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User:Prof. Carl Hewitt/EditRequestsForArticleCarlHewitt

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Carl Hewitt

Editors are welcome to edit here to improve the edit requests and to coordinate with other edit requests for the the article Carl Hewitt. Carl (talk) 02:56, 14 June 2016 (UTC)


Edit request for Infobox edit

In order to bring the Infobox of the article up to date, please change the Infobox currently in the article to the one below:


Carl Hewitt
 
Carl Hewitt in 2008
Alma materMIT
Known forActor Model
Inconsistency robustness
Planner (logic programs)
Comparative schematology
Scientific career
FieldsComputer Science
Mathematical Logic
Software Engineering
Models of Computation
Programming Languages
Philosophy of Science
Philosophy of Logic
Philosophy of Information
History of Computer Science
History of Logic
InstitutionsMIT
Keio University
Stanford University
Doctoral advisorSeymour Papert
Other academic advisorsMarvin Minsky
Mike Paterson
Doctoral studentsGul Agha
Henry Baker
William Clinger
Irene Greif
Akinori Yonezawa
Websitehttp://CarlHewitt.iRobust.org

Carl (talk) 23:00, 14 July 2016 (UTC)

Edit request for lede edit

Please change the current article lede to the following:

Carl Hewitt (/ˈhjuːɪt/) is an emeritus professor of computer science (MIT) who is best known for his work on the Actor model[1][2] of computation. For the last decade, his work has been in the field of "Inconsistency Robustness", which he founded in 2007.[3] Inconsistency Robustness aims to provide practical rigorous foundations for systems dealing with pervasively inconsistent information.[4][2] This work grew out of his doctoral dissertation focused on the procedural (as opposed to logical) embedding of knowledge, which was embodied in the Planner programming language for Logic Programs[5].
Hewitt is currently Board Chair of the International Society for Inconsistency Robustness.[4]iRobust™ and also Board Chair of Standard IoT™, an international standards organization for the Internet of Things, which is using the Actor Model to unify and generalize emerging standards for IoT.[6] Previously, he has been a Visiting Professor at Keio University and Stanford.

References

  1. ^ Carl Hewitt (2015). "Actor Model of Computation". Studies in Logic. Vol. 52. College Publications. ISBN 9781848901599.
  2. ^ a b JJ Meyer. "Review of 'Inconsistency Robustness' (Vol. 52 of Studies in Logic)". College Publications. 2016. Retrieved 2016-06-05.
  3. ^ International Society for Inconsistency Robustness
  4. ^ a b Inconsistency Robustness. Studies in Logic. Vol. 52. College Publications. 2015. ISBN 9781848901599. {{cite book}}: Unknown parameter |editors= ignored (|editor= suggested) (help) Cite error: The named reference "InconsistencyRobustness" was defined multiple times with different content (see the help page).
  5. ^ Carl Hewitt (2015). "Inconsistency Robustness for Logic Programs". Studies in Logic. Vol. 52. College Publications. ISBN 9781848901599.
  6. ^ Carl Hewitt. "Why All Writs is a Trojan Horse" Letter to Editor. CACM. May 2016.

Carl (talk) 02:34, 14 June 2016 (UTC)

Edit request fo Education and career section edit

Please change the current article Education and career section the following:

Hewitt obtained his PhD in mathematics at MIT in 1971, under the supervision of Seymour Papert, Marvin Minsky, and Mike Paterson. Hewitt started his employment at MIT in 1971.[1] He retired from the faculty of the MIT Department of Electrical Engineering and Computer Science during in 2000.[2] Among the doctoral students that Hewitt supervised during his time at MIT are Gul Agha, Henry Baker, William Clinger, Irene Greif, and Akinori Yonezawa.[3]
From September 1989 to August 1990, Hewitt was the IBM Chair Visiting Professor in the Department of Computer Science at Keio University in Japan.[4] He has been a Visiting Professor at Stanford University.

References

  1. ^ MIT News Office (April 10, 1996). "Quarter Century Club inducts 73 new members". Retrieved 2007-06-19.
  2. ^ John V. Guttag (2000). "MIT Reports to the President 1999–2000 - Department of Electrical Engineering and Computer Science". Retrieved 2007-06-19.
  3. ^ Carl Hewitt (2007). "Academic Biography of Carl Hewitt". Retrieved 2007-11-22.
  4. ^ Ryuichiro Ohyama (1991). "Department of Computer Science-Recent and Current Visiting Professors". Retrieved 2007-06-19.

