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Cyc

From Wikipedia, the free encyclopedia
(Redirected from ResearchCyc)
For other uses, see Cyc (disambiguation).
Original author(s)Douglas Lenat
Developer(s)Cycorp, Inc.
Initial release1984; 40 years ago (1984)
Stable release
6.1 / 27 November 2017; 6 years ago (2017-11-27)
Written inLisp, CycL, SubL
TypeKnowledge representation language and inference engine
Websitewww.cyc.com

Cyc (pronounced /ˈsaɪk/ SYKE) is a long-term artificial intelligence project that aims to assemble a comprehensive ontology and knowledge base that spans the basic concepts and rules about how the world works. Hoping to capture common sense knowledge, Cyc focuses on implicit knowledge. The project began in July 1984 at MCC and was developed later by the Cycorp company.

The name "Cyc" (from "encyclopedia") is a registered trademark owned by Cycorp. CycL has a publicly released specification, and dozens of HL (Heuristic Level) modules were described in Lenat and Guha's textbook,[1] but the Cyc inference engine code and the full list of HL modules are Cycorp-proprietary.[2]

History

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The project began in July 1984 by Douglas Lenat as a project of the Microelectronics and Computer Technology Corporation (MCC), a research consortium started by two United States–based corporations "to counter a then ominous Japanese effort in AI, the so-called 'fifth-generation' project."[3] The US passed the National Cooperative Research Act of 1984, which for the first time allowed US companies to "collude" on long-term research. Since January 1995, the project has been under active development by Cycorp, where Douglas Lenat was the CEO.

The CycL representation language started as an extension of RLL[4][5] (the Representation Language Language, developed in 1979–1980 by Lenat and his graduate student Russell Greiner while at Stanford University). In 1989,[6] CycL had expanded in expressive power to higher-order logic (HOL).

Cyc's ontology grew to about 100,000 terms in 1994, and as of 2017, it contained about 1,500,000 terms. The Cyc knowledge base involving ontological terms was largely created by hand axiom-writing; it was at about 1 million in 1994, and as of 2017, it is at about 24.5 million.

In 2008, Cyc resources were mapped to many Wikipedia articles.[7] Cyc is presently connected to Wikidata.

Knowledge base

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The knowledge base is divided into microtheories. Unlike the knowledge base as a whole, each microtheory must be free from monotonic contradictions. Each microtheory is a first-class object in the Cyc ontology; it has a name that is a regular constant. The concept names in Cyc are CycL terms or constants.[6] Constants start with an optional #$ and are case-sensitive. There are constants for:

  • Individual items known as individuals, such as #$BillClinton or #$France.
  • Collections, such as #$Tree-ThePlant (containing all trees) or #$EquivalenceRelation (containing all equivalence relations). A member of a collection is called an instance of that collection.[1]
  • Functions, which produce new terms from given ones. For example, #$FruitFn, when provided with an argument describing a type (or collection) of plants, will return the collection of its fruits. By convention, function constants start with an upper-case letter and end with the string Fn.
  • Truth functions, which can apply to one or more other concepts and return either true or false. For example, #$siblings is the sibling relationship, true if the two arguments are siblings. By convention, truth function constants start with a lowercase letter.

For every instance of the collection #$ChordataPhylum (i.e., for every chordate), there exists a female animal (instance of #$FemaleAnimal), which is its mother (described by the predicate #$biologicalMother).[1]

Inference engine

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An inference engine is a computer program that tries to derive answers from a knowledge base. The Cyc inference engine performs general logical deduction.[8] It also performs inductive reasoning, statistical machine learning and symbolic machine learning, and abductive reasoning.

The Cyc inference engine separates the epistemological problem from the heuristic problem. For the latter, Cyc used a community-of-agents architecture in which specialized modules, each with its own algorithm, became prioritized if they could make progress on the sub-problem.

Releases

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OpenCyc

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The first version of OpenCyc was released in spring 2002 and contained only 6,000 concepts and 60,000 facts. The knowledge base was released under the Apache License. Cycorp stated its intention to release OpenCyc under parallel, unrestricted licences to meet the needs of its users. The CycL and SubL interpreter (the program that allows users to browse and edit the database as well as to draw inferences) was released free of charge, but only as a binary, without source code. It was made available for Linux and Microsoft Windows. The open source Texai[9] project released the RDF-compatible content extracted from OpenCyc.[10] The version OpenCyc 4.0 was released in June 2012. OpenCyc 4.0 contained 239,000 concepts and 2,093,000 facts; however, these are mainly taxonomic assertions.

ResearchCyc

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In July 2006, Cycorp released the executable of ResearchCyc 1.0, a version of Cyc aimed at the research community, at no charge. (ResearchCyc was in beta stage of development during all of 2004; a beta version was released in February 2005.) In addition to the taxonomic information, ResearchCyc includes more semantic knowledge; it also includes a large lexicon, English parsing and generation tools, and Java-based interfaces for knowledge editing and querying. It contains a system for ontology-based data integration.

