Relational Program Synthesis with Numerical Reasoning

نویسندگان

چکیده

Learning programs with numerical values is fundamental to many AI applications, including bio-informatics and drug design. However, current program synthesis approaches struggle learn values. An especially difficult problem learning continuous from multiple examples, such as intervals. To overcome this limitation, we introduce an inductive logic programming approach which combines relational reasoning. Our approach, call NumSynth, uses satisfiability modulo theories solvers efficiently can identify in linear arithmetic fragments, real difference logic, infinite domains, numbers or integers. experiments on four diverse game playing synthesis, show that our (i) arithmetical reasoning, (ii) outperform existing terms of predictive accuracies times.

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ژورنال

عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence

سال: 2023

ISSN: ['2159-5399', '2374-3468']

DOI: https://doi.org/10.1609/aaai.v37i5.25790