R. J. Brachman and H.J. Levesque. Competence in Knowledge Representation. In Proc. of the National Conference on Articial Intelligence, pages 189-192, 1982.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....with by iterating this positive induction operator in a least xpoint computation. The study of the role of de nitions in knowledge representation has already a long tradition in A.I. As an outcome of a series of investigations to the semantics of semantic networks 1 , Brachman and Levesque [4] observed that an important component of expert knowledge is knowledge of the de ning properties of concepts, and that it is crucial to distinguish between de ning properties of concepts and assertional knowledge on concepts. Description logics are based on this idea, and consist of a Tbox to ....

R. J. Brachman and H.J. Levesque. Competence in Knowledge Representation. In Proc. of the National Conference on Articial Intelligence, pages 189-192, 1982.

....problem of common sense knowledge representation. Also in the context of modern AI, the study of the role of definitions in common sense knowledge representation has a long tradition. As an outcome of a series of investigations into the semantics of semantic networks 1 , Brachman and Levesque (Brachman Levesque 1982) observed that an important component of expert knowledge is knowledge of the defining properties of concepts, and that it is crucial to distinguish between defining properties of concepts and assertional knowledge on concepts. Description logics are based on this idea, and consist of a Tbox to ....

....cases is in general a non monotonic operation. ffl Adding new definitions or new axioms to a theory is a monotonic operation. This follows trivially from the definition of model. Applications of definitions Below some applications of ID logic are given. Terminological knowledge. According to (Brachman Levesque 1982), definitions of terminology constitutes an important part of expert knowledge. Terminological knowledge is about the defining properties of a concept, i.e. the necessary and sufficient conditions to belong to the concept. To see the crucial difference between terminological and assertional ....

Brachman, R. J., and Levesque, H. 1982. Competence in Knowledge Representation. In Proc. of the National Conference on Artificial Intelligence, 189--192.

....system of the need to perform taxonomic reasoning and because it extends the power of the knowledge representation system towards greater logical completeness. Other researchers have also cited the advantages of integrating knowledge representation systems with more general deduction systems [7, 26]. Krypton [6, 24] represents an approach to constructing a knowledge representation system composed of two parts: a terminological component (the TBox) and an assertional component (the ABox) For such systems, theory resolution indicates in general how information can be provided to the ABox by ....

Brachman, R.J. and H.J. Levesque. Competence in knowledge representation. Proceedings of the AAAI-82 National Conference on Artificial Intelligence, Pittsburgh, Pennsylvania, August 1982, 189--192.

....Also in A.I. the role of de nitions in knowledge representation has been acknowledged and de nitions are central in the area of description logics [7] As an outcome of a series of investigations to the semantics (or lack of semantics) of semantic networks [29] Brachman and Levesque [6] observed that expert knowledge contains an important terminological component; this is the knowledge about the de ning properties of the concepts and terminology used by experts, i.e. the necessary and sucient properties of objects to belong to that concept. Based on this observation, Brachman ....

R. J. Brachman and H.J. Levesque. Competence in Knowledge Representation. In Proc. of the National Conference on Articial Intelligence, pages 189-192, 1982.

....to be completely satisfying for all purposes. Finally, consequences in terms of computational complexity and decidability are discussed. 1 Introduction When trying to represent an expert s knowledge about a sufficiently complex domain we have to account for the vocabulary used in this domain [Brachman and Levesque, 1982; Swartout and Neches, 1986] This is exactly the purpose of terminological knowledge representation formalisms, which have their roots in structural inheritance networks [Brachman, 1979] The main building blocks of such representation formalisms are concepts and roles [Brachman and Schmolze, ....

.... Human below: a Human is defined as a Mammal with exactly 2 parents and all parents are Humans Such a definition obviously violates the plausible idea that the meaning of a concept can be completely understood in terms of the meaning of its parts and the way these are composed [Schmolze and Brachman, 1982, p. 11] In trying to understand the meaning of Human, we inevitably end up trying to figure out what the meaning of Human could be. Additionally, the subsumption algorithms usually employed (see e.g. Schmolze and Israel, 1983] would end up in an infinite loop on such definitions. For these ....

