Rough set reasoning using answer set programs

DOI10.1016/j.ijar.2020.12.010zbMath1487.68228OpenAlexW3111791439MaRDI QIDQ2237125

Patrick Doherty, Andrzej Szałas

Publication date: 27 October 2021

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2020.12.010

zbMATH Keywords

rough setsknowledge representationapproximate reasoninganswer set programming

Mathematics Subject Classification ID

Knowledge representation (68T30) Reasoning under uncertainty in the context of artificial intelligence (68T37) Logic programming (68N17)

Related Items (2)

Many-valued dynamic object-oriented inheritance and approximations ⋮ A landscape and implementation framework for probabilistic rough sets using \textsc{ProbLog}

Uses Software

• ASSAT
• Cmodels
• DLV
• clasp
• ASPTools

Cites Work

• ASSAT: computing answer sets of a logic program by SAT solvers
• Rudiments of rough sets
• A logic for default reasoning
• Sound and efficient closed-world reasoning for planning
• Extending and implementing the stable model semantics
• Rough set approach to incomplete information systems
• Rough sets. Mathematical foundations
• Kleene algebras and logic: Boolean and rough set representations, 3-valued, rough set and perp semantics
• Knowledge representation techniques. A rough set approach.
• Orthopairs: A Simple and Widely UsedWay to Model Uncertainty
• Rough sets
• Knowledge Representation, Reasoning and Declarative Problem Solving
• Stability, Supportedness, Minimality and Kleene Answer Set Programs
• The DLV system for knowledge representation and reasoning
• Rough Sets and Current Trends in Computing
• Three-Valued Logics, Uncertainty Management and Rough Sets
• Incomplete information: Structure, inference, complexity
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