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Cyc /ˈsaɪk/ is an artificial intelligence project that attempts to assemble a comprehensive ontology and knowledge base of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning

The project was started in 1984 by Douglas Lenat at MCC and is developed by the Cycorp company Parts of the project are released as OpenCyc, which provides an API, RDF endpoint, and data dump under an open source license


  • 1 Overview
  • 2 Knowledge base
  • 3 Inference engine
  • 4 Releases
    • 41 OpenCyc
    • 42 ResearchCyc
  • 5 Applications
    • 51 Terrorism Knowledge Base
    • 52 Cyclopedia
    • 53 Cleveland Clinic Foundation
  • 6 Criticisms
  • 7 Notable employees
  • 8 See also
  • 9 References
  • 10 Further reading
  • 11 External links


The project was started in 1984 as part of Microelectronics and Computer Technology Corporation The objective was to codify, in machine-usable form, millions of pieces of knowledge that compose human common sense CycL presented a proprietary knowledge representation schema that utilized first-order relationships In 1986, Doug Lenat estimated the effort to complete Cyc would be 250,000 rules and 350 man-years of effort The Cyc Project was spun off into Cycorp, Inc in Austin, Texas in 1994

The name "Cyc" from "encyclopedia", pronounced like syke is a registered trademark owned by Cycorp The original knowledge base is proprietary, but a smaller version of the knowledge base, intended to establish a common vocabulary for automatic reasoning, was released as OpenCyc under an open source Apache license More recently, Cyc has been made available to AI researchers under a research-purposes license as ResearchCyc

Typical pieces of knowledge represented in the database are "Every tree is a plant" and "Plants die eventually" When asked whether trees die, the inference engine can draw the obvious conclusion and answer the question correctly The Knowledge Base KB contains over one million human-defined assertions, rules or common sense ideas These are formulated in the language CycL, which is based on predicate calculus and has a syntax similar to that of the Lisp programming language

Much of the current work on the Cyc project continues to be knowledge engineering, representing facts about the world by hand, and implementing efficient inference mechanisms on that knowledge Increasingly, however, work at Cycorp involves giving the Cyc system the ability to communicate with end users in natural language, and to assist with the knowledge formation process via machine learning

Like many companies, Cycorp has ambitions to use Cyc's natural language processing to parse the entire internet to extract structured data

In 2008, Cyc resources were mapped to many Wikipedia articles, potentially easing connecting with other open datasets like DBpedia and Freebase

Knowledge base

The concept names in Cyc are known as constants 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
  • Functions, which produce new terms from given ones For example, #$FruitFn, when provided with an argument describing a type or collection of plants, will return the collection of its fruits By convention, function constants start with an upper-case letter and end with the string "Fn"
  • Truth Functions which can be applied to one or more other concepts and return either true or false For example, #$siblings is the sibling relationship, true if the two arguments are siblings By convention, truth function constants start with a lower-case letter Truth functions may be broken down into logical connectives such as #$and, #$or, #$not, #$implies, quantifiers #$forAll, #$thereExists, etc and predicates

The most important predicates are #$isa and #$genls The first one describes that one item is an instance of some collection, the second one that one collection is a subcollection of another one Facts about concepts are asserted using certain CycL sentences Predicates are written before their arguments, in parentheses:

#$isa #$BillClinton #$UnitedStatesPresident

"Bill Clinton belongs to the collection of US presidents" and

#$genls #$Tree-ThePlant #$Plant

"All trees are plants"

#$capitalCity #$France #$Paris

"Paris is the capital of France"

Sentences can also contain variables, strings starting with "" These sentences are called "rules" One important rule asserted about the #$isa predicate reads

#$implies #$and #$isa OBJ SUBSET #$genls SUBSET SUPERSET #$isa OBJ SUPERSET

with the interpretation "if OBJ is an instance of the collection SUBSET and SUBSET is a subcollection of SUPERSET, then OBJ is an instance of the collection SUPERSET" Another typical example is

#$relationAllExists #$biologicalMother #$ChordataPhylum #$FemaleAnimal

which means that for every instance of the collection #$ChordataPhylum ie for every chordate, there exists a female animal instance of #$FemaleAnimal which is its mother described by the predicate #$biologicalMother

