NDProp learns decision heuristics via neural networks and fuzzy propagation to compute stable models in ASP, improving accuracy and scalability over prior neuro-symbolic methods.
Ross, and John S
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
SCFO(ID) is a sequent calculus for FO(ID) that handles general non-monotone inductive definitions by adapting stable semantics ideas from logic programming.
Presents sound abstract interpretation plus controlled unsoundness techniques to produce tighter, efficient, terminating approximations of fixed points for non-monotone processes.
citing papers explorer
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Neural Decision-Propagation for Answer Set Programming
NDProp learns decision heuristics via neural networks and fuzzy propagation to compute stable models in ASP, improving accuracy and scalability over prior neuro-symbolic methods.
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A Sequent Calculus for General Inductive Definitions
SCFO(ID) is a sequent calculus for FO(ID) that handles general non-monotone inductive definitions by adapting stable semantics ideas from logic programming.
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Bounding Fixed Points of Non-Monotone Processes: Theory to Practice
Presents sound abstract interpretation plus controlled unsoundness techniques to produce tighter, efficient, terminating approximations of fixed points for non-monotone processes.