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Ronald J. Brachman and Hector J. Levesque. Competence in knowledge representation. In Proceedings of the 2nd National Conference of the American Association for Artificial Intelligence, pages 189--192, Pittsburgh, Pa., August 1982. Terminological Cycles 31

....concepts and their analytic interrelations, while the assertions stored in the ABox state contingent facts about what is true of the world. The TBox and ABox each have their own language. These are called the terminological language and the assertional language, respectively. Brachman and Levesque [7, 4] argue that these two components should be separately designed and optimized for their respective tasks. In particular, they insist on a strict separation of the inferential mechanisms each employs, in that neither component can change or manipulate the information contained in the other. ....

.... knowledge representation researchers since the latter part of 1988 (primarily as MIT LCS TM 387 and 387b) Our concern in this paper is solely with the restricted language and restricted classification theses, which have continued to exert influence on the field since their first appearances in [4, 6, 7, 19]. Subsequent to these articles and the writing of our paper, however, work by a number of authors (including Brachman, Levesque, and their students) has been concerned with improving the utility of knowledge representation systems in some of the directions we urge in our discussion, for example, ....

R. J. Brachman and H. J. Levesque. Competence in knowledge representation. In Proceedings of the National Conference on Artificial Intelligence, pages 189--192. American Association for Artificial Intelligence, 1982.

....order logic. As current description logics are all subsets of OLP, the latter may also indicate directions for enhancing the expressivity of the former. 1 Introduction At the base of research on Description Logics (or Concept Languages) 14] 15] 13] 4] 5] 8] 1] lies the idea in [3] and [2] that an expert system and a knowledge representation language in general needs to deal with two different kinds of information: on the one hand so called assertional information about the world, and on the other hand definitional or terminological information. Assertional ....

R. J. Brachman and H. Levesque. Competence in Knowledge Representation. In Proc. of the National Conference on Artificial Intelligence, pages 189--192, 1982.

....and the uncertainty component. Both the differences and the relationships between these two components are accounted for. Under the hypothesis of considering uncertainty as a kind of knowledge (about our knowledge) the proposed framework fits the hybrid knowledge representation paradigm (Brachman Levesque, 1982). Apart from its theoretical interest, this framework is meant to form a basis for defining given a KR system and a UR system a combined uncertain knowledge representation system able to perform uncertain reasoning on structured knowledge. The rest of this paper is organized as follows: ....

Brachman, R.J. and Levesque, H.J. (1982) "Competence in Knowledge Representation", Proc. of AAAI-82: 189-192.

....with kl one revealed some shortcomings. For example, although the goals of kl one included a well defined semantics, a sufficient formal semantics was not provided . Also some of the classifier s operations were not semantically justified (p. 22) The 1981 kl one Workshop (Schmolze and Brachman [1982 ] focussed on ways of improving kl one. One prominent idea was to have separate representation schemes for terminological and assertional information, thus avoiding the confusion that Woods [1975] already addressed for semantic networks. Terminological information is also referred to as ....

....the statement (1.12) on page 4 of the Preview) I essentially regard terminological information as information that can be expressed in a terminological language and assertional information as information that can only be expressed in a more powerful language such as that of first order logic. Brachman and Levesque [1982] argue that a knowledge representation system should be adequate in two respects: terminological and assertional. According to them (p. 190) terminological adequacy involves the ability to form the appropriate kind of technical vocabulary and understand the dependencies among the terms and ....

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Brachman, R.J., and Levesque, H.J. [1982]. Competence in Knowledge Representation.

....which relates this formalism to another important class of logics in AI and knowledge representation, the terminological logics. At the origin of the terminological languages lies the observation that an expert s knowledge consists of a terminological component and an assertional component [1]. The terminological component, described in the TBox, consists of the definitions of the technical vocabulary of the expert. The role of the assertional component, described in the ABox is intimately tied to the representation of uncertainty: when a number of concepts cannot be defined, then ....

