Gerd Brewka, Jurgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview, volume 73 of CSLI Lecture Notes. CSLI Publications, 1997.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....1 Introduction Abduction is a fundamental mode of reasoning, which was extensively studied by C.S. Peirce [19] It has taken on increasing importance in Artificial Intelligence (AI) and related disciplines, where it has been recognized as an important principle of commonsense reasoning (see e.g. [3]) Abduction has applications in many areas of AI and Computer Science including diagnosis, database updates, planning, natural language understanding, learning etc. see e.g. references in [10] where it is primarily used for generating explanations. In a logic based setting, abduction can be ....

G. Brewka, J. Dix, and K. Konolige. Nonmonotonic Reasoning -- An Overview. Number 73 in CSLI Lecture Notes. CSLI Publications, Stanford University, 1997.

....1 Introduction Abduction is a fundamental mode of reasoning, which was extensively studied by C.S. Peirce [18] It has taken on increasing importance in Artificial Intelligence (AI) and related disciplines, where it has been recognized as an important principle of common sense reasoning (see e.g. [3]) Abduction has applications in many areas of AI and Computer Science including diagnosis, database updates, planning, natural language understanding, learning etc. see e.g. references in [10] where it is primarily used for generating explanations. In a logic based setting, abduction can be ....

G. Brewka, J. Dix, and K. Konolige. Nonmonotonic Reasoning -- An Overview. Number 73 in CSLI Lecture Notes. CSLI Publications, Stanford University, 1997.

....abduction is the task of finding an explanation for certain observations, based on some background theory describing the relationships between causes and effects. There is a growing literature on this subject, which has been recognized as an important principle of common sense reasoning (see e.g. [5]) and has many further applications (see e.g. references in [15] More formally, abduction can be defined as follows, where we recall that b Sigma transforms a Horn theory Sigma into an equivalent set of Horn clauses. Definition 6.1 Let Sigma be a theory, A be a subset of the atoms of ....

G. Brewka, J. Dix, and K. Konolige. Nonmonotonic Reasoning -- An Overview. CSLI Lecture Notes 73. CSLI Publications, Stanford University, 1997.

.... 1 2 Preliminaries 3 3 Generating Explanations 4 4 Negative Queries 8 5 Joint Explanations 11 6 Related Works 13 7 Conclusion 14 A Appendix 14 1 Introduction Abduction is a fundamental mode of reasoning, which has been recognized as an important principle of common sense reasoning (see e.g. [3]) It has applications in many areas of AI including diagnosis, planning, learning, natural language understanding and many others (see e.g. references in [7] In a logic based setting, abduction can be defined as the task, given a set of formulas (the background theory) and a formula (the ....

G. Brewka, J. Dix, and K. Konolige. Nonmonotonic Reasoning -- An Overview. Number 73 in CSLI Lecture Notes. CSLI Publications, Stanford University, 1997.

....1994 655 Avenue of the Americas, New York, NY 10010 0743 1066 94 7.00 Intelligence (AI) such as explanation, non monotonic and default reasoning and theory revision. As a result, abduction manifests itself as an important form of inference for addressing a variety of problems in AI (see e.g. [1], 4] 5] 7] 13] 27] 33] 46] 23] 42] 51] 52] These problems include, amongst others, the problems of diagnosis, planning and scheduling, natural language understanding, assimilation of sensor data and user modeling. The high level modeling environment of abduction can offer an ....

G.Brewka, J.Dix and K.Konolige. Nonmonotonic Reasoning: An Overview. CSLI publications, 1997.

....between the more or less pure logic with which Montague worked and a system that may be more genuinely helpful in applications that involve representation of and reasoning with linguistic meaning. 11 See the papers collected in [ Lifschitz, 1990 ] 5 available, including [ Antoniou, 1997, Brewka et al. 1997, Schlechta, 1997 ] Also see the relevant chapters of [ Gabbay et al. 1994 ] Among the available theories of defeasible reasoning that could be applied in lexical semantics, I nd circumscription the most congenial to use in attempting to apply these theories to problems of natural language ....

Gerhard Brewka, Jurgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview. CSLI Publications, Stanford, 1997.

