Adrian Walker (computer scientist)

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Adrian David Walker is a US Computer Scientist, born in London, England.

Contents

Education

Adrian Walker attended Dartington Hall School, an experimental boarding school in England where attendance at classes was optional. He obtained a bachelor's degree in electrical engineering at Sheffield University (where he also chaired the Arts Society and edited a poetry magazine), and a master's degree in systems engineering [1] from the University of Surrey. He next obtained a PhD in computer science [2] from the State University of New York.

Career

He was assistant professor at Rutgers university in New Jersey, [3] then Member of Technical Staff at Bell Labs. He moved to the IBM Almaden Research Center in California as a Research Staff Member [4] then to the IBM Thomas J. Watson Research Center in Yorktown NY as manager of Principles and Applications of Logic Programming. [5] [6] After 17 years at IBM, he formed his own company, where he works on Internet Business Logic, [7] a system for social knowledge acquisition and use in executable English.

Selected work: Walker's early work [8] [9] established a novel correspondence between stable patterns in formalised biological systems and the well known Chomsky hierarchy of languages—regular, context free, and context sensitive. He continued in grammar-based research [10] by showing how Bayes' theorem can be used to fit a stochastic regular grammar to a collection of data, a result that can be used to inductively infer hidden Markov models. Walker next showed [11] [12] [13] that, under certain practically useful assumptions, it is possible to compute the semantics of sets of syllogism-like rules in open vocabulary, largely open syntax English, in such a way as to answer English questions put to databases. This relaxes an onerous assumption made in many computational natural language understanding systems—namely, that the vocabulary must be narrowly restricted to obtain a useful level of understanding. A logical theory of knowledge developed in [14] [15] is applied in a system on the Web (reference 7, below) that combines three kinds of semantics – (a) data, as in SQL or Resource Description Framework, (b) inference, and (c) English, to answer questions over networked databases, and to explain the results in hypertexted English. The subject knowledge needed to do this (e.g. knowledge about the oil industry, or about energy independence, etc.) can be captured in social network style, by typing executable English into browsers. This contrasts with other social media, such as Twitter and Facebook, in which knowledge written in English is readable, but cannot be executed as a computer program.

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Cyc

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.

Formal language Sequence of words formed by specific rules

In logic, mathematics, computer science, and linguistics, a formal language consists of words whose letters are taken from an alphabet and are well-formed according to a specific set of rules.

The following outline is provided as an overview and topical guide to linguistics:

Programming language Language for communicating instructions to a machine

A programming language is any set of rules that converts strings, or graphical program elements in the case of visual programming languages, to various kinds of machine code output. Programming languages are one kind of computer language, and are used in computer programming to implement algorithms.

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.

Natural-language understanding (NLU) or natural-language interpretation (NLI) is a subtopic of natural-language processing in artificial intelligence that deals with machine reading comprehension. Natural-language understanding is considered an AI-hard problem.

In computer science, specifically software engineering and hardware engineering, formal methods are a particular kind of mathematically rigorous techniques for the specification, development and verification of software and hardware systems. The use of formal methods for software and hardware design is motivated by the expectation that, as in other engineering disciplines, performing appropriate mathematical analysis can contribute to the reliability and robustness of a design.

The denotation of a word is its central sense and the entire set of objects that can be contained in the word's meaning. Denotation is sometimes contrasted to connotation, which includes associated meanings and pragmatic inferences, because the denotational meaning of a word is perceived through visible concepts, whereas connotational meaning evokes sensible attitudes towards the phenomena. This concept is relevant in several fields, including linguistics, philosophy, and computer science. From a philosophical standpoint, exploration of meaning as it relates to denotation is important in the study of the philosophy of language.

Conceptual graph

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Controlled natural languages (CNLs) are subsets of natural languages that are obtained by restricting the grammar and vocabulary in order to reduce or eliminate ambiguity and complexity. Traditionally, controlled languages fall into two major types: those that improve readability for human readers , and those that enable reliable automatic semantic analysis of the language.

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Grammar induction

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Donkey sentences are sentences that contain a pronoun with clear meaning but whose syntactical role in the sentence poses challenges to grammarians. Such sentences defy straightforward attempts to generate their formal language equivalents. The difficulty is with understanding how English speakers parse such sentences.

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References

  1. ↑ "Archived copy". Archived from the original on 27 June 2011. Retrieved 16 July 2011.{{cite web}}: CS1 maint: archived copy as title (link)
  2. ↑ Formal grammars and the stability of biological systems. PhD Thesis. Technical Report Number 85, Department of Computer Science, State University of New York, 1974.
  3. ↑ Research resource in AI and biomedicine at Rutgers University
  4. ↑ R*: An overview of the architecture
  5. ↑ Adrian Walker – ACM author profile page
  6. ↑ Knowledge Systems and Prolog: Developing Expert, Database, and Natural Language Systems, book, second edition, Addison-Wesley, 1990, (with M. McCord, J. Sowa and W. Wilson).
  7. ↑ A Wiki for Business Rules in Open Vocabulary, Executable English. White paper, Reengineering LLC. Findable via Google, or "Archived copy" (PDF). Archived from the original (PDF) on 27 March 2012. Retrieved 30 June 2011.{{cite web}}: CS1 maint: archived copy as title (link)
  8. ↑ Formal grammars and the stability of biological systems. Ph.D. Thesis. Technical Report Number 85, Department of Computer Science, State University of New York, 1974.
  9. ↑ Formal grammars and the regeneration capability of biological systems. Journal of Computer and System Sciences Volume 11, Issue 2, October 1975.
  10. ↑ On the inference of stochastic regular grammars (with A Van der Mude). Information and Control, Volume 38, Issue 3, September 1978.
  11. ↑ Syllog: a knowledge-based data management system. Report No. 34, Department of Computer Science, New York University, 1981.
  12. ↑ People Oriented Software Technology, and its Use in Environmental Reporting. (with Terry Krueger, George Kurian, Anil Nair, Gustaf Neumann, Ulrich Neumerkel, Stefan Nusser, Peter Reintjes, Andrew Taylor, and Daphne Tzoar). Proc. 6th International Conference and Workshop on Database and Expert Systems, September 1995.
  13. ↑ Semantics and the Web: e-Government Implications of some Emerging Technology Beyond W3C. Presentation for the Collaborative Expedition Workshop #35, 14 September 2004, at NSF: Design Workshop to Frame National Dialogue on Intelligent Information Use in Manufacturing and Implications for e-Government. Findable via Google.
  14. ↑ Towards a Theory of Declarative Knowledge, (with K. Apt and H. Blair). In: Foundations of Deductive Databases and Logic Programming, J. Minker (Ed.), Morgan Kaufmann 1988.
  15. ↑ Backchain Iteration: Towards a Practical Inference Method that is Simple Enough to be Proved Terminating, Sound and Complete. Journal of Automated Reasoning, 11:1–22, 1993.
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