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Semiring Programming: A Declarative Framework for Generalized Sum Product Problems
arXiv - CS - Logic in Computer Science Pub Date : 2016-09-21 , DOI: arxiv-1609.06954
Vaishak Belle; Luc De Raedt

To solve hard problems, AI relies on a variety of disciplines such as logic, probabilistic reasoning, machine learning and mathematical programming. Although it is widely accepted that solving real-world problems requires an integration amongst these, contemporary representation methodologies offer little support for this. In an attempt to alleviate this situation, we introduce a new declarative programming framework that provides abstractions of well-known problems such as SAT, Bayesian inference, generative models, and convex optimization. The semantics of programs is defined in terms of first-order structures with semiring labels, which allows us to freely combine and integrate problems from different AI disciplines.
更新日期:2020-01-14

 

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