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Cyc
Cyc (pronounced ) 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 that other AI platforms may take for granted. This is contrasted with facts one might find somewhere on the internet or retrieve via a search engine or Wikipedia. Cyc enables semantic reasoners to perform human-like reasoning and be less "brittle" when confronted with novel situations. Douglas Lenat began the project in July 1984 at MCC, where he was Principal Scientist 1984–1994, and then, since January 1995, has been under active development by the Cycorp company, where he is the CEO. Overview The need for a massive symbolic artificial intelligence project of this kind was born in the early 1980s. Early AI researchers had ample experience over the previous 25 years with AI programs that would generate e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SubL
Cyc (pronounced ) 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 that other AI platforms may take for granted. This is contrasted with facts one might find somewhere on the internet or retrieve via a search engine or Wikipedia. Cyc enables semantic reasoners to perform human-like reasoning and be less "brittle" when confronted with novel situations. Douglas Lenat began the project in July 1984 at MCC, where he was Principal Scientist 1984–1994, and then, since January 1995, has been under active development by the Cycorp company, where he is the CEO. Overview The need for a massive symbolic artificial intelligence project of this kind was born in the early 1980s. Early AI researchers had ample experience over the previous 25 years with AI programs that would generate e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Douglas Lenat
Douglas Bruce Lenat (born 1950) is the CEO of Cycorp, Inc. of Austin, Texas, and has been a prominent researcher in artificial intelligence; he was awarded the biannual IJCAI Computers and Thought Award in 1976 for creating the machine learning program, AM. He has worked on (symbolic, not statistical) machine learning (with his AM and Eurisko programs), knowledge representation, "cognitive economy", blackboard systems, and what he dubbed in 1984 " ontological engineering" (with his Cyc program at MCC and, since 1994, at Cycorp). He has also worked in military simulations, and numerous projects for US government, military, intelligence, and scientific organizations. In 1980, he published a critique of conventional random-mutation Darwinism. He authored a series of articles in the Journal of Artificial Intelligence exploring the nature of heuristic rules. Lenat was one of the original Fellows of the AAAI, and is the only individual to have served on the Scientific Advisor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CycL
CycL in computer science and artificial intelligence is an ontology language used by Doug Lenat's Cyc artificial intelligence project. Ramanathan V. Guha was instrumental in the design of early versions of the language. There is a close variant of CycL known as MELD. The original version of CycL was a frame language, but the modern version is not. Rather, it is a declarative language based on classical first-order logic, with extensions for modal operators and higher order quantification. CycL is used to represent the knowledge stored in the Cyc Knowledge Base, available from Cycorp. The source code written in CycL released with the OpenCyc system is licensed as open source, to increase its usefulness in supporting the semantic web. Basic ideas CycL has some basic ideas: * Naming the constants used to refer to information for represented concepts. * Grouping the constants together in a generalization/specialization hierarchy (usually called categorization). * Stating ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge Representation
Knowledge representation and reasoning (KRR, KR&R, KR²) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of ''reasoning'', such as the application of rules or the relations of sets and subsets. Examples of knowledge representation formalisms include semantic nets, systems architecture, frames, rules, and ontologies. Examples of automated reasoning engines include inference engines, theorem provers, and classifiers. History The earliest work in computerized knowledge rep ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ontology (information Science)
In computer science and information science, an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject. Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge. Each uses ontological assumptions to frame explicit theories, research and applications. New ontologies may improve problem solving within that domain. Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages. For instance, the definition and ontology of economics is a primary concern in Marxist econ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ontology (information Science)
In computer science and information science, an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject. Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge. Each uses ontological assumptions to frame explicit theories, research and applications. New ontologies may improve problem solving within that domain. Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages. For instance, the definition and ontology of economics is a primary concern in Marxist econ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Common Sense Knowledge