Carl (talk) 18:49, 22 June 2016 (UTC)

Edit request for Research section lede edit

Please change the lede of the current article Research Section to the following:

Hewitt is best known for his work on the Actor model of computation.[1] For the last decade, his work has been in "inconsistency robustness", which aims to provide practical rigorous foundations for systems dealing with pervasively inconsistent information.[2][3] This work grew out of his doctoral dissertation focused on the procedural (as opposed to logical) embedding of knowledge, which was embodied in the Planner programming language that influence the development of a family of AI programming languages (e.g. Conniver, QA-4, Prolog backward-chaining subset of micro-Planner capabilities, and Concurrent Prolog).

References

  1. ^ Cite error: The named reference ActorModel was invoked but never defined (see the help page).
  2. ^ Cite error: The named reference InconsistencyRobustness was invoked but never defined (see the help page).
  3. ^ Cite error: The named reference JJ was invoked but never defined (see the help page).

Carl (talk) 18:50, 22 June 2016 (UTC)

Edit request Actor model edit

Please change the current article Actor Model Section to the following:

Main article: Actor model

Hewitt's work on the Actor model of computation has spanned over 30 years, beginning with the introduction of the model in a 1973 paper authored by Hewitt, Peter Bishop, and Richard Steiger[1], a denotational model[2], and a summary and overview article[3]. Early work on the Actor Model was carried out in Hewitt's Message Passing Semantics Group at MIT's Artificial Intelligence Lab.[4]

Sussman and Steele developed the Scheme programming language in an effort to gain a better understanding of the Actor model. However, their Scheme interpreter was not capable of fully implementing the Actor model because Actor customers cannot be implemented as lambda calculus continuations and Actors can change concurrently in a way that is impossible in the lambda calculus [3][5] A number of programming languages were developed to specifically implement the Actor model, such as ACT-1,[6] SALSA,[7] Caltrop,[8], and the E programming language. Hewitt's programming language research has culminated with development of ActorScript[9], which extends capabilities of Java, C++, and JavaScript as well as logic programs.

The Actor model also influenced the development of other models of computation, included the π-calculus.[10] (See Actor model and process calculi history.)

References

  1. ^ Carl Hewitt, Peter Bishop, and Richard Steiger (1973). "A Universal Modular Actor Formalism for Artificial Intelligence". IJCAI. {{cite journal}}: Cite journal requires |journal= (help)CS1 maint: multiple names: authors list (link)
  2. ^ Carl Hewitt What is Commitment? Physical, Organizational, and Social COIN@AAMAS. April 27, 2006.
  3. ^ a b Cite error: The named reference ActorModel was invoked but never defined (see the help page).
  4. ^ Mark S. Miller. "Actors: Foundations for Open Systems". Retrieved 2007-06-20.
  5. ^ Gerald Sussman and Guy Steele (1998). "The First Report on Scheme Revisited" (PDF). Higher-Order and Symbolic Computation. 11 (4). Boston: Kluwer Academic Publishers: 399–404. doi:10.1023/A:1010079421970.
  6. ^ Henry Lieberman, "Concurrent Object-Oriented Programming in Act 1", In Object-Oriented Concurrent Programming, A. Yonezawa and M. Tokoro, eds., MIT Press, 1987.
  7. ^ C. Varela and G. Agha. Programming Dynamically Reconfigurable Open Systems with SALSA. OOPSLA 2001 Intriguing Technology Track. ACM SIGPLAN Notices, 36(12):20-34, December 2001.
  8. ^ Johan Eker; Jörn W. Janneck. "An introduction to the Caltrop actor language" (PDF). Retrieved 2007-06-20. {{cite journal}}: Cite journal requires |journal= (help)
  9. ^ Carl Hewitt (2015). "ActorScript™". Studies in Logic. Vol. 52. College Publications. ISBN 9781848901599.
  10. ^ Robin Milner Elements of interaction: Turing award lecture CACM. January 1993.

