Pat Hayes

Last updated

Pat Hayes
Born
Patrick John Hayes

(1944-08-21) 21 August 1944 (age 79)
Newent, Gloucestershire, UK
CitizenshipUK
Education Bentley Grammar School
Alma mater University of Cambridge (BA)
University of Edinburgh (PhD)
Known forNaive Physics Manifesto [1] [2]
Awards AAAI Fellow (1990)
Scientific career
Fields Computer Science
Institutions Florida Institute for Human & Machine Cognition
University of Cambridge
University of Edinburgh
University of Illinois at Urbana-Champaign
University of Rochester
University of Essex
Thesis Semantic trees: new foundations for automatic theorem proving  (1975)
Doctoral advisor Bernard Meltzer [3]
Website ihmc.us/groups/phayes

Patrick John Hayes FAAAI (born 21 August 1944) 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. [4]

Contents

Education

Hayes was educated at the Bentley Grammar School, Calne.[ citation needed ] He studied the Cambridge Mathematical Tripos and received a Bachelor of Arts degree in mathematics from the University of Cambridge [ when? ] and a PhD in artificial intelligence on the topic of 'Semantic trees: New foundations for automatic theorem-proving' [5] from the University of Edinburgh. [6]

Career and research

Hayes has been an active, prolific, and influential figure in artificial intelligence for over five decades. [4] [7] [8] [9] [10] [11] He has a reputation for being provocative but also quite humorous. [ citation needed ]

One of his earliest publications, with John McCarthy, was the first thorough statement of the basis for the AI field of logical knowledge representation, introducing the notion of situation calculus, representation and reasoning about time, fluents, and the use of logic for representing knowledge in a computer. [12] [13]

Hayes next major contribution was the seminal work on the Naive Physics Manifesto, [1] which anticipated the expert systems movement in many ways and called for researchers in AI to actually try to represent knowledge in computers. Although not the first to mention the word "ontology" in computer science (that distinction belongs to John McCarthy [ citation needed ]), Hayes was one of the first to actually do it, and inspired an entire generation of researchers in knowledge engineering, logical formalisations of commonsense reasoning, and ontology[ citation needed ].

In the middle of the 1990s, while serving as president of the AAAI, Hayes began a series of attacks on critics of AI, mostly phrased in an ironic light, and (together with his colleague Kenneth Ford) invented an award named after Simon Newcomb to be given for the most ridiculous argument "disproving" the possibility of AI. The Newcomb Awards are announced in the AI Magazine published by AAAI.

At the turn of the century he became active in the Semantic Web community, contributing substantially (perhaps solely) to the revised semantics of RDF known as RDF-Core, one of the three designers (along with Peter Patel-Schneider and Ian Horrocks [14] ) of the Web Ontology Language semantics, and most recently contributed to SPARQL. He is also, along with philosopher Christopher Menzel the primary designer of the ISO Common Logic standard.

Hayes has served as secretary of AISB,[ when? ] chairman and trustee of IJCAI, associate editor of Artificial Intelligence, a governor of the Cognitive Science Society and president of American Association for Artificial Intelligence. Hayes is a charter Fellow of AAAI and of the Cognitive Science Society

According to his website, his current research interests include "knowledge representation and automatic reasoning, especially the representation of space and time; the semantic web; ontology design; and the philosophical foundations of AI and computer science". [15]

Related Research Articles

<span class="mw-page-title-main">Cyc</span> Artificial intelligence project

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, such as the application of rules or the relations of sets and subsets.

<span class="mw-page-title-main">Semantic Web</span> Extension of the Web to facilitate data exchange

The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable.

In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to 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 terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as applied ontology.

Description logics (DL) are a family of formal knowledge representation languages. Many DLs are more expressive than propositional logic but less expressive than first-order logic. In contrast to the latter, the core reasoning problems for DLs are (usually) decidable, and efficient decision procedures have been designed and implemented for these problems. There are general, spatial, temporal, spatiotemporal, and fuzzy description logics, and each description logic features a different balance between expressive power and reasoning complexity by supporting different sets of mathematical constructors.

The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects and the verbs representing relations between the objects.

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.

An annotation is extra information associated with a particular point in a document or other piece of information. It can be a note that includes a comment or explanation. Annotations are sometimes presented in the margin of book pages. For annotations of different digital media, see web annotation and text annotation.

<span class="mw-page-title-main">Logic in computer science</span> Academic discipline

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:

<span class="mw-page-title-main">Deborah McGuinness</span>

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.

<span class="mw-page-title-main">James Hendler</span> AI researcher

James Alexander Hendler is an artificial intelligence researcher at Rensselaer Polytechnic Institute, United States, and one of the originators of the Semantic Web. He is a Fellow of the National Academy of Public Administration.

Vasant G. Honavar is an Indian-American computer scientist, and artificial intelligence, machine learning, big data, data science, causal inference, knowledge representation, bioinformatics and health informatics researcher and professor.

<span class="mw-page-title-main">Ian Horrocks</span> British academic (b.1958)

Ian Robert Horrocks is a professor of computer science at the University of Oxford in the UK and a Fellow of Oriel College, Oxford. His research focuses on knowledge representation and reasoning, particularly ontology languages, description logic and optimised tableaux decision procedures.

<span class="mw-page-title-main">Frank van Harmelen</span>

Frank van Harmelen is a Dutch computer scientist and professor in Knowledge Representation & Reasoning in the AI department at the Vrije Universiteit Amsterdam. He was scientific director of the LarKC project (2008-2011), "aiming to develop the Large Knowledge Collider, a platform for very large scale semantic web reasoning."

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.