In artificial intelligence research, commonsense knowledge consists of facts about the everyday world, such as "Lemons are sour", that all humans are expected to know. It is currently an unsolved problem in Artificial General Intelligence. The first AI program to address common sense knowledge was Advice Taker in 1959 by John McCarthy. Commonsense knowledge can underpin a commonsense reasoning process, to attempt inferences such as "You might bake a cake because you want people to eat the cake." A natural language processing process can be attached to the commonsense knowledge base to allow the knowledge base to attempt to answer questions about the world.Liu, Hugo, and Push Singh. "ConceptNet—a practical commonsense reasoning tool-kit." BT technology journal 22.4 (2004): 211-226. Common sense knowledge also helps to solve problems in the face of incomplete information. Using widely held beliefs about everyday objects, or common sense knowledge, AI systems make common ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Microelectronics And Computer Technology Corporation
Microelectronics and Computer Technology Corporation, originally the Microelectronics and Computer Consortium and widely seen as the acronym MCC, was the first, and at one time one of the largest, computer industry research and development consortia in the United States. MCC ceased operations in 2000 and was formally dissolved in 2004. Divisions MCC did research and development in the following areas: * System Architecture and Design (optimise hardware and software design, provide for scalability and interoperability, allow rapid prototyping for improved time-to-market, and support the re-engineering of existing systems for open systems). * Advanced Microelectronics Packaging and Interconnection (smaller, faster, more powerful, and cost-competitive). * Hardware Systems Engineering (tools and methodologies for cost-efficient, up-front design of advanced electronic systems, including modelling and design-for-test techniques to improve cost, yield, quality, and time-to-market). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Higher-order Logic
mathematics and logic, a higher-order logic is a form of predicate logic that is distinguished from first-order logic by additional quantifiers and, sometimes, stronger semantics. Higher-order logics with their standard semantics are more expressive, but their model-theoretic properties are less well-behaved than those of first-order logic. The term "higher-order logic", abbreviated as HOL, is commonly used to mean higher-order simple predicate logic. Here "simple" indicates that the underlying type theory is the ''theory of simple types'', also called the ''simple theory of types'' (see Type theory). Leon Chwistek and Frank P. Ramsey proposed this as a simplification of the complicated and clumsy ''ramified theory of types'' specified in the ''Principia Mathematica'' by Alfred North Whitehead and Bertrand Russell. ''Simple types'' is nowadays sometimes also meant to exclude polymorphic and dependent types. Quantification scope First-order logic quantifies only variables ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Circumscription (logic)
Circumscription is a non-monotonic logic created by John McCarthy to formalize the common sense assumption that things are as expected unless otherwise specified. Circumscription was later used by McCarthy in an attempt to solve the frame problem. To implement circumscription in its initial formulation, McCarthy augmented first-order logic to allow the minimization of the extension of some predicates, where the extension of a predicate is the set of tuples of values the predicate is true on. This minimization is similar to the closed-world assumption that what is not known to be true is false. The original problem considered by McCarthy was that of missionaries and cannibals: there are three missionaries and three cannibals on one bank of a river; they have to cross the river using a boat that can only take two, with the additional constraint that cannibals must never outnumber the missionaries on either bank (as otherwise the missionaries would be killed and, presumably, eate ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Non-monotonic Logic
A non-monotonic logic is a formal logic whose conclusion relation is not monotonic. In other words, non-monotonic logics are devised to capture and represent defeasible inferences (cf. defeasible reasoning), i.e., a kind of inference in which reasoners draw tentative conclusions, enabling reasoners to retract their conclusion(s) based on further evidence. Most studied formal logics have a monotonic entailment relation, meaning that adding a formula to a theory never produces a pruning of its set of conclusions. Intuitively, monotonicity indicates that learning a new piece of knowledge cannot reduce the set of what is known. A monotonic logic cannot handle various reasoning tasks such as reasoning by default (conclusions may be derived only because of lack of evidence of the contrary), abductive reasoning (conclusions are only deduced as most likely explanations), some important approaches to reasoning about knowledge (the ignorance of a conclusion must be retracted when the conc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fifth Generation Computer Systems
The Fifth Generation Computer Systems (FGCS) was a 10-year initiative begun in 1982 by Japan's Ministry of International Trade and Industry (MITI) to create computers using massively parallel computing and logic programming. It aimed to create an "epoch-making computer" with supercomputer-like performance and to provide a platform for future developments in artificial intelligence. FGCS was ahead of its time and a commercial failure. FGCS contributed greatly to the field of concurrent logic programming. The term "fifth generation" was intended to convey the system as being advanced. In the history of computing hardware, computers using vacuum tubes were called the first generation; transistors and diodes, the second; integrated circuits, the third; and those using microprocessors, the fourth. Whereas previous computer generations had focused on increasing the number of logic elements in a single CPU, the fifth generation, it was widely believed at the time, would instead tu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