The knowledge base is divided into microtheories Mt, collections of concepts and facts typically pertaining to one particular realm of knowledge Unlike the knowledge base as a whole, each microtheory is required to be free from contradictions Each microtheory has a name which is a regular constant; microtheory constants contain the string "Mt" by convention An example is #$MathMt, the microtheory containing mathematical knowledge The microtheories can inherit from each other and are organized in a hierarchy: one specialization of #$MathMt is #$GeometryGMt, the microtheory about geometry

Inference engine

An inference engine is a computer program that tries to derive answers from a knowledge base The Cyc inference engine performs general logical deduction including modus ponens, modus tollens, universal quantification and existential quantification



The latest version of OpenCyc, 40, was released in June 2012 OpenCyc 40 includes the entire Cyc ontology containing hundreds of thousands of terms, along with millions of assertions relating the terms to each other; however, these are mainly taxonomic assertions, not the complex rules available in Cyc The knowledge base contains 239,000 concepts and 2,093,000 facts and can be browsed on the OpenCyc website

The first version of OpenCyc was released in spring 2002 and contained only 6,000 concepts and 60,000 facts The knowledge base is released under the Apache License Cycorp has 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 you to browse and edit the database as well as to draw inferences is released free of charge, but only as a binary, without source code It is available for Linux and Microsoft Windows The open source Texai project has released the RDF-compatible content extracted from OpenCyc


In July 2006, Cycorp released the executable of ResearchCyc 10, 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 contained in OpenCyc, ResearchCyc includes significantly more semantic knowledge ie, additional facts about the concepts in its knowledge base, and includes a large lexicon, English parsing and generation tools, and Java based interfaces for knowledge editing and querying In addition it contains a system for Ontology-based data integration


Terrorism Knowledge Base

The comprehensive Terrorism Knowledge Base is an application of Cyc in development that will try to ultimately contain all relevant knowledge about "terrorist" groups, their members, leaders, ideology, founders, sponsors, affiliations, facilities, locations, finances, capabilities, intentions, behaviors, tactics, and full descriptions of specific terrorist events The knowledge is stored as statements in mathematical logic, suitable for computer understanding and reasoning


Cyclopedia is being developed; it superimposes Cyc keywords on pages taken from Wikipedia pages

Cleveland Clinic Foundation

The Cleveland Clinic has used Cyc to develop a natural language query interface of biomedical information The query is parsed into a set of CycL higher-order logic fragments with open variables, then after applying various constraints medical domain knowledge, common sense, discourse pragmatics, syntax, there is a way to fit those fragments together, one semantically meaningful formal query


The Cyc project has been described as "one of the most controversial endeavors of the artificial intelligence history" Criticisms include:

  • The complexity of the system—arguably necessitated by its encyclopedic ambitions — and the consequent difficulty in adding to the system by hand
  • Scalability problems, from widespread reification, especially as constants
  • Unsatisfactory treatment of the concept of substance and the related distinction between intrinsic and extrinsic properties
  • The lack of any meaningful benchmark or comparison for the efficiency of Cyc's inference engine However see Ramachandran et al 2005
  • The current incompleteness of the system in both breadth and depth and the related difficulty in measuring its completeness
  • Limited documentation
  • The lack of up-to-date on-line training material makes it difficult for new people to learn the systems
  • A large number of gaps in not only the ontology of ordinary objects, but an almost complete lack of relevant assertions describing such object
  • Machine-learning scientist Pedro Domingos refers to the project as a "catastrophic failure" for several reasons, including the unending amount of data required to produce any viable results and the inability for Cyc to evolve on its own

Notable employees

This is a list of notable people who work or have worked on Cyc either as employees of MCC where Cyc was first started or Cycorp

  • Douglas Lenat
  • Michael Witbrock
  • Pat Hayes
  • Ramanathan V Guha
  • Stuart J Russell
  • Srinija Srinivasan
  • Jared Friedman

