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Cyc 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.
Knowledge representation and reasoning 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.
In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. Symbolic AI used tools such as logic programming, production rules, semantic nets and frames, and it developed applications such as knowledge-based systems, symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems. The Symbolic AI paradigm led to seminal ideas in search, symbolic programming languages, agents, multi-agent systems, the semantic web, and the strengths and limitations of formal knowledge and reasoning systems.
Logic in computer science covers the overlap between the field of logic and that of computer science. The topic can essentially be divided into three main areas:
Bart Selman is a Dutch-American professor of computer science at Cornell University. He is also co-founder and principal investigator of the Center for Human-Compatible Artificial Intelligence (CHAI) at the University of California, Berkeley, led by Stuart J. Russell, and co-chair of the Computing Community Consortium's 20-year roadmap for AI research.
Loom is a knowledge representation language developed by researchers in the artificial intelligence research group at the University of Southern California's Information Sciences Institute. The leader of the Loom project and primary architect for Loom was Robert MacGregor. The research was primarily sponsored by the Defense Advanced Research Projects Agency (DARPA).
Raymond Reiter was a Canadian computer scientist and logician. He was one of the founders of the field of non-monotonic reasoning with his work on default logic, model-based diagnosis, closed-world reasoning, and truth maintenance systems. He also contributed to the situation calculus.
Patrick John Hayes FAAAI is a British computer scientist who lives and works in the United States. As of March 2006, he is a senior research scientist at the Institute for Human and Machine Cognition in Pensacola, Florida.
Deborah Louise McGuinness is an American computer scientist and researcher at Rensselaer Polytechnic Institute (RPI). She is a professor of Computer, Cognitive and Web Sciences, Industrial and Systems Engineering, and an endowed chair in the Tetherless World Constellation, a multidisciplinary research institution within RPI that focuses on the study of theories, methods and applications of the World Wide Web. Her fields of expertise include interdisciplinary data integration, artificial intelligence, specifically in knowledge representation and reasoning, description logics, the semantic web, explanation, and trust.
Frames are an artificial intelligence data structure used to divide knowledge into substructures by representing "stereotyped situations". They were proposed by Marvin Minsky in his 1974 article "A Framework for Representing Knowledge". Frames are the primary data structure used in artificial intelligence frame languages; they are stored as ontologies of sets.
Hector Joseph Levesque is a Canadian academic and researcher in artificial intelligence. His research concerns incorporating commonsense reasoning in intelligent systems and he initiated the Winograd Schemas Challenge.
Vivid knowledge refers to a specific kind of knowledge representation.
AI@50, formally known as the "Dartmouth Artificial Intelligence Conference: The Next Fifty Years", was a conference organized by James Moor, commemorating the 50th anniversary of the Dartmouth workshop which effectively inaugurated the history of artificial intelligence. Five of the original ten attendees were present: Marvin Minsky, Ray Solomonoff, Oliver Selfridge, Trenchard More, and John McCarthy.
William Aaron Woods, generally known as Bill Woods, is a researcher in natural language processing, continuous speech understanding, knowledge representation, and knowledge-based search technology. He is currently a Software Engineer at Google.
Yahoo! Labs served as Yahoo!'s research arm, aiming to develop research in technologies to be used within the company. Yahoo! Labs included approximately 200 research scientists and engineers.
Michael Gelfond is a Professor in Computer Sciences at Texas Tech University in the United States. He received a degree in mathematics from the Steklov Institute of Mathematics in Russia in 1974 and emigrated to the United States in 1978. Gelfond's research interests are in the areas of computational logic and knowledge representation. He is a Fellow of the Association for the Advancement of Artificial Intelligence, and an Area Editor of the journal Theory and Practice of Logic Programming.
A deductive classifier is a type of artificial intelligence inference engine. It takes as input a set of declarations in a frame language about a domain such as medical research or molecular biology. For example, the names of classes, sub-classes, properties, and restrictions on allowable values. The classifier determines if the various declarations are logically consistent and if not will highlight the specific inconsistent declarations and the inconsistencies among them. If the declarations are consistent the classifier can then assert additional information based on the input. For example, it can add information about existing classes, create additional classes, etc. This differs from traditional inference engines that trigger off of IF-THEN conditions in rules. Classifiers are also similar to theorem provers in that they take as input and produce output via first-order logic. Classifiers originated with KL-ONE frame languages. They are increasingly significant now that they form a part in the enabling technology of the Semantic Web. Modern classifiers leverage the Web Ontology Language. The models they analyze and generate are called ontologies.
Action model learning is an area of machine learning concerned with creation and modification of software agent's knowledge about effects and preconditions of the actions that can be executed within its environment. This knowledge is usually represented in logic-based action description language and used as the input for automated planners.
Henry A. Kautz is a computer scientist, Founding Director of Institute for Data Science and Professor at University of Rochester. He is interested in knowledge representation, artificial intelligence, data science and pervasive computing.
Giuseppe De Giacomo is an Italian computer scientist. He is a Professor of Computer Science at the Department of Computer Science, University of Oxford, and Professor of Computer Engineering at the Department of Computer, Control and Management Engineering, Sapienza University of Rome. He is also a Senior Research Fellow at the Green Templeton College.
References
- ↑ "Ron Brachman Joins the Jacobs Technion-Cornell Institute at Cornell Tech as the New Director". Cornell Tech. 25 May 2016. Retrieved 2016-05-25.
- ↑ "Elected AAAI Fellows". AAAI. Retrieved 2024-01-01.
- ↑ The Westfield Leader, OUR 115th YEAR - ISSUE NO. 07-2005, February 17, 2005 http://www.digifind-it.com/westfield/leader/2005/2005-02-17.pdf
- ↑ Reiter, Ray; Brachman, Ronald J.; Levesque, Hector J. (1992). Knowledge representation. Cambridge, Mass: MIT Press. ISBN 978-0-262-52168-0.
- ↑ Levesque, Hector J.; Brachman, Ronald J. (2004). Knowledge representation and reasoning. Amsterdam: Elsevier/Morgan Kaufmann. ISBN 978-1-55860-932-7.
- ↑ Ronald J. Brachman publications indexed by Microsoft Academic
- ↑ Ronald J. Brachman at DBLP Bibliography Server
- ↑ Ronald J. Brachman (1983) "What IS-A is and isn't. An Analysis of Taxonomic Links in Semantic Networks"; IEEE Computer, 16 (10); October.
