved 19 August 2016.
- ^ Cronin, Mike (2 November 2009). "Futurists' report reviews dangers of smart robots". Pittsburgh Tribune-Review. Retrieved 20 August 2016.
- ^ "Asilomar Meeting on Long-Term AI Futures". Microsoft Research. 2009. Retrieved 20 August 2016.
- ^ Fortnow, Lance (31 July 2009). "The Singularity". Computational Complexity. Blogger. Retrieved 20 August 2016.
- ^ McAllester, David (10 August 2014). "Friendly AI and the Servant Mission". Machine Thoughts. Wordpress. Retrieved 20 August 2016.