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Preface to special issue on Inductive Logic Programming, ILP 2017 and 2018 [PDF]
, 2019 Inductive Logic Programming (ILP) is a field at the intersection of Machine Learning and Logic Programming, based on logic as a uniform representation language for expressing examples, background knowledge and ...
Nicolas Lachiche +9 more
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Conflict-Driven Inductive Logic Programming [PDF]
Theory and Practice of Logic Programming, 2022 AbstractThe goal of inductive logic programming (ILP) is to learn a program that explains a set of examples. Until recently, most research on ILP targeted learning Prolog programs. The ILASP system instead learns answer set programs (ASP). Learning such expressive programs widens the applicability of ILP considerably; for example, enabling preference ...
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Few-Shot Induction of Generalized Logical Concepts via Human Guidance
Frontiers in Robotics and AI, 2020 We consider the problem of learning generalized first-order representations of concepts from a small number of examples. We augment an inductive logic programming learner with 2 novel contributions.
Mayukh Das +3 more
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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”).
Michèle Sebag +2 more
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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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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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Using inductive logic programming to discover knowledge hidden in chemical data [PDF]
, 1998 This paper demonstrates how general purpose tools from the field of Inductive Logic Programming (ILP) can be applied to analytical chemistry. As far as these authors are aware, this is the first published work to describe the application of the ILP tool ...
Adam, AE +3 more
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A Curry-Howard Correspondence for Linear, Reversible Computation [PDF]
Logical Methods in Computer ScienceIn this paper, we present a linear and reversible programming language with inductives types and recursion. The semantics of the languages is based on pattern-matching; we show how ensuring syntactical exhaustivity and non-overlapping of clauses is ...
Kostia Chardonnet +2 more
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Answer Set Programming for Regular Inference
Applied Sciences, 2020 We propose an approach to non-deterministic finite automaton (NFA) inductive synthesis that is based on answer set programming (ASP) solvers. To that end, we explain how an NFA and its response to input samples can be encoded as rules in a logic program.
Wojciech Wieczorek +2 more
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, 2022 S.58-73For many tasks in fields like computer vision, computational biology and information extraction, popular probabilistic inference methods have been devised mainly for propositional models that contain only unary and pairwise clique potentials.
Kersting, Kristian +4 more
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