See also


  1. ^ Lenat, Douglas "Hal's Legacy: 2001's Computer as Dream and Reality From 2001 to 2001: Common Sense and the Mind of HAL" Cycorp, Inc Archived from the original on 2006-10-06 Retrieved 2006-09-26 
  2. ^ The Editors of Time-Life Books 1986 Understanding Computers: Artificial Intelligence Amsterdam: Time-Life Books p 84 ISBN 0-7054-0915-5 
  3. ^ "Cyc's Natural Language" 
  4. ^ "Cyc R&D" Retrieved 2009-02-19 
  5. ^ "Integrating Cyc and Wikipedia: Folksonomy meets rigorously defined common-sense" PDF Retrieved 2013-05-10 
  6. ^ "cyc Inference engine" Retrieved 2015-06-04 
  7. ^ The open source Texai project
  8. ^ Texai SourceForge project files
  9. ^ "The Comprehensive Terrorism Knowledge Base in Cyc" CiteSeerX 1011709247  Missing or empty |url= help; |access-date= requires |url= help
  10. ^ "DBpedia and Open-Cyc" Retrieved 2009-06-09 
  11. ^ Cyclopedia Sampleshowing cyc highlighted cyc concept for family
  12. ^ http://wwww3org/2001/sw/sweo/public/UseCases/ClevelandClinic/
  13. ^ http://wwwaaaiorg/ojs/indexphp/aimagazine/article/viewArticle/2299
  14. ^ Bertino, Piero & Zarri 2001, p 275
  15. ^ Ramachandran, Deepak "First-orderized Research Cyc: expressiveness and Efficiency in a Common Sense Knowledge Base" PDF Retrieved 26 May 2013 
  16. ^ Domingos, Pedro 2015 The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World ISBN 978-0465065707 

