22 found
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  1.  76
    Nonmonotonic reasoning: logical foundations of commonsense.Gerhard Brewka (ed.) - 1991 - New York: Cambridge University Press.
    In this book the author gives a broad overview of different areas of research in nonmonotonic reasoning, and presents some new results and ideas based on his research. The guiding principles are: clarification of the different research activities in the area, which have sometimes been undertaken independently of each other; and appreciation of the fact that these research activities often represent different means to the same ends, namely sound theoretical foundations and efficient computation. The book begins with a discussion of (...)
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  2.  13
    Shedding new light on the foundations of abstract argumentation: Modularization and weak admissibility.Ringo Baumann, Gerhard Brewka & Markus Ulbricht - 2022 - Artificial Intelligence 310 (C):103742.
  3.  11
    Cumulative default logic.Gerhard Brewka - 1991 - Artificial Intelligence 50 (2):183-205.
  4.  31
    Belief revision in a framework for default reasoning.Gerhard Brewka - 1991 - In Andre Fuhrmann & Michael Morreau (eds.), The Logic of Theory Change: Workshop, Konstanz, FRG, October 13-15, 1989, Proceedings. Springer. pp. 206--222.
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  5.  18
    Nonmonotonic Reasoning: An Overview.Gerhard Brewka, Jürgen Dix & Kurt Konolige - 1997 - Center for the Study of Language and Inf.
    Nonmonotonic reasoning in its broadest sense is reasoning to conclusions on the basis of incomplete information. Given more information, previously drawn inferences may be retracted. Commonsense reasoning has a nonmonotonic component; it has been argued that almost all commonsense inferences are of this sort. From the end of the 1980s to the present there has been an explosion in research in nonmonotonic reasoning. It is now possible to understand more clearly the properties of the major formalisms from a metatheoretical point (...)
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  6.  25
    Handling and measuring inconsistency in non-monotonic logics.Markus Ulbricht, Matthias Thimm & Gerhard Brewka - 2020 - Artificial Intelligence 286 (C):103344.
  7.  7
    Preferred answer sets for extended logic programs.Gerhard Brewka & Thomas Eiter - 1999 - Artificial Intelligence 109 (1-2):297-356.
  8.  14
    Strong inconsistency.Gerhard Brewka, Matthias Thimm & Markus Ulbricht - 2019 - Artificial Intelligence 267 (C):78-117.
  9.  12
    Qualitative choice logic.Gerhard Brewka, Salem Benferhat & Daniel Le Berre - 2004 - Artificial Intelligence 157 (1-2):203-237.
  10.  21
    A general framework for preferences in answer set programming.Gerhard Brewka, James Delgrande, Javier Romero & Torsten Schaub - 2023 - Artificial Intelligence 325 (C):104023.
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  11.  30
    Answer Sets and Qualitative Decision Making.Gerhard Brewka - 2005 - Synthese 146 (1-2):171-187.
    Logic programs under answer set semantics have become popular as a knowledge representation formalism in Artificial Intelligence. In this paper we investigate the possibility of using answer sets for qualitative decision making. Our approach is based on an extension of the formalism, called logic programs with ordered disjunction (LPODs). These programs contain a new connective called ordered disjunction. The new connective allows us to represent alternative, ranked options for problem solutions in the heads of rules: A × B intuitively means: (...)
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  12. Representing meta-knowledge in Poole-systems.Gerhard Brewka - 2001 - Studia Logica 67 (2):153-165.
    We show how Poole-systems, a simple approach to nonmonotonic reasoning, can be extended to take meta-information into account adequately. The meta-information is used to guide the choice of formulas accepted by the reasoner as premises. Existence of a consistent set of conclusions is guaranteed by a least fixpoint construction. The proposed formalism has useful applications in defeasible reasoning, knowledge base fusion and belief revision.
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  13.  18
    Answer Sets and Qualitative Optimization.Gerhard Brewka - 2006 - Logic Journal of the IGPL 14 (3):413-433.
