R. J. Brachman, The future of knowledge representation', in Proc.AAAI90, pp. 1082--1092, Boston, MA (1990).  Home/Search   Document Not in Database   Summary   Related Articles   Check

....easily. 2 A BRIEF HISTORY KR R started as a sub activity of more problem specific issues such as natural language understanding. In those pioneering days a typical KR R paper was on how to distinguish between de re and de dicto readings in some semantic network formalism. According to Brachman [1], this changed with the beginning of the eighties, and KR R became formal and technical. Now questions such as what is the formal semantics of your formalism and what is the computational complexity of reasoning in your formalism became important. It is this part of KR R that builds some of ....

....Georges Kohler Allee, Geb. 52, D 79110 Freiburg, Germany, email: nebel informatik.uni freiburg.de 3 WHERE DOES KR R STAND NOW While there was a big change from the seventies to the eighties, the nineties did not establish a revolutionary new KR R trend. Very much as predicted by Brachman [1], logic and rigor, nonmonotonic reasoners, probability and statistics, as well as ontologies are still important issues. One interesting new development is that theoretically oriented researchers start to implement systems At a workshop on Logic Based AI organized by Jack Minker [3] all ....

R. J. Brachman, The future of knowledge representation', in Proc.AAAI90, pp. 1082--1092, Boston, MA (1990).

....the title Belief Revision and Default Reasoning: Syntax Based Approaches in J. A. Allen, R. Fikes, and E. Sandewall (eds. Principles of Knowledge Representation and Reasoning: Proceedings of the Second International Conference, Morgan Kaufmann, San Mateo, CA, 1991, pp. 417 428. 1 See also (Brachman 1990), in which practical and well founded theories of belief revision are called for. tisfy all AGM postulates belief revision operations should obey, however (see (Gardenfors, this book) In Section 5 some interesting special cases of epistemic relevance are analyzed that lead to the ....

Brachman, R. J. (1990): The Future of Knowledge Representation, in: Proceedings of the 8th National Conference of the American Association for Artificial Intelligence, Boston, Mass., 1082--1092.

.... Mendelzon, 1989; Katsuno and Mendelzon, 1990; Doyle, 1990 ] Most of this research has been considerably influenced by approaches in philosophical logic, in particular by Gardenfors and his colleagues [ Alchourr on et al. 1985; Gardenfors, 1988 ] who developed the logic of theory 1 See also [Brachman, 1990], in which practical and well founded theories of belief revision are called for. change, also called theory of epistemic change, which will be briefly sketched in Section 2. Syntax based approaches to belief revision to be introduced in Section 3 have been very popular because of their ....

Ronald J. Brachman. The future of knowledge representation. In Proceedings of the 8th National Conference of the American Association for Artificial Intelligence, pages 1082--1092, Boston, Mass., August 1990.

....about it [Etherington, 88, Ginsberg, 87, Reiter, 87] One issue which has received little attention until recently is the issue of efficiency. Most proposals for default reasoning are computationally intractable, while in common sense reasoning, defaults seem to be used to speed up inference (see [Brachman, 90] p. 1090, and [Cadoli Lenzerini, 90] One possible application of the access limitations in Algernon (particularly the association of rules with sets of objects) is in the development of efficient approaches to default reasoning. The example in this section represents the beginning of what ....

Brachman, R. J. (1990). The Future of Knowledge Representation. In AAAI-90, pp. 1082-1092.

....approaches that are completely incompatible with a logical, declarative point of view. Nowadays, the picture has completely changed, however. Logical methods predominate and methodological problems are hardly discussed any longer [ Brachman et al. 1989; Allen et al. 1991; Nebel et al. 1992; Brachman, 1990 ] Instead, research papers focus on particular technical representation and reasoning problems and address these problems using methods from logic and computer science. While this development indicates that KR has become a mature scientific discipline, it also leads to the situation that ....

Ronald J. Brachman. The future of knowledge representation. In AAAI-90 [1990], pages 1082--1092.

....relation weighting scheme. The usefulness of relation weighting is seen in terms of improving both the accuracy and efficiency of retrieval by feature based search. In the development of most AI systems, the issue of how to represent the knowledge required by the system must be addressed [14]. Most knowledge representations are tailored to emphasise those aspects of the domain that are most useful for the particular system s application [29] Accordingly, the knowledge representation developed in this chapter is tailored to the task of case retrieval. The representation requirements ....

