The notion of context arises in assorted areas of artificial intelligence (AI), including knowledge representation, natural language processing, intelligent information retrieval, etc. Although the term ‘context’ is frequently employed in descriptions, explanations, and analyses of computer programs in these areas, its meaning is frequently left to the reader’s understanding. -/- My aim in this paper is to offer a swift review of context in AI. I will first identify the role of context in various fields of AI. I will then (...) consider the enterprise of formalising context. The focus of my discussion will be McCarthy's (1993) proposal – a landmark study that inspired almost every logical theory of context since then – and its close variants, studied by his students. -/- (The author is grateful to Prof. Carlo Penco for his invaluable assistance with this work.). (shrink)

P.F. Strawson proposed in the early seventies a threefold distinction regarding how context bears on the meaning of "what is said" when a sentence is uttered. The proposal was somewhat tentative and, being aware of this aspect, Strawson himself raised various questions to make it more adequate. In this paper, we review Strawson's scheme, note his concerns, and add some of our own. We also defend its essence and recommend it as an insightful entry point re the interplay of intended (...) meaning and context. (shrink)

In the last decade the concept of context has been extensivelyexploited in many research areas, e.g., distributed artificialintelligence, multi agent systems, distributed databases, informationintegration, cognitive science, and epistemology. Three alternative approaches to the formalization of the notion ofcontext have been proposed: Giunchiglia and Serafini's Multi LanguageSystems (ML systems), McCarthy's modal logics of contexts, andGabbay's Labelled Deductive Systems.Previous papers have argued in favor of ML systems with respect to theother approaches. Our aim in this paper is to support these arguments froma (...) theoretical perspective. We provide a very general definition of ML systems, which covers allthe ML systems used in the literature, and we develop a proof theoryfor an important subclass of them: the MR systems. We prove variousimportant results; among other things, we prove a normal form theorem,the sub-formula property, and the decidability of an importantinstance of the class of the MR systems. The paper concludes with a detailed comparison among the alternativeapproaches. (shrink)

This paper discusses how facet-like structures occur as a commonplace feature in a variety of computer science disciplines as a means for structuring class hierarchies. The paper then focuses on a mathematical model for facets (and class hierarchies in general), called formal concept analysis, and discusses graphical representations of faceted systems based on this model.

In this paper, an objective conception of contexts based loosely upon situation theory is developed and formalized. Unlike subjective conceptions, which take contexts to be something like sets of beliefs, contexts on the objective conception are taken to be complex, structured pieces of the world that (in general) contain individuals, other contexts, and propositions about them. An extended first-order language for this account is developed. The language contains complex terms for propositions, and the standard predicate "ist" that expresses the relation (...) that holds between a context and a proposition just in case the latter is true in the former. The logic for the objective conception features a global classical predicate calculus, a local logic for reasoning within contexts, and axioms for propositions. The specter of paradox is banished from the logic by allowing "ist" to be nonbivalent in problematic cases: it is not in general the case, for any context c and proposition p, that either ist(c,p) or ist(c, ¬p). An important representational capability of the logic is illustrated by proving an appropriately modified version of an illustrative theorem from McCarthy's classic Blocks World example. (shrink)

Testing the validity of knowledge requires formal expression of that knowledge. Formality of an expression is defined as the invariance, under changes of context, of the expression's meaning, i.e. the distinction which the expression represents. This encompasses both mathematical formalism and operational determination. The main advantages of formal expression are storability, universal communicability, and testability. They provide a selective edge in the Darwinian competition between ideas. However, formality can never be complete, as the context cannot be eliminated. Primitive terms, observation (...) set-ups, and background conditions are inescapable parts of formal or operational definitions, that all refer to a context beyond the formal system. Heisenberg's Uncertainty Principle and Gödel's Theorem provide special cases of this more universal limitation principle. Context-dependent expressions, on the other hand, have the benefit of being more flexible, intuitive and direct, and putting less strain on memory. It is concluded that formality is not an absolute property, but a context-dependent one: different people will apply different amounts of formality in different situations or for different purposes. Some recent computational and empirical studies of formality and contexts illustrate the emerging scientific investigation of this dependence. (shrink)

Papers in this special issue were written upon invitation. They were then subjected to the usual refereeing process of the Journal of Pragmatics. While we have attempted to cover almost all important areas in which context is employed as a conceptual apparatus, our coverage is clearly limited in scope. Accordingly, instead of a general updated overview of the use of context in every conceivable specific field (let's say the state-of-the-art of interdisciplinary research on context: a colossal/impossible enterprise!), we will offer (...) the readers of this special issue an introduction to the problems involved in the study of context by way of eight papers encompassing eight different areas. These are (in alphabetical order): artificial intelligence, bilingualism, child development, cognitive science, conversation analysis, neuroscience, philosophy of language, and pragmatics. Our goal is to propose a multi-faceted view of context, and to stimulate further investigations of this fertile topic, which permeates our lives. (shrink)

Situated semantics can be regarded as an attempt at placing situational context (context of situation) at the center of all discussions of meaning. Situation theory is a theory of information content that takes context very seriously. Individuals, properties, relations, and spatiotemporal locations are basic constructs of situation theory. Individuals are conceived as invariants; having properties and standing in relations, they tend to persist in time and space. An anchoring function binds the location parameters to appropriate objects present in the grounding (...) situation. Anchoring plays a major role in the working of constraints that include nomic constraints, conventional constraints and conditional constraints. Situation semantics develops a theory of meaning that is based on relations between situations. Situation semantics provides a fundamental framework for realistic semantics. The ideas emerging from research into situation semantics have been combined with linguistic work and have led to numerous useful proposals. (shrink)