R. J. Brachman and H.J. Levesque. Competence in Knowledge Representation. In Proc. of the National Conference on Artificial Intelligence, pages 189--192, 1982.

....must be built in. keywords: object oriented representation, F logic, description languages. 1 Introduction Description languages (DLs) is a collective name for knowledge representation formalisms that concentrate on the management of essential descriptive vocabulary. It rests on the observation ([7]) that the natural ontology for providing information about a domain requires the ability to define, organize, and use intensional entities that stand for concepts and roles in a domain. DLs concentrate on providing means for: ffl Definition of concepts and roles. ffl Organizing concepts and ....

R.J. Brachman and H.J. Levesque. Competence in knowledge representation. In AAAI-82, pages 189--192, Pittsburgh, PA, 1982.

....query answering behavior. ffl Preserve intrinsic properties of the source forms, e.g. openness for rules. Description languages (DLs) is a collective name for knowledge representation formalisms that concentrate on the management of essential descriptive vocabulary. It rests on the observation ([15]) that the natural ontology for providing information about a domain requires the ability to define, organize, and use intensional entities that stand for concepts and roles in a domain. The main construct of DLs is the description, which is a complex term built on top of a fixed set of ....

R. Brachman and H. Levesque. Competence in knowledge representation. In AAAI-82, pages 189-- 192, Pittsburgh, PA, 1982.

....carried out in the plan calculus component, without overloading this component by reinventing the logical wheel. 2. 2 The Family of TBox ABox Systems In TBox ABox systems, two epistemological different kinds of knowledge are distinguished, namely, terminological and assertional knowledge [7], which is dealt with in different boxes the former kind of knowledge in the TBox, the latter in the ABox. Terminological knowledge is concerned with the definitional meaning of concepts, e.g. a parent is defined as a person who has a child, while assertional knowledge is about the state of ....

R. J. Brachman and H. J. Levesque. Competence in knowledge representation. In Proceedings of the 2nd National Conference of the American Association for Artificial Intelligence, pages 189--192, Pittsburgh, Pa., Aug. 1982.

....conclusions. See also Guarino et al. 1993 for a finer account of this and other ontological distinctions. 23 See for instance Simons 1987. We assume here that L m and C are suitably extended to nclude . 24 Cocchiarella 1993, Cocchiarella 1977. 25 See a brief review in Woods and Schmolze 1992. 26 Brachman and Levesque 1982. 27 Pelletier and Schubert 1989. 27 Smith 1992. 27 Guarino and Boldrin 1993a. 12 ....

Brachman, R. and H. Levesque 1982. "Competence in Knowledge Representation", AAAI 82.

....but needs an underlying integration framework, in which a coherent compositional semantics can be defined. Description languages (DLs) is a collective name for knowledge representation formalisms that concentrate on the management of essential descriptive vocabulary. It rests on the observation ([10]) that the natural ontology for providing information about a domain requires the ability to define, organize, and use intensional entities that stand for concepts and roles in a domain. The main construct of DLs is the description, which is a complex term built on top of a fixed set of ....

R. Brachman and H. Levesque. Competence in knowledge representation. In AAAI-82, pages 189--192, Pittsburgh, PA, 1982.

....within a KR formalism, by specifying a functional interface designed to answer safe queries about analytical relationships between terms independently of the structure of the knowledge base, like a large grey igneous rock is a grey rock . On the other hand, the same authors, in an earlier paper [4], stressed the importance of terminological competence in knowledge representation, stating for instance that an enhancement mode transistor (which is a kind of transistor ) should be understood as different from a pass transistor (which is a role a transistor plays in a larger circuit ) We ....

R. Brachman and H. Levesque 1982. Competence in Knowledge Representation. In Proceedings of AAAI 82.

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Ronald J. Brachman & Hector J. Levesque [1982], "Competence in knowledge representation," in Proceedings National Conference on Artificial Intelligence, Pittsburgh, PE, 18--20 August 1982, American Association for Artificial Intelligence, 189--192.

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