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Can Neural Networks Learn Symbolic Rewriting?

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arxiv 1911.04873 v2 pith:YDSYRIQA submitted 2019-11-07 cs.AI cs.CLcs.LG

Bartosz Piotrowski , Josef Urban , Chad E. Brown , Cezary Kaliszyk This is my paper
classification cs.AIcs.CLcs.LG
keywords neuralcurrentproposedresearchrewritingsymbolicadequatearchitectures
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This work investigates if the current neural architectures are adequate for learning symbolic rewriting. Two kinds of data sets are proposed for this research -- one based on automated proofs and the other being a synthetic set of polynomial terms. The experiments with use of the current neural machine translation models are performed and its results are discussed. Ideas for extending this line of research are proposed, and its relevance is motivated.

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