
Translating AnswerSet Programs into BitVector Logic
Answer set programming (ASP) is a paradigm for declarative problem solvi...
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Interval Structure: A Framework for Representing Uncertain Information
In this paper, a unified framework for representing uncertain informatio...
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Belief Base Revision for Further Improvement of Unified Answer Set Programming
A belief base revision is developed. The belief base is represented usin...
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Characterizing and Extending Answer Set Semantics using Possibility Theory
Answer Set Programming (ASP) is a popular framework for modeling combina...
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Smodels: A System for Answer Set Programming
The Smodels system implements the stable model semantics for normal logi...
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Module Theorem for The General Theory of Stable Models
The module theorem by Janhunen et al. demonstrates how to provide a modu...
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Semantic Reasoning with Differentiable Graph Transformations
This paper introduces a differentiable semantic reasoner, where rules ar...
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A Unified Framework for Nonmonotonic Reasoning with Vagueness and Uncertainty
An answer set programming paradigm is proposed that supports nonmonotonic reasoning with vague and uncertain information. The system can represent and reason with prioritized rules, rules with exceptions. An iterative method for answer set computation is proposed. The terminating conditions are identified for a class of logic programs using the notion of difference equations. In order to obtain the difference equations the set of rules are depicted by a signalflowgraph like structure.
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