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Learning extended logic programs
- In Proceedings of the 15th International Joint Conference on Artificial Intelligence
, 1997
"... inouefieedept.kobe-u.ac.jp This paper presents a method to generate nonmonotonic rules with exceptions from positive/negative examples and background knowledge in Inductive Logic Programming. We adopt extended logic programs as the form of programs to be learned, where two kinds of negation—negation ..."
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Cited by 19 (0 self)
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inouefieedept.kobe-u.ac.jp This paper presents a method to generate nonmonotonic rules with exceptions from positive/negative examples and background knowledge in Inductive Logic Programming. We adopt extended logic programs as the form of programs to be learned, where two kinds of negation
Possibilistic and Extended Logic Programs
"... . Based on our earlier work on partial logics and extended logic programs [Wag91, Wag94, HJW96], and on the possibilistic logic of [DLP94], we define a compositional possibilistic first-order logic with two kinds of negation as the logical basis of semi-possibilistic and possibilistic logic prog ..."
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. Based on our earlier work on partial logics and extended logic programs [Wag91, Wag94, HJW96], and on the possibilistic logic of [DLP94], we define a compositional possibilistic first-order logic with two kinds of negation as the logical basis of semi-possibilistic and possibilistic logic
Learning with Extended Logic Programs
- IN PROCEEDINGS OF THE LOGIC PROGRAMMING TRACK OF THE SEVENTH INTERNATIONAL WORKSHOP ON NONMONOTONIC REASONING (LP-NMR98
, 1998
"... We discuss the adoption of a three-valued setting for inductive concept learning. Distinguishing between what is true, what is false and what is unknown can be useful in situations where decisions have to be taken on the basis of scarce information. In a three-valued setting, we want to learn a defi ..."
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Cited by 2 (0 self)
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definition for both the target concept and its opposite, considering positive and negative examples as instances of two disjoint classes. To this purpose, we adopt extended logic programs under a well-founded semantics as the representation formalism for learning. In this way, we are able to represent both
Argument-Based Extended Logic Programming With Defeasible Priorities
"... . Inspired by legal reasoning, this paper presents a semantics and proof theory of a system for defeasible argumentation. Arguments are expressed in a logic-programming language with both weak and strong negation. Conflicts between arguments are decided with the help of priorities on the rules. An i ..."
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Cited by 248 (28 self)
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reasoning, Extended logic programming, Legal reasoning, Defeasible priorities Introduction W...
Fuzzy Argumentation and Extended Logic Programming
- In Proceedings of ECSQARU Workshop Adventures in Argumentation
, 2001
"... We define a fuzzy version of extended logic programming under well-founded semantics with explicit negation. We develop a fuzzy fixpoint argumentation semantics and an efficient, top-down, goal-directed proof procedure. We show that the procedure is sound and complete with respect to the argumentati ..."
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Cited by 9 (1 self)
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We define a fuzzy version of extended logic programming under well-founded semantics with explicit negation. We develop a fuzzy fixpoint argumentation semantics and an efficient, top-down, goal-directed proof procedure. We show that the procedure is sound and complete with respect
Preferred Answer Sets for Extended Logic Programs
- ARTIFICIAL INTELLIGENCE
, 1998
"... In this paper, we address the issue of how Gelfond and Lifschitz's answer set semantics for extended logic programs can be suitably modified to handle prioritized programs. In such programs an ordering on the program rules is used to express preferences. We show how this ordering can be used ..."
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Cited by 158 (20 self)
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In this paper, we address the issue of how Gelfond and Lifschitz's answer set semantics for extended logic programs can be suitably modified to handle prioritized programs. In such programs an ordering on the program rules is used to express preferences. We show how this ordering can be used
Argumentation for Distributed Extended Logic Programs
, 1997
"... Argumentation semantics in extended logic programming has been defined in [5, 12] for a single agent which determines its believes by an internal argumentation process. In this paper we extend the argumentation framework for a multi-agent setting [13] including cooperation. We present an algorit ..."
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Argumentation semantics in extended logic programming has been defined in [5, 12] for a single agent which determines its believes by an internal argumentation process. In this paper we extend the argumentation framework for a multi-agent setting [13] including cooperation. We present
Strategies for Learning with Extended Logic Programs
, 1998
"... We discuss the adoption of a three-valued setting for inductive concept learning. Distinguishing between what is true, what is false and what is unknown can be useful in situations where decisions have to be taken on the basis of scarce information. In a three-valued setting, we learn a definit ..."
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definition for both the target concept and its opposite, considering positive and negative examples as instances of two disjoint classes. To this purpose, we adopt extended logic programs under a well-founded semantics as the representation formalism for learning.
Temporally Annotated Extended Logic Programs
"... Abstract — Extended logic programs (ELPs) are a set of logic rules with strong negation � allowed in the bodies or head of the rules and weak negation ~ allowed in the bodies of the rules. ELPs enable for various forms of reasoning that cannot be achieved by definite logic programs. Answer Set Progr ..."
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Abstract — Extended logic programs (ELPs) are a set of logic rules with strong negation � allowed in the bodies or head of the rules and weak negation ~ allowed in the bodies of the rules. ELPs enable for various forms of reasoning that cannot be achieved by definite logic programs. Answer Set
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