    One of the major reasons for the success of answer set programming in recent years was the shift from a theorem proving to a constraint programming view: problems are represented such that stable models, respectively answer sets, rather than theorems correspond to solutions. This shift in perspective proved extremely fruitful in many areas. We believe that going one step further from a “hard” to a “soft” constraint programming paradigm, or, in other words, to a paradigm of qualitative optimization, will prove (...)
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  14.  46
    Declarative Representation of Revision Strategies.Gerhard Brewka - 2001 - Journal of Applied Non-Classical Logics 11 (1-2):151-167.
    In this paper we introduce a nonmonotonic framework for belief revision in which reasoning about the reliability of different pieces of information based on meta-knowledge about the information is possible, and where revision strategies can be described declaratively. The approach is based on a Poole-style system for default reasoning in which entrenchment information is represented in the logical language. A notion of inference based on the least fixed point of a monotone operator is used to make sure that all theories (...)
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  15.  1
    Nonmonotonic Reasoning: From Theoretical Foundation Towards Efficient Computation: Diss.Gerhard Brewka - 1989 - [S.N.].
  16.  4
    Principles of Knowledge Representation.Gerhard Brewka - 1996 - Center for the Study of Language and Inf.
    The book contains a collection of eight survey papers written by some of the best researchers in foundations of knowledge representation and reasoning. It covers topics like theories of uncertainty, nonmonotonic and causal reasoning, logic programming, abduction, inductive logic programming, description logics, complexity in Artificial Intelligence, and model-based diagnosis. It thus provides an up-to-date coverage of recent approaches to some of the most challenging problems underlying knowledge representation and Artificial Intelligence in general.
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  17.  10
    Reactive multi-context systems: Heterogeneous reasoning in dynamic environments.Gerhard Brewka, Stefan Ellmauthaler, Ricardo Gonçalves, Matthias Knorr, João Leite & Jörg Pührer - 2018 - Artificial Intelligence 256 (C):68-104.
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  18.  13
    Preface.Manuel Ojeda-Aciego, Gerhard Brewka, Inma P. de Guzmán & Luís Moniz Pereira - 2002 - Studia Logica 72 (1):3-5.
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  19.  10
    Preface.Gerhard Brewka & Pavlos Peppas - 2005 - Studia Logica 79 (1):3-5.
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  20.  10
    Skeptical reason maintenance and belief revision.Cees Witteveen & Gerhard Brewka - 1993 - Artificial Intelligence 61 (1):1-36.
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  21.  8
    Nonmonotonic and Inductive Logic: Second International Workshop, Reinhardsbrunn Castle, Germany, December 2-6, 1991. Proceedings.Gerhard Brewka & Klaus P. Jantke - 1993 - Springer Verlag.
    This proceedings volume contains a selection of revised and extended papers presented at the Second International Workshop on Nonmonotonic and InductiveLogic, NIL '91, which took place at Reinhardsbrunn Castle, December 2-6, 1991. The volume opens with an extended version of a tutorial on nonmonotonic logic by G. Brewka, J. Dix, and K. Konolige. Fifteen selected papers follow, on a variety of topics. The majority of papers belong either to the area of nonmonotonic reasoning or to the field of inductive inference, (...)
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  22.  10
    Logics in Artificial Intelligence: European Workshop, JELIA 2000 Malaga, Spain, September 29 - October 2, 2000 Proceedings.Manuel Ojeda-Aciego, Inma P. De Guzman, Gerhard Brewka & Luis M. Pereira - 2000 - Springer.
    This book constitutes the refereed proceedings of the European Workshop on Logics in Artificial Intelligence, JELIA 2000, held in Malaga, Spain in September/October 2000. The 24 revised full papers presented together with three invited papers were carefully reviewed and selected out of 60 submissions. The papers are organized in topical sections on knowledge representation, reasoning about actions, belief revision, theorem proving, argumentation, agents, decidability and complexity, updates, and preferences.
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