....logic, Reiter [1980] defined normal theories, that could be shown to have at least one extension. Etherington [1987] defined ordered theories and showed that ordered, semi normal theories always have an extension. More results and references are for instance given by Gabbay et al. 1994] and Brewka et al. 1997]. In the present paper, the notorious extension existence and extension multiplicity problems are solved in the context of a specific form of defeasible reasoning, viz. dialectical argumentation. In dialectical argumentation, statements are not only adduced as reasons for other statements, but ....

Brewka, G. Dix, J., and Konolige, K. (1997). Nonmonotonic reasoning: an overview. CSLI Publications, Stanford.

....logical paradigm, McCarthy s Circumscription [McC80] is one of the first major nonmonotonic reasoning tools. Since its debut, the nonmonotonic reasoning line of work has expanded and several textbooks now exist that give a fair view of nonmonotonic reasoning and its uses (e.g. Bre91] Ant97] [BDK97], DG94] San94] Sha97] The motivations for nonmonotonic reasoning vary from formalizing Common Sense reasoning through Elaboration Tolerance and representation of uncertainty to Belief Revision. We do not expand on these motivations further here, and the reader may look at ....

Gerd Brewka, Jurgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview, volume 73 of CSLI Lecture Notes. CSLI Publications, 1997.

....certain premises. We follow the following strategy: # Take a close look at the arguments. Design the syntax of a formal language to represent their premises and the conclusions. # Standard technical references on the subject include: McCarty (1980) Makinson (1994) and Veltman (1996) Brewka, Dix, and Konolige (1997) provide an accessible overview of the eld of nonmonotonic logic. 2 # Identify the logical principles used in this type of argumentation and generalize them. # Formalize these principles in a semantics and a semantically de ned system of inference for the sentences of this language. # Verify ....

Brewka, G., J. Dix, and K. Konolige. 1997. Nonmonotonic Reasoning: An Overview.

....We will, for instance, hesitate to accept an explanation as plausible which involves many and unmotivated changes. Generally, there is always an assumption of inertia formalizing that certain properties tend to persist over time. Many nonmonotonic logics have been used to formalize persistency ([2]) e.g. circumscriptive approaches try to minimize change by circumscribing certain predicates (see [17,10] Default logics formalize persistency by stating special default rules ( 9] In logic programming, various versions of negation as failure have been de ned to specify that uents persist ....

Gerd Brewka, Jurgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview. CSLI Lecture Notes 73. CSLI Publications, Stanford, CA, 1997.

....The system s ability to handle conflicting evidence implies that old evidence can be discounted as new evidence is introduced. An important issue associated with a rigorous implementation of probabilistic diagnostic system is that of computation burden. Compared to other diagnostic systems [9] [10], the computation for very large BBN networks have been shown to be tractable [11] BBN have been successfully applied in many disciplines including engineering decision support systems [12] In this paper, we develop a Bayesian Belief Network (BBN) model of the xerographic printing process. It ....

G. Brewka, J, Dix, and K.Konolige, Nonmonotonic Reasoning: An Overview. No. 73 in CSLI lecture notes, Stanford, CSLI Publications CA 1997

.... put more emphasis on computational aspects since the eld [of non monotonic reasoning in general and default reasoning in particular] can only have a lasting impact on AI and Computer Science in general if it can provide useful tools helping people to better handle their real world problems ([5], page 144) Di erently from the stable semantics, the admissibility semantics requires only a local search, rst to construct a set of assumptions which (monotonically) implies the sentence to be justi ed, and then to augment the set with further assumptions to defend the constructed set ....

G. Brewka, J. Dix. K. Konolige, Nonmonotonic reasoning: an overview. CLSI Lecture Notes 73 (Standford, California) (1997)

....transformations rules that respect this last condition and thus we combine methods from rewriting with logic programming technology and we get a powerful framework for investigating the semantics of logic programs. Most of the well known semantics are induced by confluent systems. In a recent book [2] the authors (Brewka, Dix and Konolige) introduced the notion of well behaved semantics, and aim at a classification of well behaved semantics according to other, clearly formulated declarative properties. In particular the mentioned book presents three conjectures (conjectures 7.20, 7.21 and ....

