Titlebook: Inductive Logic Programming; 30th International C Nikos Katzouris,Alexander Artikis Conference proceedings 2022 Springer Nature Switzerland

谄媚于性

Automatic Conjecturing of P-Recursions Using Lifted Inference,mated fashion, by casting them as first-order model counting problems. Algorithms for this problem typically output a single number, which is the number of models of the first-order logic sentence in question on a given domain. However, in the combinatorics setting, we are more interested in obtaini

octogenarian

Machine Learning of Microbial Interactions Using Abductive ILP and Hypothesis Frequency/Compressioncrobiota. Many statistical approaches have been proposed to infer these interactions from microbial abundance information. However, these statistical approaches have no general mechanisms for incorporating existing ecological knowledge in the inference process. We propose an Abductive/Inductive Logi

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制定法律

Synthetic Datasets and Evaluation Tools for Inductive Neural Reasoning,e induction process. However, we argue that existing datasets and evaluation approaches are lacking in various dimensions; for example, different kinds of rules or dependencies between rules are neglected. Moreover, for the development of neural approaches, we need large amounts of data to learn fro

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遗传学

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Programmatic Policy Extraction by Iterative Local Search,interpretable, amenable to formal verification, or generalize better. While efficient algorithms for learning neural policies exist, learning programmatic policies is challenging. Combining imitation-projection and dataset aggregation with a local search heuristic, we present a simple and direct app