Applications

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For over a decade, Glaxo has used Cyc to semi-automatically integrate the large thesauri of pharmaceutical-industry terms.[11] Previously, they used staff to do that manually. The Cleveland Clinic has used Cyc to develop a natural-language query interface of biomedical information on cardiothoracic surgeries.[12] A query is parsed into a set of CycL fragments with open variables.[13] The Terrorism Knowledge Base was an application of Cyc that tried to contain knowledge about "terrorist"-related descriptions. The knowledge is stored as statements in mathematical logic.[14][15]

One Cyc application has the stated aim to help students doing math at a 6th grade level.[16] The application, called MathCraft,[17] was supposed to play the role of a fellow student who is slightly more confused than the user about the subject. As the user gives good advice, Cyc allows the avatar to make fewer mistakes.

Criticisms

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The Cyc project has been described as "one of the most controversial endeavors of the artificial intelligence history".[18] Catherine Havasi, CEO of Luminoso, says that Cyc is the predecessor project to IBM's Watson.[19] Machine-learning scientist Pedro Domingos refers to the project as a "catastrophic failure" for the unending amount of data required to produce any viable results and the inability for Cyc to evolve on its own.[20]

Gary Marcus, a cognitive scientist and the cofounder of an AI company called Geometric Intelligence, says "it represents an approach that is very different from all the deep-learning stuff that has been in the news."[21] This is consistent with Doug Lenat's position that "Sometimes the veneer of intelligence is not enough".[22]

Notable employees

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This is a list of some of the notable people who work or have worked on Cyc either while it was a project at MCC (where Cyc was first started) or Cycorp.

See also

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References

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  1. ^ a b c Lenat, Douglas B.; Guha, R. V. (1989). Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project (1st ed.). Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc. ISBN 978-0201517521.
  2. ^ Lenat, Douglas. "Hal's Legacy: 2001's Computer as Dream and Reality. From 2001 to 2001: Common Sense and the Mind of HAL" (PDF). Cycorp, Inc. Archived (PDF) from the original on 2019-12-09. Retrieved 2006-09-26.
  3. ^ Wood, Lamont (2002). "The World in a Box". Scientific American. 286 (1): 18–19. Bibcode:2002SciAm.286a..18W. doi:10.1038/scientificamerican0102-18.
  4. ^ "A Representation Language Language". www.aaai.org. Retrieved 2017-11-27.
  5. ^ Russell, Greiner (October 1980). RLL-1: A Representation Language Language (Report). Archived from the original on February 8, 2015.
  6. ^ a b Lenat, Douglas B.; Guha, R. V. (June 1991). "The Evolution of CycL, the Cyc Representation Language". ACM SIGART Bulletin. 2 (3): 84–87. doi:10.1145/122296.122308. ISSN 0163-5719. S2CID 10306053.
  7. ^ "Integrating Cyc and Wikipedia: Folksonomy meets rigorously defined common-sense" (PDF). Retrieved 2013-05-10.
  8. ^ "cyc Inference engine". Archived from the original on 2019-12-09. Retrieved 2015-06-04.
  9. ^ "The open source Texai project". Archived from the original on 2009-02-16.
  10. ^ "Texai SourceForge project files".
  11. ^ HILTZIK, MICHAEL A. (2001-06-21). "Birth of a Thinking Machine". Los Angeles Times. ISSN 0458-3035. Retrieved 2017-11-29.
  12. ^ "Case Study: A Semantic Web Content Repository for Clinical Research". www.w3.org. Retrieved 2018-02-28.
  13. ^ Lenat, Douglas; Witbrock, Michael; Baxter, David; Blackstone, Eugene; Deaton, Chris; Schneider, Dave; Scott, Jerry; Shepard, Blake (2010-07-28). "Harnessing Cyc to Answer Clinical Researchers' Ad Hoc Queries". AI Magazine. 31 (3): 13. doi:10.1609/aimag.v31i3.2299. ISSN 0738-4602.
  14. ^ Chris Deaton; Blake Shepard; Charles Klein; Corrinne Mayans; Brett Summers; Antoine Brusseau; Michael Witbrock; Doug Lenat (2005). "The Comprehensive Terrorism Knowledge Base in Cyc". Proceedings of the 2005 International Conference on Intelligence Analysis. CiteSeerX 10.1.1.70.9247.
  15. ^ Douglas B. Lenat; Chris Deaton (April 2008). TERRORISM KNOWLEDGE BASE (TKB) Final Technical Report (Technical report). Rome Research Site, Rome, New York: Air Force Research Laboratory Information Directorate. AFRL-RI-RS-TR-2008-125.
  16. ^ Lenat, Douglas B.; Durlach, Paula J. (2014-09-01). "Reinforcing Math Knowledge by Immersing Students in a Simulated Learning-By-Teaching Experience". International Journal of Artificial Intelligence in Education. 24 (3): 216–250. doi:10.1007/s40593-014-0016-x. ISSN 1560-4292.
  17. ^ "Mathcraft by Cycorp". www.mathcraft.ai. Retrieved 2017-11-29.
  18. ^ Bertino, Piero & Zarria 2001, p. 275
  19. ^ Havasi, Catherine (Aug 9, 2014). "Who's Doing Common-Sense Reasoning And Why It Matters". TechCrunch. Retrieved 2017-11-29.
  20. ^ Domingos, Pedro (2015). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. Basic Books. ISBN 978-0465065707.
  21. ^ Knight, Will (Mar 14, 2016). "An AI that spent 30 years learning some common sense is ready for work". MIT Technology Review. Retrieved 2017-11-29.
  22. ^ Doug Lenat (May 15, 2017). "Sometimes the Veneer of Intelligence is Not Enough". CogWorld. Retrieved 2017-11-29.

Further reading

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