Formal language

About: Formal language is a research topic. Over the lifetime, 5763 publications have been published within this topic receiving 154114 citations.

Artificial grammar learning meets formal language theory: an overview

Abstract: Formal language theory (FLT), part of the broader mathematical theory of computation, provides a systematic terminology and set of conventions for describing rules and the structures they generate, along with a rich body of discoveries and theorems concerning generative rule systems. Despite its name, FLT is not limited to human language, but is equally applicable to computer programs, music, visual patterns, animal vocalizations, RNA structure and even dance. In the last decade, this theory has been profitably used to frame hypotheses and to design brain imaging and animal-learning experiments, mostly using the ‘artificial grammar-learning’ paradigm. We offer a brief, non-technical introduction to FLT and then a more detailed analysis of empirical research based on this theory. We suggest that progress has been hampered by a pervasive conflation of distinct issues, including hierarchy, dependency, complexity and recursion. We offer clarifications of several relevant hypotheses and the experimental designs necessary to test them. We finally review the recent brain imaging literature, using formal languages, identifying areas of convergence and outstanding debates. We conclude that FLT has much to offer scientists who are interested in rigorous empirical investigations of human cognition from a neuroscientific and comparative perspective.

Natural language question-answering systems: 1969

Abstract: Recent experiments in programming natural language question-answering systems are reviewed to summarize the methods that have been developed for syntactic, semantic, and logical analysis of English strings. It is concluded that at least minimally effective techniques have been devised for answering questions from natural language subsets in small scale experimental systems and that a useful paradigm has evolved to guide research efforts in the field. Current approaches to semantic analysis and logical inference are seen to be effective beginnings but of questionable generality with respect either to subtle aspects of meaning or to applications over large subsets of English. Generalizing from current small-scale experiments to language-processing systems based on dictionaries with thousands of entries—with correspondingly large grammars and semantic systems—may entail a new order of complexity and require the invention and development of entirely different approaches to semantic analysis and question answering.

Formal Syntax and Semantics of Programming Languages: A Laboratory Based Approach

Abstract: From the Publisher: Formal Syntax and Semantics of Programming Languages: A Laboratory Based Approach presents a panorama of techniques in formal syntax, operational semantics and formal semantics. Using a teaching/learning perspective rather than a research-oriented approach, an understanding of the meta-languages is accessible to anyone with a basic grounding in discrete mathematics and programming language concepts. Throughout the book, valuable hands-on laboratory exercises provide the opportunity for practical application of difficult concepts. Various exercises and examples, implementing syntactic and semantic specifications on real systems, give students hands-on practice. Supplemental software is available on disk or via file transfer protocol. This book is suitable for an advanced undergraduate or introductory graduate level course on the formal syntax and semantics of programming languages.

Supporting knowledge-base evolution with incremental formalization

Abstract: A number of systems have been built which integrate the knowledge representations of hypermedia and knowledge-based systems. Experiences with such have shown users are willing to use the semi-formal mechanisms of such systems systems leaving much structure implicit rather than use the formal mechanisms provided. The problem remains that it is hard (1) to encode knowledge in the formal languages required by knowledge-based systems and (2) to provide support with the semi-formal knowledge found in hypermedia systems. Incremental formalization enables users to enter information into the system in an informal or semi-formal representation and to have computer support for the formalization of this information. The domain independent Hyper-Object Substrate (HOS) differs from other systems that integrate hypermedia and knowledge-based system styles of representations in that it enables the incremental addition of formalism to any piece of information in the system. HOS actively supports incremental formalization with a set of tools which suggest new formalizations to be added to the information space. These suggestions are based on patterns in the informally and semi-formally represented information and the existing formalized knowledge in the information space. An important assumption is that suggestions need not be completely accurate to be of general benefit to users. These suggestions provide a starting point which can be edited, thus changing part of of formalization from creation to modification. XNetwork, an environment the process supporting the design of computer networks, is one of several applications that have been created with HOS. Experiences with HOS show that its flexibility for incrementally adding and formalizing information is useful for the rapid prototyping and modification of semi-formal information spaces.