Amit Sheth is a computer scientist at University of South Carolina in Columbia, South Carolina. He is the founding Director of the Artificial Intelligence Institute, and a Professor of Computer Science and Engineering. From 2007 to June 2019, he was the Lexis Nexis Ohio Eminent Scholar, director of the Ohio Center of Excellence in Knowledge-enabled Computing, and a Professor of Computer Science at Wright State University. Sheth's work has been cited by over 48,800 publications. He has an h-index of 106, which puts him among the top 100 computer scientists with the highest h-index. Prior to founding the Kno.e.sis Center, he served as the director of the Large Scale Distributed Information Systems Lab at the University of Georgia in Athens, Georgia.

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.

Knowledge extraction is the creation of knowledge from structured and unstructured sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (NLP) and ETL, the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge or the generation of a schema based on the source data.

<span class="mw-page-title-main">Pascal Hitzler</span> German-American computer scientist

Pascal Hitzler is a German American computer scientist specializing in Semantic Web and Artificial Intelligence. He is endowed Lloyd T. Smith Creativity in Engineering Chair, one of the Directors of the Institute for Digital Agriculture and Advanced Analytics (ID3A) and Director of the Center for Artificial Intelligence and Data Science (CAIDS) at Kansas State University, and the founding Editor-in-Chief of the Semantic Web journal and the IOS Press book series Studies on the Semantic Web.

Sheila McIlraith is a Canadian computer scientist specializing in Artificial Intelligence (AI). She is a Professor in the Department of Computer Science, University of Toronto, Canada CIFAR AI Chair, and Associate Director and Research Lead of the Schwartz Reisman Institute for Technology and Society.

References

  1. 1 2 The naive physics manifesto in Michie, Donald (1979). Expert systems in the micro-electronic age. Edinburgh: Edinburgh University Press. ISBN   978-0-85224-381-7.
  2. Hayes, Patrick (1995). "The second naive physics manifesto". Computation & Intelligence. pp. 567–585. ISBN   978-0262621014.
  3. Pat Hayes at the Mathematics Genealogy Project OOjs UI icon edit-ltr-progressive.svg
  4. 1 2 Pat Hayes at DBLP Bibliography Server OOjs UI icon edit-ltr-progressive.svg
  5. Hayes, Patrick J. (1973). "Semantic trees: New foundations for automatic theorem-proving". Meltzer, Bernard. hdl:1842/8115.{{cite journal}}: Cite journal requires |journal= (help)
  6. Hayes, Patrick John (1975). Semantic trees: new foundations for automatic theorem proving (PhD thesis). University of Edinburgh. hdl:1842/8115. EThOS   uk.bl.ethos.586181. Lock-green.svg
  7. Hayes, P.; Eskridge, T. C.; Saavedra, R.; Reichherzer, T.; Mehrotra, M.; Bobrovnikoff, D. (2005). "Collaborative knowledge capture in ontologies". Proceedings of the 3rd international conference on Knowledge capture - K-CAP '05. p. 99. doi:10.1145/1088622.1088641. ISBN   978-1595931634. S2CID   15663316.
  8. Carroll, J. J.; Bizer, C.; Hayes, P.; Stickler, P. (2005). "Named graphs, provenance and trust". Proceedings of the 14th international conference on World Wide Web - WWW '05. p. 613. CiteSeerX   10.1.1.1.2197 . doi:10.1145/1060745.1060835. ISBN   978-1595930460. S2CID   207156699.
  9. Clark, P.; Hayes, P.; Reichherzer, T.; Thompson, J.; Barker, K.; Porter, B.; Chaudhri, V.; Rodriguez, A.; Thomere, J.; Mishra, S.; Gil, Y. (2001). "Knowledge entry as the graphical assembly of components". Proceedings of the international conference on Knowledge capture - K-CAP 2001. p. 22. CiteSeerX   10.1.1.24.9465 . doi:10.1145/500737.500745. ISBN   978-1581133806. S2CID   663883.
  10. Carroll, J. J.; Bizer, C.; Hayes, P.; Stickler, P. (2005). "Named graphs". Web Semantics: Science, Services and Agents on the World Wide Web. 3 (4): 247. doi:10.1016/j.websem.2005.09.001.
  11. Jensen, C. S.; Dyreson, C. E.; Böhlen, M.; Clifford, J.; Elmasri, R.; Gadia, S. K.; Grandi, F.; Hayes, P.; Jajodia, S.; Käfer, W.; Kline, N.; Lorentzos, N.; Mitsopoulos, Y.; Montanari, A.; Nonen, D.; Peressi, E.; Pernici, B.; Roddick, J. F.; Sarda, N. L.; Scalas, M. R.; Segev, A.; Snodgrass, R. T.; Soo, M. D.; Tansel, A.; Tiberio, P.; Wiederhold, G. (1998). "The consensus glossary of temporal database concepts — February 1998 version". Temporal Databases: Research and Practice. Lecture Notes in Computer Science. Vol. 1399. p. 367. doi:10.1007/BFb0053710. ISBN   978-3-540-64519-1.
  12. Shanahan, Murray (1997). Solving the frame problem: a mathematical investigation of the common sense law of inertia. MIT Press. p. 45. ISBN   978-0-262-19384-9 . Retrieved 12 November 2010.
  13. Hayes, Patrick J.; John McCarthy (1969). "Some philosophical problems from the standpoint of artificial intelligence". Machine Intelligence. 4: 463–502.
  14. Fikes, R.; Hayes, P.; Horrocks, I. (2004). "OWL-QL—a language for deductive query answering on the Semantic Web". Web Semantics: Science, Services and Agents on the World Wide Web. 2: 19–29. CiteSeerX   10.1.1.67.1967 . doi:10.1016/j.websem.2004.07.002.
  15. "Pat Hayes". IHMC | Institute for Human & Machine Cognition. Retrieved 30 January 2019.