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26
Classical Negation in Logic Programs and Disjunctive Databases
 New Generation Computing
, 1991
"... An important limitation of traditional logic programming as a knowledge representation tool, in comparison with classical logic, is that logic programming does not allow us to deal directly with incomplete information. In order to overcome this limitation, we extend the class of general logic progra ..."
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Cited by 853 (75 self)
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An important limitation of traditional logic programming as a knowledge representation tool, in comparison with classical logic, is that logic programming does not allow us to deal directly with incomplete information. In order to overcome this limitation, we extend the class of general logic programs by including classical negation, in addition to negationasfailure. The semantics of such extended programs is based on the method of stable models. The concept of a disjunctive database can be extended in a similar way. We show that some facts of commonsense knowledge can be represented by logic programs and disjunctive databases more easily when classical negation is available. Computationally, classical negation can be eliminated from extended programs by a simple preprocessor. Extended programs are identical to a special case of default theories in the sense of Reiter. 1 Introduction An important limitation of traditional logic programming as a knowledge representation tool, in comp...
Logic Programming and Knowledge Representation
 Journal of Logic Programming
, 1994
"... In this paper, we review recent work aimed at the application of declarative logic programming to knowledge representation in artificial intelligence. We consider exten sions of the language of definite logic programs by classical (strong) negation, disjunc tion, and some modal operators and sh ..."
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Cited by 224 (21 self)
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In this paper, we review recent work aimed at the application of declarative logic programming to knowledge representation in artificial intelligence. We consider exten sions of the language of definite logic programs by classical (strong) negation, disjunc tion, and some modal operators and show how each of the added features extends the representational power of the language.
Stable Semantics for Disjunctive Programs
 New Generation Computing
, 1991
"... We introduce the stable model semantics for disjunctive logic programs and deductive databases, which generalizes the stable model semantics, defined earlier for normal (i.e., nondisjunctive) programs. Depending on whether only total (2valued) or all partial (3valued) models are used we obtain th ..."
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Cited by 163 (2 self)
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We introduce the stable model semantics for disjunctive logic programs and deductive databases, which generalizes the stable model semantics, defined earlier for normal (i.e., nondisjunctive) programs. Depending on whether only total (2valued) or all partial (3valued) models are used we obtain the disjunctive stable semantics or the partial disjunctive stable semantics, respectively. The proposed semantics are shown to have the following properties: ffl For normal programs, the disjunctive (respectively, partial disjunctive) stable semantics coincides with the stable (respectively, partial stable) semantics. ffl For normal programs, the partial disjunctive stable semantics also coincides with the wellfounded semantics. ffl For locally stratified disjunctive programs both (total and partial) disjunctive stable semantics coincide with the perfect model semantics. ffl The partial disjunctive stable semantics can be generalized to the class of all disjunctive logic programs. ffl B...
Answer Set Programming and Plan Generation
 ARTIFICIAL INTELLIGENCE
, 2002
"... The idea of answer set programming is to represent a given computational problem by a logic program whose answer sets correspond to solutions, and then use an answer set solver, such as smodels or dlv, to find an answer set for this program. Applications of this method to planning are related to the ..."
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Cited by 137 (5 self)
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The idea of answer set programming is to represent a given computational problem by a logic program whose answer sets correspond to solutions, and then use an answer set solver, such as smodels or dlv, to find an answer set for this program. Applications of this method to planning are related to the line of research on the frame problem that started with the invention of formal nonmonotonic reasoning in 1980.
Nonmonotonic Reasoning in the Framework of Situation Calculus
 Artificial Intelligence
, 1991
"... Most of the solutions proposed to the Yale shooting problem have either introduced new nonmonotonic reasoning methods (generally involving temporal priorities) or completely reformulated the domain axioms to represent causality explicitly. This paper presents a new solution based on the idea that si ..."
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Cited by 132 (0 self)
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Most of the solutions proposed to the Yale shooting problem have either introduced new nonmonotonic reasoning methods (generally involving temporal priorities) or completely reformulated the domain axioms to represent causality explicitly. This paper presents a new solution based on the idea that since the abnormality predicate takes a situational argument, it is important for the meanings of the situations to be held constant across the various models being compared. This is accomplished by a simple change in circumscription policy: when Ab is circumscribed, Result (rather than Holds) is allowed to vary. In addition, we need an axiom ensuring that every consistent situation is included in the domain of discourse. Ordinary circumscription will then produce the intuitively correct answer. Beyond its conceptual simplicity, the solution proposed here has additional advantages over the previous approaches. Unlike the approach that uses temporal priorities, it can support reasoning backward...