Ronald J Brachman. The Future of Knowledge Representation. In AAAI-90: Proceedings of the Ninth National Conference on Artificial Intelligence., pages pp1082-- 1092, 1990. Extended Abstract.

....Instead they argue in favour of expressiveness of language. After all, usually a domain of application is specified in ordinary natural language. And natural language is expressively very powerful. Reflecting on the history of knowledge representation and discussion future directions in research Brachman (1990) notes that natural language specific issues have received less attention than they should have. He says (p. 1091) It would not hurt at this point to go back and spend some time thinking about the relation of KR [knowledge representation] to natural language, for example after all, that was in ....

Brachman, R. J. (1990), The future of knowledge representation, Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 1082--1092. Extended Abstract.

....incompatible semantics [29] The representational differences are caused by the need to bind data to representations that are most natural and efficient with respect to specific applications. In general, there simply does not exist a universal representation that is perfect for every application [5, 14, 19]. Examples of representational mismatches are: ffl Identification. Employees could be identified by employee ID numbers in the personnel department, but by social security numbers in the payroll department. The nature of operations in these two departments demands that different identifiers be ....

....databases do not form a single logical view, sharing object identifiers between them is meaningless. In other words, object identifiers are not interoperable. In general, mediators are knowledge base systems. Since it is unrealistic to expect a single, general purpose mediator with optimal power [5], multiple mediators should coexist (just like the coexistence of multiple federated schemas in the federated database approach) offering information communication services at various levels [19, 33] These mediators could differ in their tradeoffs between communication cost and capability ....

R. J. Brachman. The future of knowledge representation. In Proceedings of the Eighth National Conference on Artificial Intelligence, pages 1082--1092, 1990.

....(Baader Hollunder 1992) and undecidable problems may become more undecidable (e.g. from r.e. complete to Pi 1 2 complete (Schlipf 1987) An upto date survey on computational aspects of NMR appears as (Cadoli Schaerf 1993) This aspect of NMR is acknowledged in the AI community. Brachman (1990, p. 1090) writes: An irony of work on NMR is that, while the easy adoption and retraction of assumptions is most useful for speeding up natural everyday reasoning, most current NMR proposals drastically compound the already difficult problem of deductive reasoning. We urgently need to determine ....

Brachman, R. J. 1990. The future of knowledge representation.

....aware of such pragmatic considerations as knowledge reusability or appropriateness of representation formalisms for the differents kinds of knowledge coming up in a specific application domain. Putting such pragmatic considerations into the center of interest may promote the spirit of Brachman [10], who blamed the KR community for having lost sight of their users being caught in technical details. 2 TaxLog: A Close Integration of Terminological Reasoning and Logic Programming First, let us introduce the language TaxLog, also presented in [2, 1] A TaxLog program clause is a definite ....

R.L. Brachman. The future of knowledge representation. In AAAI'90. The MIT Press / AAAI Press, 1990.

....knowledge representation has traditionally been considered as the heart of software activities and particularly of Artificial Intelligence. Indeed, there have been noticing in AI literature that the activity of knowledge representation constitutes a crucial step when building almost any AI system [Brachman 90] For the most AI research, knowledge (facts, raw data, and actions describing objects of application domain and their behavior) needed to get al..ong in a system could be written in some form, and then used as needed. Hence, it is worthwhile to be able to express suitably this knowledge to enable ....

....at best a limited set of knowledge and to infer all implicit information that it withdraws. In 1980 s knowledge representation has surpassed the backstage activity of AI research. It has seen major changes in methodology and emerged as a field unto itself with its own burgeoning literature [Brachman 90] Along this growth, knowledge representation has benefited of important technical and no so technical contributions from other disciplines such mathematics and particularly logic (classic, nonclassic) psychology (script, prototype theory) informatics (databases, object oriented programming) ....

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: R. J. Brachman. The future of knowledge representation. In proceedings of AAAI'90 Boston Massachusetts, 1990. pp. 1082-1092.

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R. J. Brachman, "The future of knowledge representation, " in Proceedings of the Eighth National Conference on Artificial Intelligence, (Menlo Park, CA), pp. 1082--1092, AAAI Press, 1990.

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R. J. Brachman. The future of knowledge representation. In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), pages 1082--1092, 1990.

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Ronald J. Brachman (1990). "The future of knowledge representation," Proceedings Eighth National Conference on Artificial Intelligence (AAAI-90), Cambridge, Mass.: MIT Press, p. 1082-1092.

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