Formal language

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

Mathematical Methods in Linguistics

Abstract: Preface. Part A. Set Theory. 1. Basic Concepts of Set Theory. 2. Relations and Functions. 3. Properties of Relations. 4. Infinities. Appendix A1. Part B. Logic and Formal Systems. 5. Basic Concepts of Logic. 6.Statement Logic. 7. Predicate Logic. 8. Formal Systems, Axiomatization, and Model Theory. Appendix B1. Appendix BII. Part C. Algebra. 9. Basic Concepts of Algebra. 10. Operational Structures. 11. Lattices. 12. Boolean and Heyting Algebras. Part D. English as a Formal Language. 13. Basic Concepts of Formal Languages. 14. Generalized Quantifiers. 15. Intensionality. Part E. Languages, Grammars, and Automata. 16. Basic Concepts of Languages, Grammars, and Automata. 17. Finite Automata, Regular Languages and Type 3 Grammars. 18. Pushdown Automata, Context-Free Grammars and Languages. 19. Turing Machines, Recursively Enumberable Languages, and Type 0 Grammars. 20. Linear Bounded Automata, Context-Sensitive Languages and Type 1 Grammars. 21. Languages Between Context-Free and Context-Sensitive. 22. Transformational Grammars. Appendix EI. Appendix EII. Review Problems. Index.

A deduction model of belief

Abstract: Representing and reasoning about the knowledge an agent (human or computer) must have to accomplish some task is becoming an increasingly important issue in artificial intelligence (AI) research. To reason about an agent's beliefs, an AI system must assume some formal model of those beliefs. An attractive candidate is the Deductive Belief model: an agent's beliefs are described as a set of sentences in some formal language (the base sentences), together with a deductive process for deriving consequences of those beliefs. In particular, a Deductive Belief model can account for the effect of resource limitations on deriving consequences of the base set: an agent need not believe all the logical consequences of his beliefs. In this paper we develop a belief model based on the notion of deduction, and contrast it with current AI formalisms for belief derived from Hintikka/Kripke possible-worlds semantics for knowledge.

Towards a mathematical operational semantics

Abstract: We present a categorical theory of 'well-behaved' operational semantics which aims at complementing the established theory of domains and denotational semantics to form a coherent whole. It is shown that, if the operational rules of a programming language can be modelled as a natural transformation of a suitable general form, depending on functorial notions of syntax and behaviour, then one gets the following for free: an operational model satisfying the rules and a canonical, internally fully abstract denotational model which satisfies the operational rules. The theory is based on distributive laws and bialgebras; it specialises to the known classes of well-behaved rules for structural operational semantics, such as GSOS.

BLOG: probabilistic models with unknown objects

Abstract: This paper introduces and illustrates BLOG, a formal language for defining probability models over worlds with unknown objects and identity uncertainty. BLOG unifies and extends several existing approaches. Subject to certain acyclicity constraints, every BLOG model specifies a unique probability distribution over first-order model structures that can contain varying and unbounded numbers of objects. Furthermore, complete inference algorithms exist for a large fragment of the language. We also introduce a probabilistic form of Skolemization for handling evidence.

An axiomatic basis for computer programming

Abstract: In this paper an attempt is made to explore the logical foundations of computer programming by use of techniques which were first applied in the study of geometry and have later been extended to other branches of mathematics. This involves the elucidation of sets of axioms and rules of inference which can be used in proofs of the properties of computer programs. Examples are given of such axioms and rules, and a formal proof of a simple theorem is displayed. Finally, it is argued that important advantages, both theoretical and practical, may follow from a pursuance of these topics.