Explanatory Learning: Beyond Empiricism in Neural Networks. (arXiv:2201.10222v1 [cs.LG])

We introduce Explanatory Learning (EL), a framework to let machines use
existing knowledge buried in symbolic sequences -- e.g. explanations written in
hieroglyphic -- by autonomously learning to interpret them. In EL, the burden
of interpreting symbols is not left to humans or rigid human-coded compilers,
as done in Program Synthesis. Rather, EL calls for a learned interpreter, built
upon a limited collection of symbolic sequences paired with observations of
several phenomena. This interpreter can be used to make predictions …

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