Gerd Brewka, Jurgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview. CSLI Lecture Notes 73. CSLI Publications, Stanford, CA, 1997.

....programmingand non monotonicreasoning in general. Nevertheless, to make this paper self contained and also readable to the non specialist, we have added some remarks and references about classical notions in this field. For more detailed investigations and overview articles we refer the reader to [1, 27, 59, 60, 41, 17, 45, 16, 37, 50, 51]. 2. Normal Programs Although our aim is to create a disjunctive logic programming system, many problems already occur for negation with respect to non disjunctive programs. There are two main competing approaches to provide semantics for negation in logic programming, namely the stable model ....

Gerd Brewka, J urgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview. CSLI Lecture Notes 73. CSLI Publications, Stanford, CA, 1997.

....We will, for instance, hesitate to accept an explanation as plausible which involves many and unmotivated changes. Generally, there is always an assumption of inertia formalizing that certain properties tend to persist over time. Many nonmonotonic logics have been used to formalize persistency ([2]) e.g. circumscriptive approaches try to minimize change by circumscribing certain predicates (see [16,10] Default logics formalize persistency by stating special default rules ( 9] In logic programming, various versions of negation as failure have been defined to specify that fluents persist ....

Gerd Brewka, Jurgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview. CSLI Lecture Notes 73. CSLI Publications, Stanford, CA, 1997.

....[GHR99] Handbook of Logic in Computer Science [AGM99] Handbook of Philosophical Logic, 2nd Edition [GG99] and Handbook of Automated Reasoning [Rob98] All contain up to date information on the treated subject. In particular, we suggest [Gab94] Gin94] Mak94] RS92] BD98] DFN98] [BDK97] is a recent book on Nonmonotonic Reasoning and treats most aspects on an post graduate or PhD level. 34 ....

Gerd Brewka, Jurgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview. CSLI Lecture Notes 73. CSLI Publications, Stanford, CA, 1997.

....2 Stefan Brass and Jurgen Dix forms of negation as failure from non disjunctive to disjunctive semantics. Many interrelationships of non monotonic logics (Default Logic DL, Circumscription CIRC, Autoepistemic Logic AEL) with semantics of logic programs have been discovered during the last years [1, 20, 28, 14]. Eiter and Gottlob have shown in [23, 24] that disjunctive semantics are strictly more expressive than non disjunctive semantics and therefore may be better suited for many knowledge representation tasks (see also [2, 15] for using such semantics in KR) One of the main problems today is that ....

Gerd Brewka, Jurgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview. CSLI Lecture Notes 73. CSLI Publications, Stanford, CA, 1997.

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Gerd Brewka, Jurgen Dix, and Kurt Konolige. Nonmonotonic Reasoning: An Overview, volume 73 of CSLI Lecture Notes. CSLI Publications, 1997.

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Brewka, G., Dix, J., Konolige, K., Nonmonotonic Reasoning -- An Overview, chapter 5: Abduction, pp. 65--86. CSLI Lecture Notes 73, CSLI Publications, Stanford University, 1997.

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G. Brewka, J. Dix, and K. Konolige. Nonmonotonic Reasoning -- An Overview. Number 73 in CSLI Lecture Notes. CSLI Publications, Stanford University, 1997.

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G. Brewka, J. Dix. K. Konolige, Nonmonotonic reasoning: an overview. CLSI Lecture Notes 73 (Standford, California) (1997)

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G Brewka, J Dix, and K Konolige. Non-monotonic Reasoning: An Overview. CLSI Publications, 1997.

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G Brewka, J Dix, and K Konolige. Non-monotonic Reasoning: An Overview. CLSI Publications, 1997.

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G. Brewka, J. Dix, and K. Konolige. Nonmonotonic Reasoning: an overview. Number 73 in CSLI Lecture Notes. CSLI Publications, Stanford CA, 1997.

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G. Brewka, J. Dix, and K. Konolige. Nonmonotonic Reasoning: an overview. CSLI Lecture Notes, 1997. 14

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