Buvac, S.: 1996, `Quantificational Logic of Context'. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence. Portland, OR, pp. 600--606.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....computers context aware is an idea that attracts more and more researchers within the computer science communities to the field of context aware computing. Researchers in the field of Artificial Intelligence are trying to formalize the notion of context and formalize reasoning using context [32, 8, 2, 19, 5, 7]. Researchers in the fields of Human Computer Interaction, Mobile Computing, and Ubiquitous Computing are building prototype context aware systems for use in various settings [45, 46, 4, 1, 14, 11, 3, 31, 40] For example, Cyberguide is a mobile context aware tour guide developed at George Tech. ....

Sasa Buvac. Quantificational logic of context. In AAAI/IAAI, Vol. 1, pages 600--606, 1996.

....and strongly tied with the language syntax [8] This only allows us to construct systems based on a specific language with out any portability to other languages. Recently a new paradigm of natural language processing is developed that is based on context but free from grammar or composition [9, 10, 11, 12, 13]. This gives a hope of a system capable of interpreting different languages at the same time in a particular context. Since the Asian languages are very symbolic in nature, a context based system is the most suited method of extracting and representing semantics independent of grammatical or ....

S. Buvac, "Quantificational logic of context," Proceedings of 13 th National Conference on Artificial Intelligence, AAAI, 1996.

.... integration is (Catarci and Lenzerini, 1993) The DWQ project has also produced analyses of query rewriting in languages with regular expressions (Calvanese et al. 2000) and aggregates (Nutt et al. 1998) Perhaps the most general approach to information integration is given by context logic (Buvac, 1996; Guha, 1991) which extends the predicate calculus with a new modality, ist c OE) meaning that a logical sentence OE is true in a context c. The logic is sound and complete, but undecidable. Lifting axioms relate formulas in different contexts, similarly to the view definitions above. The ....

Buvac, S.: 1996, `Quantificational Logic of Context'. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence.

....stating the preconditions and the effects of flying from a city 4 McCarthy and his group proposed a formalization of context that is meant to deal with all these problems. The reader interested in this approach may refer to [24, 14] for the general intuitions and many motivating examples, and to [4, 3] for a semantics of a propositional and quantificational logic of context based on an extension of a Kripke semantics. The basic intuitions are: context must be reified as reasoning objects (so that, for instance, we can write formulae like ist(c; w) whose intended meaning is that the formula ....

S. Buvac. Quantificational Logic of Contexts. In P. Brezillon and S. Abu-Hakima, editors, Proc. of the IJCAI-95 Workshop on "Modelling Context in Knowledge Representation and Reasoning", pages 25--34, 1995.

....study seems to be more appropriate. There are possible links between NCGs and contextual reasoning [21] although contextual reasoning is not our goal here. But both logical semantics mentioned above do not seem to be close to one of the logical formalizations of contextual reasoning (e.g. 22] [23]) However, a more in depth comparison has to be done. Acknowledgments We would like to thank G. Kerdiles and E. Salvat for their comments on a previous version of this paper, and specially G. simonet for her suggestions that greatly improved clarity of this work. ....

S. Buvac, Quantificational Logic of Context, in Proceedings AAAI'96, 600606, 1996.

.... of contexts (the set of contexts is treestructured, contextual formulas are restricted to existential positive conjunctive FOL formulas) But none of the logical semantics proposed in this paper seem to be close to one of the logical formalizations of contextual reasoning (e.g. McC93] Guh91] Buv96] However, more in depth comparisons will now have to be done. 8 Conclusion In this paper, a graph based model for hierarchical structured knowledge, nested graphs , is presented. Projection a labelled nested graph morphism is the main reasoning tool. The model is given two FOL ....

