Grammar learning

cosmos 1st November 2017 at 5:30pm
Formal grammar Machine learning

aka automata learning

The task of learning a Formal grammar.

At the time of Chomsky's paper, I was trying to find a satisfactory utility evaluation function for my own system. I continued working on this with no great success until 1958, when I decided to look at Chomsky's paper more closely. It was easy for me to understand and build upon. In a short time, I devised a fast left to right parser for context free languages and an extremely fast matrix parser for context sensitive languages It took advantage of special 32 bit parallel processing instructions that most computers have My main interest, however, was learning. I was trying to find an algo rithm for the discovery of the "best" grammar for a given set of acceptable sentences. One of the things sought for: Given a set of positive cases of ac ceptable sentences and several grammars, any of which is able to generate all of the sentences what goodness of fit criterion should be used? It is clear that the "Ad-hoc grammar that lists all of the sentences in the corpus, fits perfectly. The "promiscuous grammar" that accepts any conceivable sentence also fits perfectly. The first grammar has a long description, the second has a short description. It seemed that some grammar half way between these, was but what criterion should be used? correct There are other modes of learning in which the "goodness of fit" criterion is clearer

https://books.google.co.uk/books?hl=en&lr=&id=XAOE5V9B4dUC&oi=fnd&pg=PR9&ots=rbA1pmUJgB&sig=wjS3fuyps3_LPb3YH6hoSaz6zIY#v=onepage&q&f=false

http://link.springer.com/chapter/10.1007/3-540-33486-6_7#page-1

See Evolving automata

Cryptographic limitations on learning boolean formulae and finite automata