Carl (talk) 20:57, 6 June 2016 (UTC)

Edit request Inconsistency Robustness edit

Please introduce the following Inconsistency Robustness subsection in the Research section of the article:

Hewitt is the founder of the field of Inconsistency Robustness, i.e., the science and engineering of large systems with continual, pervasive inconsistencies (a shift from the previously dominant paradigms of inconsistency denial and inconsistency elimination)iRobust™[1][2] He is currently Board Chair of the International Society for Inconsistency Robustness (iRobust™).iRobust™ Previously, he was Program Chair of international symposia on the subject at Stanford in 2011 and 2014.iRobust™[1] The text on the subject is Inconsistency Robustness[1] for which Hewitt is co-editor and a contributor. Operational aspects of Inconsistency Robustness are addressed using the Actor Model of computation and inferential aspects using Direct Logic™.[1][2]

Hewitt is the creator (together with his students and other colleagues) of Direct Logic™ for inference in Inconsistency Robust systems.[3][1][2] Inconsistency robust logic is an important conceptual advance in that requires that nothing “extra” can be inferred just from the presence of a contradiction.[2] A natural question that arises is the relationship between paraconsistency and inconsistency robustness. It turns out that a paraconsistent logic can allow erroneous inferences from an inconsistency that are not allowed by inconsistency robustness.[2] Of course, an inconsistency robust logic is also necessarily paraconsistent.[2]

The goal of Classical Direct Logic (a special case of Inconsistency Robust Direct Logic) is to provide mathematical foundations for Computer Science.[1][2] Because Direct Logic is strongly typed, it defies Gödel's meta-mathematical results on which is the proposition of the Dedekind/Peano theory of numbers that is true but unprovable.[1][2] Gödel proposed the sentence I'm unprovable. as a true but unprovable sentence.[1][2] I'm unprovable. is a sentence in Provability Logic which is untyped and consequently allows taking fixed points of untyped sentences to construct the sentence. However, Provability Logic is not suitable for the mathematical foundations of Computer Science, which require strong parameterized types. Consequently, I'm unprovable. is not a sentence in the mathematical foundations of Computer Science because it does not have a proper type.[1][4] In fact, Wittgenstein correctly pointed out that Gödel's sentence leads to inconsistency in mathematics.[1] Consequently Gödel's argument (using his sentence) is incorrect that mathematics cannot prove its own consistency without itself falling into inconsistency.[1] In Direct Logic, mathematics formally proves its own consistency (using a very simple proof by contradiction) without evident self-contradiction in mathematics (e.g., all the usual paradoxes such as Berry, [[[Burali-Forti paradox|Burali-Forti]], Girad, Russell, etc. do not produce inconsistencies).[1][4]

References

  1. ^ a b c d e f g h i j k l Cite error: The named reference InconsistencyRobustness was invoked but never defined (see the help page).
  2. ^ a b c d e f g h i Cite error: The named reference JJ was invoked but never defined (see the help page).
  3. ^ "Carl Hewitt. Formalizing common sense reasoning for scalable inconsistency-robust information coordination using Direct Logic Reasoning and the Actor Model." in Vol. 52 of Studies in Logic. College Publications. ISBN-10: ISBN 1848901593. 2015.
  4. ^ a b "Carl Hewitt remembers Marvin Minsky" Remembering AI Pioneer Marvin Minsky. AAAI Spring Symposia. Stanford University. YouTube. March 16, 2016.

Carl (talk) 01:53, 12 July 2016 (UTC)

Edit request Opposition to Mandatory IoT Backdoors edit

Please introduce the following Mandatory IoT Backdoors subsection in the Research section of the article:

Hewitt has been an advocate against mandatory IoT backdoors.[1][2] [3][4]

IoT devices are becoming pervasive in all aspects of life including personal, corporate, government, and social. Adopting IoT mandatory backdoors ultimately means that security agencies of each country surveil and control IoT in their own country and perhaps swap surveillance information with other countries.[1][2] US Senators Burr and Feinstein have proposed that it must be possible for security agencies to be able to secretly access and take control of any individual IoT device. However adopting their proposal would make it very difficult to prevent security agencies from accessing and controlling large numbers of devices and abusing their surveillance and control capabilities.[1] Also, adopting IoT mandatory backdoors would be corrosive to civil liberties because any IoT device could be secretly accessed and controlled without any awareness by those using the device.[2] A critical security issue is that after a backdoor has been exercised to take control of a citizen’s IoT device without their awareness, the device thereby becomes somewhat less secure because of potential vulnerabilities in the new virtualized system used to take control of the device.[2]

