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Learning and reasoning with graph data
Frontiers in Artificial Intelligence, 2023 Reasoning about graphs, and learning from graph data is a field of artificial intelligence that has recently received much attention in the machine learning areas of graph representation learning and graph neural networks.
Manfred Jaeger
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Abella: A System for Reasoning about Relational Specifications
Journal of Formalized Reasoning, 2014 The Abella interactive theorem prover is based on an intuitionistic logic that allows for inductive and co-inductive reasoning over relations. Abella supports the λ-tree approach to treating syntax containing binders: it allows simply typed λ-terms to be
David Baelde +6 more
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Logic programs as specifications in the inductive verification of logic programs
Electronic Notes in Theoretical Computer Science, 2001 AbstractIn this paper we define a new verification method based on an assertion language able to express properties defined by the user through a logic program. We first apply the verification framework defined in [3] to derive sufficient inductive conditions to prove partial correctness.
Comini M, GORI, ROBERTA, Levi G.
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BMC Bioinformatics, 2012 Background There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically
A Santos Jose C +4 more
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Logical Rule-Based Knowledge Graph Reasoning: A Comprehensive Survey
Mathematics, 2023 With its powerful expressive capability and intuitive presentation, the knowledge graph has emerged as one of the primary forms of knowledge representation and management.
Zefan Zeng, Qing Cheng, Yuehang Si
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Induction of constraint logic programs [PDF]
, 1998 Inductive Logic Programming (ILP) is concerned with learning hypotheses from examples, where both examples and hypotheses are represented in the Logic Programming (LP) language. The application of ILP to problems involving numerical information has shown the need for basic numerical background knowledge (e.g. relation “less than”).
Sebag, Michèle +2 more
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ChemSusChem, Volume 16, Issue 2, January 20, 2023., 2023 Keep dry: Ni‐rich layered oxide cathodes are highly promising for high‐energy lithium‐ion batteries, and their aqueous electrode manufacturing is attractive regarding sustainability and recycling aspects. However, aqueous processing of these materials is challenging due to surface reconstruction. Here, it is shown that Li2SO4 as processing additive can
Marcel Heidbüchel +6 more
wiley +1 more source
Inductive assertion method for logic programs [PDF]
Theoretical Computer Science, 1988 AbstractCertain properties of logic programs are inexpressible in terms of their declarative semantics. One example of such properties would be the actual form of procedure calls and successes which occur during computations of a program. They are often used by programmers in their informal reasoning.
Wlodzimierz Drabent, Jan Maluszynski
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The Curriculum Journal, Volume 34, Issue 1, Page 156-172, March 2023., 2023 Abstract In June 2020, the world witnessed an upsurge in Black Lives Matter (BLM) demonstrations following the murder of George Floyd, an African American, by a White American police officer. The international response called for the global community to reassess the value of black lives blighted by racist social systems.
Sharon Walker +4 more
wiley +1 more source
The Logic of Logic Programming [PDF]
arXiv, 2023 Our position is that logic programming is not programming in the Horn clause sublogic of classical logic, but programming in a logic of (inductive) definitions. Thus, the similarity between prototypical Prolog programs (e.g., member, append, ...) and how inductive definitions are expressed in mathematical text, is not coincidental but essential.
arxiv