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Dyna: Extending Datalog for Modern AI

  • Conference paper
Datalog Reloaded (Datalog 2.0 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6702))

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Abstract

Modern statistical AI systems are quite large and complex; this interferes with research, development, and education. We point out that most of the computation involves database-like queries and updates on complex views of the data. Specifically, recursive queries look up and aggregate relevant or potentially relevant values. If the results of these queries are memoized for reuse, the memos may need to be updated through change propagation. We propose a declarative language, which generalizes Datalog, to support this work in a generic way. Through examples, we show that a broad spectrum of AI algorithms can be concisely captured by writing down systems of equations in our notation. Many strategies could be used to actually solve those systems. Our examples motivate certain extensions to Datalog, which are connected to functional and object-oriented programming paradigms.

This chapter has been condensed for publication; the full version is available as [22]. This material is based on work supported by the National Science Foundation under Grants No. 0347822 and 0964681 to the first author, and by a graduate fellowship to the second author from the Human Language Technology Center of Excellence, Johns Hopkins University.We thank Wren N. G. Thornton and John Blatz for many stimulating discussions. We also thank Yanif Ahmad, Adam Teichert, Jason Smith, Nicholas Andrews, and Veselin Stoyanov for timely comments on the writing.

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Authors and Affiliations

  1. Computer Science Department, Johns Hopkins University, 3400 N. Charles Ave., Baltimore, MD, 21218, USA

    Jason Eisner & Nathaniel W. Filardo

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  1. Jason Eisner
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  2. Nathaniel W. Filardo
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Editors and Affiliations

  1. Department of Computer Science, Oxford University, Wolfson Building, Parks Road, OX1 3QD, Oxford, UK

    Oege de Moor

  2. Department of Computer Science, University of Oxford, UK

    Georg Gottlob , Tim Furche  & Andrew Sellers ,  & 

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Eisner, J., Filardo, N.W. (2011). Dyna: Extending Datalog for Modern AI. In: de Moor, O., Gottlob, G., Furche, T., Sellers, A. (eds) Datalog Reloaded. Datalog 2.0 2010. Lecture Notes in Computer Science, vol 6702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24206-9_11

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  • DOI: https://doi.org/10.1007/978-3-642-24206-9_11

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