Distributed Encrypted Public Recording (DEPR) is system in which distributed public and private organizations keep encrypted electronic records of all activity that takes place in outside the homestead including tracking automobiles, cell phones locations, humans (using facial recognition), and all financial transactions.[2] The records can be decrypted only by court warrant using both a key kept by the recording establishment and a key provided by the court. If not court ordered within a time set at recording, the recordings cannot read by anyone (enforced by cryptography using a trans-national distributed Internet time authority). In addition to ensuring that outdated information cannot be decrypted, the trans-national time authority can provide continual statistics on the amount of decrypted information as a deterrent to mass surveillance and control. Advanced Inconsistency Robust information technology can be a very powerful tool for catching and prosecuting suspects using DEPR.[2] Using DEPR is a less risky to civil liberties than requiring IoT mandatory backdoors for all IoT devices. The DEPR proposal brings out the issue that massive amounts of information are being collected and disseminated with almost no regulation whatsoever. Soon there stands to be even greater collection and dissemination, which will inevitably lead to increasingly severe scandals.[2]

Hewitt's proposal aims to balance the Constitutional requirement to protect citizens’ civil liberties and for law enforcement to catch and prosecute suspects (such as alleged “terrorists”).[2] Hewitt maintains that it would uphold the U.S. Constitution’s Fifth Amendment right against self-incrimination by prohibiting mandatory IoT backdoors that could provide access to sensitive personal information. At the same time, it would not prohibit access to “distributed encrypted public recording” (such as videos in public places, all financial transactions, and locations of cell phones from cell towers) so all recorded activities except those in personal IoT devices could be subpoenaed.[2]

References

  1. ^ a b c Cite error: The named reference backdoorsCACM was invoked but never defined (see the help page).
  2. ^ a b c d e f g h i Carl Hewitt. "Security Without Iot Mandatory Backdoors: Using Distributed Encrypted Public Recording to Catch & Prosecute Suspects"[1] SSRN. June 14, 2016.
  3. ^ Carl Hewitt. "Islets Protect Sensitive IoT Information in Commerce: Islets™ Can Verifiably End Use of Sensitive IoT Information for (Foreign) Mass Surveillance and Thereby Foster (International) Commerce"[2] SSRN. September 7, 2016.
  4. ^ Cite error: The named reference InconsistencyRobustness was invoked but never defined (see the help page).

Carl (talk) 18:50, 22 June 2016 (UTC)

Edit request Planner edit

Please change the current Planner Section to the following:

Main article: Planner (programming language)

The Planner language was developed during the late 1960s as part of Hewitt's doctoral research in MIT's Artificial Intelligence Laboratory. Hewitt's work on Planner introduced the notion of the "procedural embedding of knowledge",[1] which was an alternative to the purely logical approach to knowledge encoding for artificial intelligence (epitomized by uniform procedure resolution theorem provers).[2] Planner has been described as "extremely ambitious".[3] A subset of Planner called Micro-Planner was implemented at MIT by Gerry Sussman, Drew McDermott, Eugene Charniak and Terry Winograd[4] and was used in Winograd's SHRDLU program,[5] Charniak's natural language story understanding work,[6] and L. Thorne McCarty's work on legal reasoning.[7] Planner was almost completely implemented in Popler[8] by Julian Davies at Edinburgh, where (together with earlier work at Edinburgh on Pico-Planner by Bruce Anderson[9]) it influenced Robert Kowalski and Pat Hayes in the development of ideas that later became Prolog.[10].[11] Planner also influenced the later development of other AI research languages such as QA-4, Muddle, and Conniver,[3] as well as the Smalltalk object-oriented programming language.[12]

Hewitt's own work on Planner initially continued with Muddle (later called MDL), which was developed in the early 1970s by Sussman, Hewitt, Chris Reeve, and David Cressey as a stepping-stone towards a full implementation of Planner. Muddle was implemented as an extended version of Lisp, and introduced several features that were later adopted by Conniver, Lisp Machine Lisp, and Common Lisp.[3] However, in late 1972 Hewitt abruptly halted his work on MDL, when he and his graduate students invented the Actor model of computation.