Further reading

  • Alan Belasco et al 2004 "Representing Knowledge Gaps Effectively" In: D Karagiannis, U Reimer Eds: Practical Aspects of Knowledge Management, Proceedings of PAKM 2004, Vienna, Austria, December 2–3, 2004 Springer-Verlag, Berlin Heidelberg
  • Elisa Bertino, Gian Piero & BC Zarria 2001 Intelligent Database Systems Addison-Wesley Professional
  • John Cabral & others 2005 "Converting Semantic Meta-Knowledge into Inductive Bias" In: Proceedings of the 15th International Conference on Inductive Logic Programming Bonn, Germany, August 2005
  • Jon Curtis et al 2005 "On the Effective Use of Cyc in a Question Answering System" In: Papers from the IJCAI Workshop on Knowledge and Reasoning for Answering Questions Edinburgh, Scotland: 2005
  • Chris Deaton et al 2005 "The Comprehensive Terrorism Knowledge Base in Cyc" In: Proceedings of the 2005 International Conference on Intelligence Analysis, McLean, Virginia, May 2005
  • Kenneth Forbus et al 2005 "Combining analogy, intelligent information retrieval, and knowledge integration for analysis: A preliminary report" In: Proceedings of the 2005 International Conference on Intelligence Analysis, McLean, Virginia, May 2005
  • douglas foxvog 2010, "Cyc" In: Theory and Applications of Ontology: Computer Applications", Springer
  • Fritz Lehmann and d foxvog 1998, "Putting Flesh on the Bones: Issues that Arise in Creating Anatomical Knowledge Bases with Rich Relational Structures" In: Knowledge Sharing across Biological and Medical Knowledge Based Systems, AAAI
  • Douglas Lenat and R V Guha 1990 Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project Addison-Wesley ISBN 0-201-51752-3
  • James Masters 2002 "Structured Knowledge Source Integration and its applications to information fusion" In: Proceedings of the Fifth International Conference on Information Fusion Annapolis, MD, July 2002
  • James Masters and Z Güngördü 2003 "Structured Knowledge Source Integration: A Progress Report" In: In Integration of Knowledge Intensive Multiagent Systems Cambridge, Massachusetts, USA, 2003
  • Cynthia Matuszek et al 2006 "An Introduction to the Syntax and Content of Cyc" In: Proc of the 2006 AAAI Spring Symposium on Formalizing and Compiling Background Knowledge and Its Applications to Knowledge Representation and Question Answering Stanford, 2006
  • Cynthia Matuszek et al 2005 "Searching for Common Sense: Populating Cyc from the Web" In: Proceedings of the Twentieth National Conference on Artificial Intelligence Pittsburgh, Pennsylvania, July 2005
  • Tom O'Hara et al 2003 "Inducing criteria for mass noun lexical mappings using the Cyc Knowledge Base and its Extension to WordNet" In: Proceedings of the Fifth International Workshop on Computational Semantics Tilburg, 2003
  • Fabrizio Morbini and Lenhart Schubert 2009 "Evaluation of EPILOG: a Reasoner for Episodic Logic" University of Rochester, Commonsense '09 Conference describes Cyc's library of ~1600 'Commonsense Tests'
  • Kathy Panton et al 2002 "Knowledge Formation and Dialogue Using the KRAKEN Toolset" In: Eighteenth National Conference on Artificial Intelligence Edmonton, Canada, 2002
  • Deepak Ramachandran P Reagan & K Goolsbey 2005 "First-Orderized ResearchCyc: Expressivity and Efficiency in a Common-Sense Ontology" In: Papers from the AAAI Workshop on Contexts and Ontologies: Theory, Practice and Applications Pittsburgh, Pennsylvania, July 2005
  • Stephen Reed and D Lenat 2002 "Mapping Ontologies into Cyc" In: AAAI 2002 Conference Workshop on Ontologies For The Semantic Web Edmonton, Canada, July 2002
  • Benjamin Rode et al 2005 "Towards a Model of Pattern Recovery in Relational Data" In: Proceedings of the 2005 International Conference on Intelligence Analysis McLean, Virginia, May 2005
  • Dave Schneider et al 2005 "Gathering and Managing Facts for Intelligence Analysis" In: Proceedings of the 2005 International Conference on Intelligence Analysis" McLean, Virginia, May 2005
  • Blake Shepard et al 2005 "A Knowledge-Based Approach to Network Security: Applying Cyc in the Domain of Network Risk Assessment" In: Proceedings of the Seventeenth Innovative Applications of Artificial Intelligence Conference Pittsburgh, Pennsylvania, July 2005
  • Nick Siegel et al 2004 "Agent Architectures: Combining the Strengths of Software Engineering and Cognitive Systems" In: Papers from the AAAI Workshop on Intelligent Agent Architectures: Combining the Strengths of Software Engineering and Cognitive Systems Technical Report WS-04-07, pp 74–79 Menlo Park, California: AAAI Press, 2004
  • Nick Siegel et al 2005 Hypothesis Generation and Evidence Assembly for Intelligence Analysis: Cycorp's Nooscape Application" In Proceedings of the 2005 International Conference on Intelligence Analysis, McLean, Virginia, May 2005
  • Michael Witbrock et al 2002 "An Interactive Dialogue System for Knowledge Acquisition in Cyc" In: Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence Acapulco, Mexico, 2003
  • Michael Witbrock et al 2004 "Automated OWL Annotation Assisted by a Large Knowledge Base" In: Workshop Notes of the 2004 Workshop on Knowledge Markup and Semantic Annotation at the 3rd International Semantic Web Conference ISWC2004 Hiroshima, Japan, November 2004, pp 71–80
  • Michael Witbrock et al 2005 "Knowledge Begets Knowledge: Steps towards Assisted Knowledge Acquisition in Cyc" In: Papers from the 2005 AAAI Spring Symposium on Knowledge Collection from Volunteer Contributors KCVC pp 99–105 Stanford, California, March 2005
  • William Jarrold 2001 "Validation of Intelligence in Large Rule-Based Systems with Common Sense" "Model-Based Validation of Intelligence: Papers from the 2001 AAAI Symposium" AAAI Technical Report SS-01-04
  • William Jarrold 2003 Using an Ontology to Evaluate a Large Rule Based Ontology: Theory and Practice NIST Special Publication 1014

External links

  • Cycorp homepage
  • Publications available from the Cycorp webpage
  • Opencycorg includes several tutorials
  • researchcyccom
  • The Cyc Foundation
  • Public access to OpenCyc Semantic Web Endpoints via a web browser
  • Cyc on SourceForgenet, the open source release of the top-level Cyc ontology release 10 created July 14, 2006
  • OpenCyc C API
  • Whatever happened to machines that think 23 April 2005, New Scientist
  • Common sense 15 April 2006, New Scientist
  • Official Cyc blog
  • Video Tutorials on Cyc

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