Truth Maintenance
, 1990
"... General purpose truth maintenance systems have received considerable attention in the past few years. This paper discusses the functionality of truth maintenance systems and compares various existing algorithms. Applications and directions for future research are also discussed. Introduction In 197 ..."
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Cited by 110 (3 self)
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General purpose truth maintenance systems have received considerable attention in the past few years. This paper discusses the functionality of truth maintenance systems and compares various existing algorithms. Applications and directions for future research are also discussed. Introduction In 1978 Jon Doyle wrote a masters thesis at the MIT AI Laboratory entitled "Truth Maintenance Systems for Problem Solving" [ Doyle, 1979 ] . In this thesis Doyle described an independent module called a truth maintenance system, or TMS, which maintained beliefs for general problem solving systems. In the twelve years since the appearance of Doyle's TMS a large body of literature has accumulated on truth maintenance. The seminal idea appears not to have been any particular technical mechanism but rather the general concept of an independent module for truth (or belief) maintenance. All truth maintenance systems manipulate proposition symbols and relationships between proposition symbols. I will use...
A Simple Solution to the Yale Shooting Problem
, 1989
"... Most of the solutions proposed to the Yale shooting problem have either introduced new nonmonotonic reasoning methods (generally involving temporal priorities) or completely reformulated the domain axioms to represent causality explicitly. This paper presents a new solution based on the idea that si ..."
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Cited by 51 (3 self)
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Most of the solutions proposed to the Yale shooting problem have either introduced new nonmonotonic reasoning methods (generally involving temporal priorities) or completely reformulated the domain axioms to represent causality explicitly. This paper presents a new solution based on the idea that since the abnormality predicate takes a situational argument, it is important for the meanings of the situations to be held constant across the various models being compared. This is accomplished by a simple change in circumscription policy: when Ab is circumscribed, Result (rather than Holds) is allowed to vary. In addition, we need an axiom ensuring that every consistent situation is included in the domain of discourse. Ordinary circumscription will then produce the intuitively correct answer. Beyond its conceptual simplicity, the solution proposed here has additional advantages over the previous approaches. Unlike the approach that uses temporal priorities, it can support reasoning backwar...
What the Lottery Paradox Tells Us About Default Reasoning
, 1989
"... In this paper I argue that we do not understand the process of default reasoning. A number of examples are given which serve to distinguish different default reasoning systems. It is shown that if we do not make our assumptions explicit we get into trouble with disjunctive knowledge, and if we make ..."
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Cited by 38 (4 self)
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In this paper I argue that we do not understand the process of default reasoning. A number of examples are given which serve to distinguish different default reasoning systems. It is shown that if we do not make our assumptions explicit we get into trouble with disjunctive knowledge, and if we make our assumptions explicit, we run foul of the lottery paradox. None of the current popular default reasoning systems work on all of the examples. It is argued that the lottery paradox does arise in default reasoning and can cause problems. It is also shown that some of the intuitively plausible requirements for default reasoning are incompatible. How different systems cope with this is discussed. 1 Introduction Default reasoning is the ability to jump to a conclusion based on the lack of evidence to the contrary. Deduction in standard logic does not allow such reasoning; if some proposition follows from a set of axioms, it follows from a superset of the axioms. There have been many proposal...
Active Logics: A Unified Formal Approach to Episodic Reasoning
"... Artificial intelligence research falls roughly into two categories: formal and implementational. This division is not completely firm: there are implementational studies based on (formal or informal) theories (e.g., CYC, SOAR, OSCAR), and there are theories framed with an eye toward implementabili ..."
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Cited by 35 (2 self)
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Artificial intelligence research falls roughly into two categories: formal and implementational. This division is not completely firm: there are implementational studies based on (formal or informal) theories (e.g., CYC, SOAR, OSCAR), and there are theories framed with an eye toward implementability (e.g., predicate circumscription). Nevertheless, formal /theoretical work tends to focus on very narrow problems (and even on very special cases of very narrow problems) while trying to get them "right" in a very strict sense, while implementational work tends to aim at fairly broad ranges of behavior but often at the expense of any kind of overall conceptually unifying framework that informs understanding. It is sometimes urged that this gap is intrinsic to the topic: intelligence is not a unitary thing for which there will be a unifying theory, but rather a "society" of subintelligences whose overall behavior cannot be reduced to useful characterizing and predictive principles.