References

  1. ^ Carl Hewitt. Procedural Embedding of Knowledge In Planner IJCAI. 1971.
  2. ^ Philippe Rouchy, Aspects of PROLOG History: Logic Programming and Professional Dynamics, TeamEthno-Online Issue 2, June 2006, 85-100.
  3. ^ a b c Sussman, Gerald Jay; Guy L. Steele (1998). "The First Report on Scheme Revisited" (PDF). Higher-Order and Symbolic Computation. 11 (4). Boston: Kluwer Academic Publishers: 399–404. doi:10.1023/A:1010079421970. Retrieved 2009-01-03.
  4. ^ Gerry Sussman and Terry Winograd. Micro-planner Reference Manual AI Memo No, 203, MIT Project MAC, July 1970.
  5. ^ Terry Winograd. Procedures as a Representation for Data in a Computer Program for Understanding Natural Language MIT AI TR-235. January 1971.
  6. ^ Marvin Minsky and Seymour Papert. “Progress Report on Artificial Intelligence” MIT AI Memo 252. 1971.
  7. ^ L. Thorne McCarty. "Reflections on TAXMAN: An Experiment on Artificial Intelligence and Legal Reasoning" Harvard Law Review. Vol. 90, No. 5, March 1977
  8. ^ Julian Davies. Popler 1.6 Reference Manual University of Edinburgh, TPU Report No. 1, May 1973.
  9. ^ Bruce Anderson. Documentation for LIB PICO-PLANNER School of Artificial Intelligence, Edinburgh University. 1972.
  10. ^ Carl Hewitt (2015). "Inconsistency Robustness for Logic Programs". Studies in Logic. Vol. 52. College Publications. ISBN 9781848901599.
  11. ^ Robert Kowalski Predicate Logic as Programming Language IFIP'74.
  12. ^ Alan Kay and Stefan Ram (2003-07-23). "E-Mail of 2003-07-23". Dr. Alan Kay on the Meaning of “Object-Oriented Programming”. Retrieved 2009-01-03.

Carl (talk) 03:13, 14 June 2016 (UTC)

Edit Request Logic Programs edit

Please introduce the following Logic Programs subsection in the Research section of the article:

After Planner, Hewitt continued to work on Logic Programs in the context of the Actor Model developing the criteria that a Logic Program could only take steps justified by logical forward and backward inference. Using the Actor Model, he then proved that (contrary to Kowalski) Logic Programs do not subsume all programs. Many years of development lead to the development of the ActorScript[1] programming language, which includes a logic program subset in which each computational step is justified by a rule of Direct Logic.[2] The logic program subset of ActorScript completes the development of the project initiated with Planner by providing for fully concurrent forward and backward chaining for inconsistency robust logical inference.

References

  1. ^ Cite error: The named reference ActorScript was invoked but never defined (see the help page).
  2. ^ Cite error: The named reference LogicPrograms was invoked but never defined (see the help page).

Carl (talk) 22:35, 26 August 2016 (UTC)

Edit request Comparative Schematology edit

Please introduce the following Comparative Schematolog subsection in the Research section of the article:

As a graduate student, Hewitt worked on the mathematical disciple of comparative schematology, which studies the power of programming language constructs using program schemas.[1] Together with Mike Paterson, he proved that recursion is more powerful than iteration[2] using a pebble argument. Pebble arguments have subsequently seen widespread application in theoretical computer science.

References

  1. ^ Carl Hewitt. "More Comparative Schematology" MIT AI Memo 207. August 1970.
  2. ^ Michael Paterson and Carl Hewitt. "Comparative Schematology" MIT AI Memo 464. May 1970.

Carl (talk) 02:38, 14 June 2016 (UTC)

Edit request for Selected Works edit

Please change the current section "Selected Works" to the following:

Historical edit

Current edit

Carl (talk) 17:34, 8 November 2016 (UTC)

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