S. Buvac. Quantificational Logic of Context. In Proc. AAAI'96, pages 600---606, 1996.

....arbitrary local agents to use the mechanisms of logics of context to state hypothesis about their relation with other (local) agents. We take the approach of contexts as founded in [ McCarthy, 1987 ] and [ Giunchiglia and Ghidini, 1998 ] and taken into practice in the logics of contexts (LCs) Buvac, 1996 ] Ghidini and Serafini, 1998a ] or [ Nayak, 1995 ] We consider agents formalized as contexts. In the field of agents, contexts have been used to formalize reasoning about belief ( Giunchiglia and Serafini, 1994 ] and [ Benerecetti et al. 1997 ] or information integration ( Ghidini ....

....behind section 3.3 was to show how the notion of distinguishability could be formalized within a certain logic of context and we used DFOL for that. Besides different technical issues we might have encountered, we could have used other logic, such as the Quantificational Logic of Context (QLC, Buvac, 1996 ] to fulfill the same background goals. QLC and DFOL offer different approaches to provide specific means for stating relations between contexts. Although they start off from different underlying assumptions, both of them provide concrete logics which follow the principles behind the notion of ....

S. Buvac. Quantificational logic of context. In Proc. 13 th National Conference on Artificial Intelligence (AAAI-96), pages 600--606, Portland, Oregon, 1996.

....does not seem justified, even for the applications they consider. There is no reason why a database should have complete information about the contents of other databases. Buvac (Buvac 1994) has investigated decidability, while (Massacci 1996) has considered complexity for a certain fragment. (Buvac 1996) considers a simple notion of quantification over contexts in , which corresponds to our first completeness theorem, with the assumption 2 1 2 2 OE 2 1 :2 2 OE, and a 5 like assumption that multiple modalities may always be reduced to a single modality. 12 Similar systems to this (Gabbay and ....

Buvac, S. 1996. Quantificational logic of context. In Proceedings of the Thirteenth National Conference on Artificial Intelligence.

....is, their systems assume, 2 1 2 2 OE2 1 :2 2 OE. This axiom does not seem justified, even for the applications they consider. There is no reason why a database should have complete information about the contents of other databases. This limitation has been noticed by (Attardi and Simi 1995a) (Buvac 1996) considers a simple notion of quantification over contexts, which corresponds to our first completeness theorem, with the assumption 2 1 2 2 OE 2 1 :2 2 OE, and a 5 like assumption that multiple modalities may always be reduced to a single modality. Similar systems to this (Gabbay and Nossum ....

Buvac, S. 1996. Quantificational logic of context. In Proceedings of the Thirteenth National Conference on Artificial Intelligence.

....formulate a contextual query by selecting pointers from the local and global textual context. The query formulator assists the client request for additional contextual information by presenting a form describing the actual queries provided to the MetaCrawler. A contextual structure, as defined in [Buvac 1996] Source 1 Source n Source Model n Source 2 Source Model 2 Source Model 1 USER Query Formulator browser Explanation Generator Inference System Knowledge Base Presenter WWWeb Retrieved text segment Context Model Retrieved text segment Retrieved text segment MetaCrawler MetaCrawler MetaCrawler ....

....the feedback of the contextual structures on the initial WordNet based classification rules. They represent the input of the algorithm detailed in [Harabagiu and Moldovan 1997 1] which infers the contextual structures of a given text. We consider the formal definition of a context as given in [Buvac 1996], where a context is viewed as a collection of first order structures, satisfied by any atom assumed to be true in that context. We accommodate this definition in the semantic space provided by WordNet, by identifying the contextual structures with any relation from the extended WordNet (or ....

S. Buvac. Quantificational Logic of Context. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, AAAI-96, pages 600--606, 1996.

....Objects McCarthy has introduced in [McCarthy, 1993] contexts as formal objects for artificial intelligence by investigating their logical properties from a purely mathematical point of view. A classical propositional logic of contexts was developed, extended now to the quantificational case [Buvac, 1996]. The theory is based on the ist modality: ist(c; p) is true iff p is true within the scope of the context c. The usage of the ist as a validity measure corresponds to Guha s proposal of context semantics, motivated by the CYC knowledge base. As WordNet 1.6 does not represent contextual ....

....like Green and Carberry s reasoning model for indirect answers (reported in [Green and Carberry, 1994] shows that Grice s theory, like many other discourse logic models is rather too informal than inadequate. In contrast with Grice s logic, the quantificational logic of contexts developed by Buvac [Buvac, 1996] is a clear, precise formal theory. Therefore, a reformulation of Grice s principles via Buvac like axioms meets the requirements set by Frederking: correct, detailed mathematic descriptions, preceded by a correct general theory. The axioms presented here were suggested by the study of the ....

Buvac, S. (1996). Quantificational logic of context. In Proceedings of the 13th National Conference on Artificial Intelligence (AAAI-96), pages 600--606, Menlo Park, CA. AAAI Press.

....We can straightforwardly determine when a user query cannot be answered. More importantly, we can easily identify the classes with missing information, and, consequently, we can guide the query relaxation. Perhaps the most general approach to information integration is given by context logic [7, 13], which extends the predicate calculus with a new modality, ist c OE) meaning that a logical sentence OE is true in a context c. The logic is sound and complete, but undecidable. Lifting axioms relate formulas in different contexts, similarly to the view definitions above. The Carnot system [8] ....

Sasa Buvac. Quantificational logic of context. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, 1996.

....a mathematical viewpoint. They investigate the logical properties of contexts. They use the modality ist(c; p) to denote contextdependent truth and extend the classical propositional logic to what they call the propositional logic of context. The quantificational logic of context is treated in [14]. In their proposal, each context is considered to have its own vocabulary a set of propositional atoms which are defined (or meaningful) in that context. S. Buvac and Mason discuss the syntax and semantics of a general propositional language of context, and give a Hilbert style proof system ....

S. Buvac. Quantificational logic of context. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, 1996.

....provide complete answers. SIMS can straightforwardly determine when a user query cannot be answered. More importantly, SIMS can point to which classes of information it is missing and guide query relaxation. Perhaps the most general approach to information integration is given by context logic [7, 11] which extends the predicate calculus with a new modality, ist c OE) meaning that a logical sentence OE is true in a context c. The logic is sound and complete but undecidable. Lifting axioms relate formulas in different contexts, similarly to the view definitions above. The Carnot system [8] ....

Sasa Buvac. Quantificational logic of context. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, 1996.

....for various extensions of the general systems, we show that our propositional logic is decidable, and give a comparison to Kripke s possible worlds semantics. We also discuss some extensions and applications of our logics. Many of the results of this thesis have been previously published in [49, 19, 12, 11, 15, 14, 18]. See also [16] 1.1 Notation We use standard mathematical notation. If X and Y are sets, then X p Y is the set of partial functions from X to Y . P(X) is the set of subsets of X. X is the set of all finite sequences, and we let x = x 1 ; x n ] range over X . ffl is the empty ....

Sasa Buvac. Quantificational logic of context. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, 1996.

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Buvac, S.: 1996, `Quantificational Logic of Context'. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence. Portland, OR, pp. 600--606.

No context found.

Buvac, S. 1996. Quantificational logic of context. In Proceedings of the Thirteenth National Conference on Artificial Intelligence.

No context found.

Sasa Buvac. Quantificational logic of context. In Howard Shrobe and Ted Senator, editors, AAAI 1996, pages 600--606, Menlo Park, California, 1996. AAAI Press.

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Sasa Buvac. Quantificational logic of context. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, 1996.

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Buvac, S. 1996 Quantificational logic of context. In Proc 13 AAAI Conf Menlo Park CA.

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Sasa Buvac. Quantificational logic of context. In Proceedings of the 13th National Conference on Artificial Intelligence (AAAI96) , pages 600--606, Portland, OR, 1996.

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Buvac, S (1996) Quantificational logic of context. In Proceeding the 13 th AAAI-96, Menlo Park, CA. 21

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